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Colombo, Rinaldo M., Francesca Marcellini, and Michel Rascle. "A 2-Phase Traffic Model Based on a Speed Bound." SIAM Journal on Applied Mathematics 70, no. 7 (January 2010): 2652–66. http://dx.doi.org/10.1137/090752468.
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COLOMBO, RINALDO M., PAOLA GOATIN, and BENEDETTO PICCOLI. "ROAD NETWORKS WITH PHASE TRANSITIONS." Journal of Hyperbolic Differential Equations 07, no. 01 (March 2010): 85–106. http://dx.doi.org/10.1142/s0219891610002025.
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This paper is devoted to a hyperbolic 2-phase model for traffic flow on a network. The model is rigorously described and the existence of solutions is proved, without any restriction on the network geometry.
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Bin, Lv. "Modeling of Signal Plans for Transit Signal Priority at Isolated Intersections under Stochastic Condition." Mathematical Problems in Engineering 2012 (2012): 1–10. http://dx.doi.org/10.1155/2012/650242.
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Transit signal priority (TSP) is recognized as having the potential to improve transit service reliability at small cost to general traffic. The popular preference for TSP encounters the challenges of various and challenging test scenarios. According to the stochastic characteristics of traffic flow, the signal timing model was established for TSP at an isolated signal intersection, where the passenger average delay was used as the optimization objective, and the weights of all phases were considered. The priority logic that is considered in the study provides cycle length and green time within a fixed-time traffic signal control environment. Using the Gauss elimination, the quantitative relationships were determined between phase clearance reliability (PCR), cycle length, and green time. Simulation experiments conducted by the particle swarm optimization (PSO) algorithm indicated that (1) the random variation of arrival rate has an obvious effect on traffic signal settings; (2) the proposed TSP model can reduce passenger delays, especially under stochastic traffic flow.
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Enayatollahi, Fatemeh, and M. A. Amiri Atashgah. "WIND EFFECT ANALYSIS ON AIR TRAFFIC CONGESTION IN TERMINAL AREA VIA CELLULAR AUTOMATA." Aviation 22, no. 3 (November 22, 2018): 102–14. http://dx.doi.org/10.3846/aviation.2018.6252.
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The behavior of any traffic flow is sensitive to the speed pattern of the vehicles involved. The heavier the traffic, the more sensitive the behavior is to speed changes. Focusing on air traffic flow, weather condition has a major role in the deviations of aircraft operational speed from the desired speed and causes surplus delays. In this paper, the effects of wind on delays in a terminal area are analyzed using a Cellular Automaton (CA) model. Cellular automata are discrete models that are widely used for simulating complex emerging properties of dynamic systems. A one-dimensional cellular array is used to model the flow of the terminal traffic into a wind field. The proposed model, due to the quickness and acceptable level of accuracy, can be utilized online in the tactical phase of air traffic control processes and system-level decision-makings, where quick response and system behavior are needed. The modeled route is an RNAV STAR route to Atlanta International Airport. The model is verified by real traffic data in a non-delayed scenario. Based on simulation results, the proposed model exhibits an acceptable level of accuracy (3–15% accuracy drop), with worthy time and computational efficiency (about 2.9 seconds run time for a 2-hour operation).
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He, Shuxian, Haihang Han, Huan Zhang, Shanzhi Sun, and Tony Z. Qiu. "Connected Transit Bus Dynamic Priority Weight Modeling and Conflicting Request Resolution Control at the Signalized Intersection." Journal of Advanced Transportation 2022 (December 6, 2022): 1–22. http://dx.doi.org/10.1155/2022/1550015.
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Multiaccess edge computing (MEC) and connected vehicle (CV) technologies have shown great potential and strength for traffic perception and real-time computing, which can be applied to enhance the efficiency of connected transit bus operations under their lower penetration conditions. Moreover, for the transit signal priority system, how to establish a model to measure traffic demand for conflicting priority request resolution and improve system response time has been widely researched for the last few decades. This paper proposes a dynamic priority weight (DPW) model for connected transit buses and a traffic signal control approach to coordinate multidirectional conflicting priority requests at a signalized intersection. The proposed model takes advantage of vehicle location, speed, and signal timing data to build time to change (TTOC) correlation functions to measure priority weights of both single-vehicle and directionality accumulation with consideration of vehicles arriving during the current green phase and conflict phase conditions; then, the aggregated priority weight value of each movement can be calculated in real-time. Once the maximum aggregated priority weight value among all movements is determined, the corresponding phase switch strategy is presented for the conflicting request resolution control problem. Homologous algorithm software for distributed deployment can be subsequently used for swift response. Simulation results show that the proposed DPW model-based traffic signal control method shows significant performance advancement, where the queueing vehicle number decrease exceeds 1 pcu/s and the throughput rate of major movements increases by approximately 2% without sacrificing the performance of minor movements in a large amount. What is more, it shows better delay optimization for social vehicles than the algorithm with delay as the objective while declining bus delay appreciable quantity with 43.4 s in average. Field test results also show that this method has excellent abilities to improve intersectional traffic capacity, for which queueing vehicle number and throughput rate indicators of all phases dramatically improved with 1.92 pcu/s and 6.68% on average, except for a slight degradation of individual minor traffic movements with 0.99 pcu/s and 0.11%.
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Xia, Lihong, Penghui Li, Zhizhuo Su, Tao Chen, Zhaoxiang Deng, and Dihua Sun. "Longitudinal Driving Behavior before, during, and after a Left-Turn Movement at Signalized Intersections: A Naturalistic Driving Study in China." Sustainability 14, no. 18 (September 16, 2022): 11630. http://dx.doi.org/10.3390/su141811630.
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A human-like driving model can help to improve the acceptance and safety of automated driving systems (ADS). To improve the performance of human-like driving and interaction with conventional vehicles of ADS, the speed behavior of left-turn vehicles at the signalized intersection was studied using natural driving data. In this study, 374 valid data points of left-turn snippets at signalized intersections were extracted and three phases were introduced based on the reaction behavior of braking, stopping, and accelerating in the left-turn process. Firstly, a one-way ANOVA was used to study the influence of traffic density, traffic light state, intersection type, and left-turn waiting area on the reaction position of each phase and the spatial distribution of the speed. The traffic light state and traffic density were the main significant effects. Furthermore, to analyze the spatial distribution of acceleration, a method of frequency contour was conducted. The butterfly-shaped frequency contour suggested that “the closer to the stop line, the higher the variation of acceleration”. Finally, the driving parameters at each phase were further analyzed. The main results indicate the following: (1) The red traffic light will lead to a larger variation of acceleration, a larger maximum deceleration, a larger starting acceleration, and a larger maximum acceleration. (2) On the condition of dense traffic density, more stops and the duration of the stop–go phase may cause the time pressure, and the driver tends to choose a greater maximum acceleration. (3) The red traffic light leads to a further reaction distance of all three phases, whilst increased traffic density only increases the reaction distance of the stop. (4) Both the dense traffic density and red traffic light lead to an earlier reaction time. The findings can provide a basis for the design of human-like driving of left-turn driving assistance systems and improve the interaction with left-turn conventional vehicles.
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Yu, Lei, Peng Yue, and Hualiang Teng. "Comparative Study of EMME/2 and QRS II for Modeling a Small Community." Transportation Research Record: Journal of the Transportation Research Board 1858, no. 1 (January 2003): 103–11. http://dx.doi.org/10.3141/1858-15.
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The availability of so many computer-based travel-demand forecasting models provides transportation planners with powerful and flexible tools in the modeling phase of their planning or traffic-impact studies, but it has confused users in the selection of an appropriate model for a particular study. It is commonly recognized that none of the existing travel-demand models is perfectly suited for all network scenarios and traffic conditions. A particular model that is strong in one application scenario may be weak in a different application scenario. A comparative study is presented of two widely used travel-demand forecasting models, EMME/2 and QRS II, for applications to a small community. A structural comparison is performed, and a real-world small network is modeled by EMME/2 and QRS II to identify specific features and limitations of each model. Areas for comparison include model structure, drawing of the network, data input, network modification, parameter calibration, and modeling output. The study does not recommend either model to transportation planners for a practical application to a small community. Instead, the study identifies the major differences and common features of two models, which can help planners understand what they can expect from a certain model when they choose to use it.
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Echab, H., and H. Ez-Zahraouy. "Dynamic characteristics of traffic flow with consideration of crossing pedestrians’ behavior at a nonsignalized T-shaped intersection." International Journal of Modern Physics C 28, no. 11 (November 2017): 1750134. http://dx.doi.org/10.1142/s0129183117501340.
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In this paper, we present a cellular automata model to depict the traffic characteristics at such a nonsignalized [Formula: see text]-shaped intersection in the presence of pedestrian crossings. The vehicular traffic flow characteristics with different parameters are studied. Throughput, phase diagrams, space-time and density profiles are built to point various traffic states and the phase transition features. The principal finding of the simulation are as follows: (1) The presence of crossing pedestrians has a significant influence on the vehicular traffic and the system performance, (2) The intersection capacity has a close relevance with the state of the weaving section. The smaller the interactions are at the weaving section, the higher the capacity and (3) In order to have a higher system ability, the crosswalk location should not be far from the yield line of the weaving section.
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Ahac, Saša, Maja Ahac, Josipa Domitrović, and Vesna Dragčević. "Modeling the Influence of Roundabout Deflection on Its Efficiency as a Noise Abatement Measure." Sustainability 13, no. 10 (May 12, 2021): 5407. http://dx.doi.org/10.3390/su13105407.
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Challenges that emerge in roundabout design are mostly related to space constrictions and provision of appropriate deflection around the central island. This can result in speed profiles on roundabouts that might reduce their potential as a noise abatement measure. Because of this, the impact of a roundabout on noise levels and its applicability as a traffic calming device and a noise abatement measure should be investigated in the early design stage, by modeling noise levels. In this paper, the following hypothesis is tested: vehicle movement trajectories, defined during the fastest path performance check in roundabout early design phase, can be used as the road traffic noise sources when modeling noise at roundabouts using static noise model. This procedure (1) simplifies the preparation of the noise model, (2) results in a model that is closer to the real-world in terms of traffic flow conditions, (3) allows the noise calculations in the early stages of roundabout design, and (4) includes the influence of roundabout deflection on calculated noise levels. The abovementioned simplifications of the road traffic noise modeling process should encourage the optimization of roundabout geometry in terms of its noise reduction capabilities in the preliminary design phase of these intersections.
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Huang, Jianchang, Guohua Song, Jianbo Zhang, Zufen Li, Yizheng Wu, and Lei Yu. "The Impact of Pedestrian and Nonmotorized Vehicle Violations on Vehicle Emissions at Signalized Intersections in the Real World: A Case Study in Beijing." Journal of Advanced Transportation 2021 (March 2, 2021): 1–11. http://dx.doi.org/10.1155/2021/8849234.
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Emission around intersections has become an issue in the urban traffic network. This paper aims to investigate the impact of pedestrian and nonmotorized vehicle violations on emissions at mixed-traffic flow intersection based on the volumes of vehicles, nonmotor vehicles, and pedestrians. Also, it focuses on the arterial and collector intersections with high vehicle volume and limited space. Running red light and crossing intersection diagonally are two critical violations, accounting for 91.75% of effective violations (interference with vehicles’ operation). In this context, a violation blocking model is developed to estimate the blocking probability for each vehicle based on the volumes of pedestrians and nonmotor vehicles. The model includes two scenarios. (1) Through phase: the violation blocking model of running red light is developed based on the survival curve (the relationship between waiting time and running red light probability). (2) Left-turn phase: the violation blocking model at this phase includes two parts: (i) crossing the intersection diagonally model is developed for the first vehicle and (ii) running red light model is developed for subsequent vehicles. The existing emission model can estimate the emissions based on the blocking positions. In the case study, emissions increase with the vehicle volume approaching the saturated flow rate and the volumes of nonmotor vehicles and pedestrians increasing. Results show that the maximum emission increase of CO (carbon monoxide) for through phase and left-turn phase can reach 16.7% and 36.4%.
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Ghosh, Laura E., Liqun Lu, Hasan Ozer, Yanfeng Ouyang, and Imad L. Al-Qadi. "Effects of Pavement Surface Roughness and Congestion on Expected Freeway Traffic Energy Consumption." Transportation Research Record: Journal of the Transportation Research Board 2503, no. 1 (January 2015): 10–19. http://dx.doi.org/10.3141/2503-02.
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In life-cycle assessments of roadway infrastructure projects, the significant amount of energy consumed during the use phase has been largely ignored when decisions related to roadway construction and rehabilitation have been evaluated. Traffic congestion, pavement types, and surface roughness conditions affect energy consumption throughout the use phase. This study developed an integrated modeling framework that accounted for the effects of pavement roughness degradation on estimated energy consumption for freeways and other restricted access highways, considering vehicle types and traffic growth, as well as congestion patterns. The framework was achieved through three interdependent modules: Module 1 estimated vehicle specific power (VSP) by relating the International Roughness Index (IRI) of pavements to coefficients used in the Environmental Protection Agency's motor vehicle emission simulator, Module 2 used the state-of-the-art cell transmission model to predict traffic evolution and congestion on the freeway and determined the total vehicle miles traveled at a spectrum of speed ranges, and Module 3 estimated energy consumption from an IRI profile, VSP coefficients, and traffic speed–miles profile. A case study confirmed that IRI and congestion had significant impacts on estimates of energy consumption during the use phase. The study showed that ignoring IRI variation or traffic congestion could lead to underestimations in VSP by up to 2.5% and energy consumption by approximately 6%.
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Wang, Baojie, Wei Wang, Xiaojian Hu, and Xiaowei Li. "A Segmented Signal Progression Model for the Modern Streetcar System." Discrete Dynamics in Nature and Society 2015 (2015): 1–10. http://dx.doi.org/10.1155/2015/763565.
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This paper is on the purpose of developing a segmented signal progression model for modern streetcar system. The new method is presented with the following features: (1) the control concept is based on the assumption of only one streetcar line operating along an arterial under a constant headway and no bandwidth demand for streetcar system signal progression; (2) the control unit is defined as a coordinated intersection group associated with several streetcar stations, and the control joints must be streetcar stations; (3) the objective function is built to ensure the two-way streetcar arrival times distributing within the available time of streetcar phase; (4) the available time of streetcar phase is determined by timing schemes, intersection structures, track locations, streetcar speeds, and vehicular accelerations; (5) the streetcar running speed is constant separately whether it is in upstream or downstream route; (6) the streetcar dwell time is preset according to historical data distribution or charging demand. The proposed method is experimentally examined in Hexi New City Streetcar Project in Nanjing, China. In the experimental results, the streetcar system operation and the progression impacts are shown to affect transit and vehicular traffic. The proposed model presents promising outcomes through the design of streetcar system segmented signal progression, in terms of ensuring high streetcar system efficiency and minimizing negative impacts on transit and vehicular traffic.
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Sowlat, Mohammad Hossein, Sina Hasheminassab, and Constantinos Sioutas. "Source apportionment of ambient particle number concentrations in central Los Angeles using positive matrix factorization (PMF)." Atmospheric Chemistry and Physics 16, no. 8 (April 20, 2016): 4849–66. http://dx.doi.org/10.5194/acp-16-4849-2016.
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Abstract. In this study, the positive matrix factorization (PMF) receptor model (version 5.0) was used to identify and quantify major sources contributing to particulate matter (PM) number concentrations, using PM number size distributions in the range of 13 nm to 10 µm combined with several auxiliary variables, including black carbon (BC), elemental and organic carbon (EC/OC), PM mass concentrations, gaseous pollutants, meteorological, and traffic counts data, collected for about 9 months between August 2014 and 2015 in central Los Angeles, CA. Several parameters, including particle number and volume size distribution profiles, profiles of auxiliary variables, contributions of different factors in different seasons to the total number concentrations, diurnal variations of each of the resolved factors in the cold and warm phases, weekday/weekend analysis for each of the resolved factors, and correlation between auxiliary variables and the relative contribution of each of the resolved factors, were used to identify PM sources. A six-factor solution was identified as the optimum for the aforementioned input data. The resolved factors comprised nucleation, traffic 1, traffic 2 (with a larger mode diameter than traffic 1 factor), urban background aerosol, secondary aerosol, and soil/road dust. Traffic sources (1 and 2) were the major contributor to PM number concentrations, collectively making up to above 60 % (60.8–68.4 %) of the total number concentrations during the study period. Their contribution was also significantly higher in the cold phase compared to the warm phase. Nucleation was another major factor significantly contributing to the total number concentrations (an overall contribution of 17 %, ranging from 11.7 to 24 %), with a larger contribution during the warm phase than in the cold phase. The other identified factors were urban background aerosol, secondary aerosol, and soil/road dust, with relative contributions of approximately 12 % (7.4–17.1), 2.1 % (1.5–2.5 %), and 1.1 % (0.2–6.3 %), respectively, overall accounting for about 15 % (15.2–19.8 %) of PM number concentrations. As expected, PM number concentrations were dominated by factors with smaller mode diameters, such as traffic and nucleation. On the other hand, PM volume and mass concentrations in the study area were mostly affected by sources with larger mode diameters, including secondary aerosols and soil/road dust. Results from the present study can be used as input parameters in future epidemiological studies to link PM sources to adverse health effects as well as by policymakers to set targeted and more protective emission standards for PM.
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Zegeye, Wondimu, Richard Dean, and Farzad Moazzami. "Multi-Layer Hidden Markov Model Based Intrusion Detection System." Machine Learning and Knowledge Extraction 1, no. 1 (December 25, 2018): 265–86. http://dx.doi.org/10.3390/make1010017.
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The all IP nature of the next generation (5G) networks is going to open a lot of doors for new vulnerabilities which are going to be challenging in preventing the risk associated with them. Majority of these vulnerabilities might be impossible to detect with simple networking traffic monitoring tools. Intrusion Detection Systems (IDS) which rely on machine learning and artificial intelligence can significantly improve network defense against intruders. This technology can be trained to learn and identify uncommon patterns in massive volume of traffic and notify, using such as alert flags, system administrators for additional investigation. This paper proposes an IDS design which makes use of machine learning algorithms such as Hidden Markov Model (HMM) using a multi-layer approach. This approach has been developed and verified to resolve the common flaws in the application of HMM to IDS commonly referred as the curse of dimensionality. It factors a huge problem of immense dimensionality to a discrete set of manageable and reliable elements. The multi-layer approach can be expanded beyond 2 layers to capture multi-phase attacks over longer spans of time. A pyramid of HMMs can resolve disparate digital events and signatures across protocols and platforms to actionable information where lower layers identify discrete events (such as network scan) and higher layers new states which are the result of multi-phase events of the lower layers. The concepts of this novel approach have been developed but the full potential has not been demonstrated.
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Thilo, L., E. Stroud, and T. Haylett. "Maturation of early endosomes and vesicular traffic to lysosomes in relation to membrane recycling." Journal of Cell Science 108, no. 4 (April 1, 1995): 1791–803. http://dx.doi.org/10.1242/jcs.108.4.1791.
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The controversy whether endocytic processing occurs by organellar maturation or by vesicular traffic has not been resolved. It is also not clear whether maturation continues to the stage of lysosomes, to what extent it involves a decrease in organellar fusogenicity, and how it relates to membrane recycling. Maturation and vesicular traffic imply distinct kinetics for the intermingling of endocytic markers after sequential endocytic uptake. We have studied the kinetics of intermingling of fluid-phase markers (fluorescein-labelled dextran and horseradish peroxidase) and cell surface-derived membrane (labelled by galactosylation) in organelles at early and late stages of the endocytic pathway in macrophage-like P388D1 cells. Intermingling declined by sigmoid kinetics, indicating that endosomes matured within about 3 minutes to become non-fusogenic towards early endosomes. During maturation about 60% of internalized membrane was recycled with T1/2 approximately 2 minutes. Whereas matured endosomes were non-fusogenic towards early endosomes and towards each other, a second phase of intermingling was observed upon delivery to lysosomes. This intermingling occurred by a first-order process (T1/2 approximately 4 minutes), concurrent with recycling of the remaining 40% of internalized membrane marker. These kinetic observations suggest a model for endocytic processing which reconciles maturation of early endosomes with the known function of carrier vesicles: Endocytic carrier vesicles do not bud off from permanent early endosomes as proposed for vesicular traffic, but are derived, together with recycling vesicles, from the maturation of early endosomes which are consumed by this process; these carrier vesicles subsequently mediate delivery to lysosomes by vesicular traffic during which the remaining surface-derived membrane is recycled.
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Salamati, Katy, Nagui M. Rouphail, H. Christopher Frey, Bin Liu, and Bastian J. Schroeder. "Simplified Method for Comparing Emissions in Roundabouts and at Signalized Intersections." Transportation Research Record: Journal of the Transportation Research Board 2517, no. 1 (January 2015): 48–60. http://dx.doi.org/10.3141/2517-06.
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An empirically based macroscopic method is presented. It estimates and compares the pollutant emissions generated from signalized intersections and roundabouts. This method was built on a large sample size of real-world second-by-second vehicle trajectories, traffic volumes, and other traffic characteristics collected at signalized intersections and roundabouts in six U.S. states. The basis for predicting and estimating pollutant emissions was the concept of vehicle-specific power. The method enables inclusion of emissions standards and vehicle classes, such as Tier 1 (T1) and Tier 2 (T2) passenger cars (PCs) and passenger trucks (PTs). More than 1,980 vehicle trajectories were analyzed. Traffic variables including intersection capacity, demand-to-capacity ratio ( d/ c), cycle length, green-to-cycle length ratio, signal progression (i.e., arrival type), and number of lanes were included in the model for analysis and comparison between signals and roundabouts. Application of the method to a case study showed that on average under low d/ c (<0.7), roundabouts generated lower emission rates than signalized intersections. As demand approached capacity under high traffic volumes, signalized intersections with favorable progression (i.e., most demand arrived during green phase) generally produced lower emission rates than roundabouts. Signalized intersections with poor progression (i.e., most demand arrived during red phase) generated more emissions than roundabouts. Results also showed that during oversaturation periods (when d/ c > 1), the amount of produced emissions increased steadily in roundabouts but increased a large amount at signals.
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Hammadi, Ayad, and Eric J. Miller. "An agent-based transportation impact sketch planning (TISP) model system." Journal of Transport and Land Use 14, no. 1 (February 14, 2021): 219–53. http://dx.doi.org/10.5198/jtlu.2021.1863.
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A traffic impact sketch planning (TISP) model is presented for the estimation of the likely travel demand generated by a major land-use development or redevelopment project. The proposed approach overcomes the problems with the non-behavioral transportation-related studies used in practice for assessing the development design impacts on the local transportation system. The architectural design of the development, in terms of the number and type of dwellings, by number of bedrooms per unit, and the land-use categories of the non-residential floorspace, are reflected in the TISP model through an integrated population and employment synthesis approach. The population synthesis enables the feasible deployment of an agent-based microsimulation (ABM) model system of daily activity and travel demand for a quick, efficient, and detailed assessment of the transportation impacts of a proposed neighborhood or development. The approach is not restricted to a certain type of dataset of the control variables for the geographic location of the development. Datasets for different geographic dimensions of the study area, with some common control variables, are merged and cascaded into a synthesized, disaggregate population of resident persons, households and jobs. The prototype implementation of the TISP model is for Waterfront Toronto’s Bayside Development Phase 2, using the operational TASHA-based GTAModel V4.1 ABM travel demand model system. While the conventional transportation studies focus on the assessment of the local traffic impacts in the immediate surroundings of the development, the TISP model investigates and assesses many transportation related impacts in the district, city, and region, for both residents and non-residents of the development. TISP model analysis includes the overall spatiotemporal trips distribution generated by the residents and non-residents of the development for the auto and non-auto mobility systems and the simulated agents diurnal peaking travel times. The model results are compared with the trips estimates by a prior project traffic impact study and the Institute of Transportation Engineers (ITE) Trip Generation Manual (TGM) rates of weekday trips for the relevant land uses. Future extensions and improvements of the model including the generalization and full automation of the model, and the bi-level macro-micro representation of the transportation network are also discussed.
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Zhang, Xinyu, Hongbo Gao, Chong Xue, Jianhui Zhao, and Yuchao Liu. "Real-time vehicle detection and tracking using improved histogram of gradient features and Kalman filters." International Journal of Advanced Robotic Systems 15, no. 1 (January 1, 2018): 172988141774994. http://dx.doi.org/10.1177/1729881417749949.
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Intelligent transportation systems and safety driver-assistance systems are important research topics in the field of transportation and traffic management. This study investigates the key problems in front vehicle detection and tracking based on computer vision. A video of a driven vehicle on an urban structured road is used to predict the subsequent motion of the front vehicle. This study provides the following contributions. (1) A new adaptive threshold segmentation algorithm is presented in the image preprocessing phase. This algorithm is resistant to interference from complex environments. (2) Symmetric computation based on a traditional histogram of gradient (HOG) feature vector is added in the vehicle detection phase. Symmetric HOG feature with AdaBoost classification improves the detection rate of the target vehicle. (3) A motion model based on adaptive Kalman filter is established. Experiments show that the prediction of Kalman filter model provides a reliable region for eliminating the interference of shadows and sharply decreasing the missed rate.
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Xu, Qing, Jiangfeng Wang, Botong Wang, and Xuedong Yan. "Modeling and simulation of intersection quasi-moving block speed guidance based on connected vehicles." Journal of Intelligent and Connected Vehicles 3, no. 2 (August 10, 2020): 67–78. http://dx.doi.org/10.1108/jicv-01-2020-0002.
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Purpose This study aims to propose a speed guidance model of the CV environment to alleviate traffic congestion at intersections and improve traffic efficiency. By introducing the theory of moving block section for high-speed train control, a speed guidance model based on the quasi-moving block speed guidance (QMBSG) is proposed to direct platoon including human-driven vehicles and connected vehicles (CV) through the intersection coordinately. Design/methodology/approach In this model, the green time of the intersection is divided into multiple block intervals according to the minimal safety headway. Connected vehicles can pass through the intersection by following the block interval using the QMBSG model. The block interval is assigned dynamically according to the traveling relation of HV and CV, when entering the communication range of the intersection. To validate the comprehensive guidance effect of the proposed model, a general evaluation function (GEF) is established. Compared to CVs without speed guidance, the simulation results show that the GEF of QMBSG model has an obvious improvement. Findings Compared to CVs without speed guidance, the simulation results show that the GEF of QMBSG model has an obvious improvement. Also, compared to the single intersection speed guidance model, the GEF value of the QMBSG model improves over 17.1%. To further explore the guidance effect, the impact of sensitivity factors of the CVs’ environment, such as intersection environment, communication range and penetration rate (PR) is analyzed. When the PR reaches 75.0%, the GEF value will change suddenly and the model guidance effect will be significantly improved. This paper also analyzes the impact of the length of block interval under different PR and traffic demands. It is found that the proposed model has a better guidance effect when the length of the block section is 2 s, which facilitates traffic congestion alleviation of the intersection in practice. Originality/value Based on the aforementioned discussion, the contributions of this paper are three-fold. Based on the traveling information of HV/CV and the signal phase and timing plans, the QMBSG model is proposed to direct platoon consisting of HV and CV through the intersection coordinately, by following the block interval assigned dynamically. Considering comprehensively the indexes of mobility, safety and environment, a GEF is provided to evaluate the guidance effect of vehicles through the intersection. Sensitivity analysis is carried out on the QMBSG model. The key communication and traffic parameters of the CV environment are analyzed, such as path attenuation, PR, etc. Finally, the effect of the length of block interval is explored.
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Adamson, Michael, Grant G. Schultz, Mitsuru Saito, and Michael D. Stevens. "Developing Decision Boundaries for Left-Turn Treatments." Transportation Research Record: Journal of the Transportation Research Board 2674, no. 5 (April 23, 2020): 315–26. http://dx.doi.org/10.1177/0361198120915470.
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The purpose of this research was to evaluate the interaction of left-turn and opposing through traffic volumes for permitted and protected left-turn phasing at intersections and develop boundaries that help identify when to switch from permitted to protected phasing at signalized intersections. Permitted phasing allows vehicles to turn left after yielding to opposing vehicles; protected phasing provides an exclusive phase for vehicles to turn left without opposition; and protected-permitted phasing combines these phasing alternatives, allowing both permitted and protected turning movements. Intersections with 1, 2, and 3 opposing-lane configurations with permitted and protected-permitted models (split into green times of 10, 15, and 20 s) were analyzed for a total of 12 simulation models. Each model was divided into 100–225 different volume scenarios, with incremental increases in left-turn and opposing volumes. By exporting trajectory files from VISSIM and importing these into the Surrogate Safety Assessment Model, crossing conflicts for each volume combination in each model were extracted. MATLAB was then used to create contour maps representing the number of crossing conflicts per hour associated with different combinations of left-turn and opposing volume. Basic decision boundaries were examined in each contour map. Statistical analysis software was used to perform a linear regression analysis on transformed data and to develop natural log-based equations that form the decision boundaries for each configuration and phase alternative. These equations were graphed and final decision boundaries developed for the 1-, 2-, and 3-lane configurations between permitted and protected-permitted phasing as well as between protected-permitted and protected phasing.
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Maranzano, Paolo, Alessandro Fassò, Matteo Pelagatti, and Manfred Mudelsee. "Statistical Modeling of the Early-Stage Impact of a New Traffic Policy in Milan, Italy." International Journal of Environmental Research and Public Health 17, no. 3 (February 8, 2020): 1088. http://dx.doi.org/10.3390/ijerph17031088.
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Most urban areas of the Po basin in the North of Italy are persistently affected by poor air quality and difficulty in disposing of airborne pollutants. In this context, the municipality of Milan started a multi-year progressive policy based on an extended limited traffic zone (Area B). Starting on 25 February 2019, the first phase partially restricted the circulation of some classes of highly polluting vehicles on the territory, in particular, Euro 0 petrol vehicles and Euro 0 to 3 diesel vehicles, excluding public transport. This is the early-stage of a long term policy that will restrict access to an increasing number of vehicles. The goal of this paper is to evaluate the early-stage impact of this policy on two specific vehicle-generated pollutants: total nitrogen oxides (NO x ) and nitrogen dioxide (NO 2 ), which are gathered by Lombardy Regional Agency for Environmental Protection (ARPA Lombardia). We use a statistical model for time series intervention analysis based on unobservable components. We use data from 2014 to 2018 for pre-policy model selection and the relatively short period up to September 2019 for early-stage policy assessment. We include weather conditions, socio-economic factors, and a counter-factual, given by the concentration of the same pollutant in other important neighbouring cities. Although the average concentrations reduced after the policy introduction, this paper argues that this could be due to other factors. Considering that the short time window may be not long enough for social adaptation to the new rules, our model does not provide statistical evidence of a positive policy effect for NO x and NO 2 . Instead, in one of the most central monitoring stations, a significant negative impact is found.
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Sun, Lei. "Research on the Connectivity of Network." Applied Mechanics and Materials 568-570 (June 2014): 1412–16. http://dx.doi.org/10.4028/www.scientific.net/amm.568-570.1412.
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Based on the characteristic of real network, this paper introduces traffic routing model, uses the capacity of network to measure the connectivity of network, establishes connectivity research model and finally we analyze the method for determining the capacity of network, and the relation between the connectivity of network with the capacity of each node (C) through simulation. Conclusions are shown as following: (1) It is feasible to use the capacity of network to measure the connectivity of network. (2) The capacity of network is measured by the critical generating rate Rc at which a continuous phase transition will occur from free state to congestion. (3) The connectivity of network is positively related with C, and the capacity of network shows a linear growth with the increasing of C. Results show that this evaluation of connectivity can better reflect the connectivity of real network, and well meets the research needs of real network.
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Arivunambi, Amirthasaravanan, and Arjun Paramarthalingam. "A Study on Two-Phase Monitoring Server for Ransomware Evaluation and Detection in IoT Environment." Journal of Trends in Computer Science and Smart Technology 4, no. 2 (July 13, 2022): 72–82. http://dx.doi.org/10.36548/jtcsst.2022.2.003.
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Current trending- Internet of things (IoT) is internetworking of an assortment of hardware devices to offer a collection of applications and services. In the present-day world, ransomware cyber-attack has become one of the major attacks in IoT systems. Ransomware is a hazardous malware that targets the user’s computer inaccessible or inoperative, and then requesting the computer victim user to transfer a huge ransom to relapse the damage. At instance, the evolution rate outcomes illustrate that the level of attacks such as Locky and Cryptowall ransomware are conspicuously growing then other ransomware. Thus, these ransomware relations are the latent threat to IoT. To address the issue, this paper presents Two-phase ransomware prediction model based on the behavioral and communication study of Cryptowall ransomware for IoT networks. This proposed Two-phase model equipped with, Phase-1: observes the inward TCP/IP flowing traffic through a monitoring server to avert the ransomware attack The procedure of the monitoring server is to monitor the IoT's TCP/IP. The process of Monitoring TCP/IP is to extract TCP/IP header and routines command and control (C&C) server IP blacklisting to discover the ransomware attacks. In Phase-2: the proposed system will also analyze the application pattern for malicious behavior of the Web and URLs. Several societies have very affluent security tools in their milieu, but their events or logs are not monitored, which make affluent tools ineffective. The process of having efficient security based monitoring server is vital for detecting and controlling the ransomware attack.
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Meng, Yang. "Analysis of Performance Improvement of Real-time Internet of Things Application Data Processing in the Movie Industry Platform." Computational Intelligence and Neuroscience 2022 (October 10, 2022): 1–9. http://dx.doi.org/10.1155/2022/5237252.
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The goal of this study is to plan and develop complete strategies to improve the performance of film industry. The primary objectives of this study are to investigate a dataset generated by a IoT application and the nature of the data forms obtained, the speed of the data arriving rate, and the required query response time and to list the issues that the current film industry faces when attempting to handle IoT applications in real time. Finally, in film industry platforms, high performance with varied stream circulation levels of real-time IoT application information was realized. In this study, we proposed three alternative methods on top of the Storm platform, nicknamed Re-Storm, to improve the performance of IoT application data. Three different proposed strategies are (1) data stream graph optimization framework, (2) energy-efficient self-scheduling strategy, and (3) real-time data stream computing with memory DVFS. The work proposed a methodology for dealing with heterogeneous traffic-aware incoming rate of data streams Re-Storm at multiple traffic points, resulting in a short response time and great energy efficiency. It is divided into three parts, the first of which is a scientific model for fast response time and great energy efficiency. The distribution of resources is then considered using DVFS approaches, and successful optimum association methods are shown. Third is self-allocation of worker nodes towards optimizing DSG using hot swapping and making the span minimization technique. Furthermore, the testing findings suggest that Re-Storm outperforms Storm by 20–30% for real-time streaming data of IoT applications. This research focuses on high energy efficiency, short reaction time, and managing data stream traffic arrival rate. A model for a specific phase of data coming via IoT and real-time computing devices was built on top of the Storm platform. There is no need to change any software approach or hardware component in this design, but only merely add an energy-efficient and traffic-aware algorithm. The design and development of this algorithm take into account all of the needs of the data produced by IoT applications. It is an open-source platform with less prerequisites for addressing a more sophisticated big data challenge.
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Chen, Hao, and Hesham A. Rakha. "Battery Electric Vehicle Eco-Cooperative Adaptive Cruise Control in the Vicinity of Signalized Intersections." Energies 13, no. 10 (May 12, 2020): 2433. http://dx.doi.org/10.3390/en13102433.
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This study develops a connected eco-driving controller for battery electric vehicles (BEVs), the BEV Eco-Cooperative Adaptive Cruise Control at Intersections (Eco-CACC-I). The developed controller can assist BEVs while traversing signalized intersections with minimal energy consumption. The calculation of the optimal vehicle trajectory is formulated as an optimization problem under the constraints of (1) vehicle acceleration/deceleration behavior, defined by a vehicle dynamics model; (2) vehicle energy consumption behavior, defined by a BEV energy consumption model; and (3) the relationship between vehicle speed, location, and signal timing, defined by vehicle characteristics and signal phase and timing (SPaT) data shared under a connected vehicle environment. The optimal speed trajectory is computed in real-time by the proposed BEV eco-CACC-I controller, so that a BEV can follow the optimal speed while negotiating a signalized intersection. The proposed BEV controller was tested in a case study to investigate its performance under various speed limits, roadway grades, and signal timings. In addition, a comparison of the optimal speed trajectories for BEVs and internal combustion engine vehicles (ICEVs) was conducted to investigate the impact of vehicle engine types on eco-driving solutions. Lastly, the proposed controller was implemented in microscopic traffic simulation software to test its networkwide performance. The test results from an arterial corridor with three signalized intersections demonstrate that the proposed controller can effectively reduce stop-and-go traffic in the vicinity of signalized intersections and that the BEV Eco-CACC-I controller produces average savings of 9.3% in energy consumption and 3.9% in vehicle delays.
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Hassan, Yasser, Said M. Easa, and A. O. Abd El Halim. "State-of-the-art of three-dimensional highway geometric design." Canadian Journal of Civil Engineering 25, no. 3 (June 1, 1998): 500–511. http://dx.doi.org/10.1139/l97-111.
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Geometric design is an important phase in the highway design process that is directly related to traffic safety. Highway elements should be jointly designed to account for such design criteria as sight distance, vehicle stability, driver comfort, drainage, and aesthetics. Intuitively, such a design should be based on a three-dimensional (3-D) analysis. This paper reviews the current practice and research work related to each design criterion with emphasis on the conformity with the 3-D nature of the highway. Current standards are based mainly on a two-dimensional (2-D) analysis that does not guarantee a satisfactory design. Recently, several research efforts have been expended in the 3-D highway analysis with sight distance being the most researched area. Analytical models and computer software have been developed to accurately model 3-D daytime and nighttime sight distances. Roads designed using current 2-D standards may compromise safety or economy. Different models are currently available to simulate the forces acting on a vehicle in 3-D. These models show that the point-mass formula for modelling vehicle dynamics in the current standards can be inaccurate. Current standards contain recommendations for drainage of surface water, but explicit quantitative coordination of combined alignments is lacking. Furthermore, research is still needed to study the effect of alignment coordination on highway aesthetics and driver's perception of information.Key words: highway geometric design, three-dimensional analysis, sight distance, vehicle dynamics, drainage, highway aesthetics.
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Li, Suoping, Hongli Li, Jaafar Gaber, Sa Yang, and Qian Yang. "Performance Analysis of IEEE 802.11p Protocol in IoV under Error-Prone Channel Conditions." Security and Communication Networks 2023 (February 15, 2023): 1–20. http://dx.doi.org/10.1155/2023/5476836.
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The complexity of the channel condition in the Internet of vehicles (IoV) may increase the bit error rate (BER) of the intelligent vehicle terminals, resulting in data transmission failures or errors. Therefore, it is necessary to improve the performance of communication protocols under error-prone channel conditions. This article investigates the influence of the access categories’ (ACs) performance with channel errors by using four A C s to cause service differentiation based on the enhanced distributed channel access (EDCA) mechanism of the IEEE 802.11p. To address the error-prone characteristics of the channel and unsaturated traffic conditions, a three-dimensional Markov model is developed first, followed by an analysis of the characteristics and mutual transition probabilities of the seven classes of states in the model, and then, the steady-state equations of the system are developed to derive the steady-state distribution to study system performance. The model considers the backoff phase, the freezing of the backoff counter, the retransmission limit, the probability of collisions occurring, the size of the maximum and minimum contention window, and the number of interframe intervals. These parameters are chosen to meet the requirements for the protocol to operate, while also preventing overestimation of throughput and avoiding having packets being served all the time. We derive expressions for the throughput and delay of A C s under the conditions of error channels and unsaturated traffic. The impact of channel errors on the throughput and delay of A C s is evaluated by numerical simulation. Numerical results show that too many stations in the system will increase the average access delay and decrease throughput. The increase in BER will seriously decrease the performance of high-priority A C s . The throughput of the A C s is also modeled to vary with frame length and BER, and the variation curves of the optimal frame lengths for A C 3 and A C 2 were obtained.
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Dalsøren, S. B., B. H. Samset, G. Myhre, J. J. Corbett, R. Minjares, D. Lack, and J. S. Fuglestvedt. "Environmental impacts of shipping in 2030 with a particular focus on the Arctic region." Atmospheric Chemistry and Physics 13, no. 4 (February 20, 2013): 1941–55. http://dx.doi.org/10.5194/acp-13-1941-2013.
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Abstract. We quantify the concentrations changes and Radiative Forcing (RF) of short-lived atmospheric pollutants due to shipping emissions of NOx, SOx, CO, NMVOCs, BC and OC. We use high resolution ship emission inventories for the Arctic that are more suitable for regional scale evaluation than those used in former studies. A chemical transport model and a RF model are used to evaluate the time period 2004–2030, when we expect increasing traffic in the Arctic region. Two datasets for ship emissions are used that characterize the potential impact from shipping and the degree to which shipping controls may mitigate impacts: a high (HIGH) scenario and a low scenario with Maximum Feasible Reduction (MFR) of black carbon in the Arctic. In MFR, BC emissions in the Arctic are reduced with 70% representing a combination technology performance and/or reasonable advances in single-technology performance. Both scenarios result in moderate to substantial increases in concentrations of pollutants both globally and in the Arctic. Exceptions are black carbon in the MFR scenario, and sulfur species and organic carbon in both scenarios due to the future phase-in of current regulation that reduces fuel sulfur content. In the season with potential transit traffic through the Arctic in 2030 we find increased concentrations of all pollutants in large parts of the Arctic. Net global RFs from 2004–2030 of 53 mW m−2 (HIGH) and 73 mW m−2 (MFR) are similar to those found for preindustrial to present net global aircraft RF. The found warming contrasts with the cooling from historical ship emissions. The reason for this difference and the higher global forcing for the MFR scenario is mainly the reduced future fuel sulfur content resulting in less cooling from sulfate aerosols. The Arctic RF is largest in the HIGH scenario. In the HIGH scenario ozone dominates the RF during the transit season (August–October). RF due to BC in air, and snow and ice becomes significant during Arctic spring. For the HIGH scenario the net Arctic RF during spring is 5 times higher than in winter.
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Yuan, Da-jun, Hui Jin, Zhi-cong Chen, and Sheng-nan Liu. "Evacuation Experiment Study in Up and Down Escape Staircase of Underground Road." Advances in Civil Engineering 2021 (March 19, 2021): 1–10. http://dx.doi.org/10.1155/2021/8834180.
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To measure evacuation basic parameters, reveal evacuation performance, and study reasonable staircase spacing of up and down escape staircase in case of fire, an evacuation experiment, which was based on the most unfavorable evacuation scenario, was conducted. The experiment took personnel and vehicles of actual underground road traffic into account, and evacuation process image data were extracted and analyzed by artificial statistics. Experimental results indicate that the personnel plane evacuation speed is between 1.43 and 1.95 m/s, and the upstairs evacuation speed that is less affected by gender and age is mainly between 0.5 and 1.1 m/s; under the escape stairs width of 0.8 m, the average capacity of escape staircase is 0.7 P/s, and the entrance of the staircase is evacuation bottleneck and queuing phenomenon occurs. Based on the experiment, a calculation model of three-phase personnel net evacuation time was established. By simplifying the evacuation model, a calculation formula of the reasonable escape stair spacing considering the influence of multiple factors was proposed. And the proposed theoretical model was verified by project cases of up and down escape staircase. With 2 min emergency broadcasting time and 6 min Available Safety Evacuation Time of medium-sized fire as the Personnel Safety Evacuation Rule’s reference, the recommended value of escape staircase spacing of single pipe double-deck two-way four-lane (double pipes double-deck two-way eight-lane) underground roads is 64.3 m.
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Liu, D., J. D. Allan, D. E. Young, H. Coe, D. Beddows, Z. L. Fleming, M. J. Flynn, et al. "Size distribution, mixing state and source apportionments of black carbon aerosols in London during winter time." Atmospheric Chemistry and Physics Discussions 14, no. 11 (June 20, 2014): 16291–349. http://dx.doi.org/10.5194/acpd-14-16291-2014.
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Abstract. Black carbon aerosols (BC) at a London urban site were characterized in both winter and summer time 2012 during the Clean Air for London (ClearfLo) project. Positive matrix factorization (PMF) factors of organic aerosol mass spectra measured by a high resolution aerosol mass spectrometer (HR-AMS) showed traffic-dominant sources in summer but in winter the influence of additional non-traffic sources became more important, mainly from solid fuel sources (SF). Measurements using a single particle soot photometer (SP2, DMT), showed the traffic-dominant BC exhibited an almost uniform BC core size (Dc) distribution with very thin coating thickness throughout the detectable range of Dc. However the size distribution of Dc (project average mass median Dc = 149 ± 22 nm in winter, and 120 ± 6 nm in summer) and BC coating thickness varied significantly in winter. A novel methodology was developed to attribute the BC number concentrations and mass abundances from traffic (BCtr) and from SF (BCsf), by using a 2-D histogram of the particle optical properties as a function of BC core size, as measured by the SP2. The BCtr and BCsf showed distinctly different Dc distributions and coating thicknesses, with BCsf displaying larger Dc and larger coating thickness compared to BCtr. BC particles from different sources were also apportioned by applying a multiple linear regression between the total BC mass and each AMS-PMF factor (BC-AMS-PMF method), and also attributed by applying the absorption spectral dependence of carbonaceous aerosols to 7-wavelength Aethalometer measurements (Aethalometer method). Air masses that originated from westerly (W), southeasterly (SE), or easterly (E) sectors showed BCsf fractions that ranged from low to high, and whose mass median Dc values were 137 ± 10 nm, 143 ± 11 nm, and 169 ± 29 nm respectively. The corresponding bulk relative coating thickness of BC (coated particle size / BC core – Dp / Dc) for these same sectors was 1.28 ± 0.07, 1.45 ± 0.16, and 1.65 ± 0.19. For W, SE and E air masses, the number fraction of BCsf ranged from 6 ± 2% to 11 ± 5% to 18 ± 10% respectively, but importantly the larger BC core sizes lead to an increased fraction of BCsf in terms of mass than number (for W–SE–E air masses, the BCsf mass fractions ranged from 16 ± 6 %–24 ± 10%–39 ± 14% respectively). An increased fraction of non-BC particles (particles that did not contain a BC core) was also observed when SF sources were more significant. The BC mass attribution by the SP2 method agreed well with the BC-AMS-PMF multiple linear regression method (BC-AMS-PMF : SP2 ratio = 1.05, r2 = 0.80) over the entire experimental period. Good agreement was found between BCsf attributed with the Aethalometer model and the SP2. However, the assumed Absorption Ångström Exponent (αwb) had to be changed according to the different air mass sectors to yield the best comparison with the SP2. This could be due to influences of fuel type or burn phase.
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Liu, D., J. D. Allan, D. E. Young, H. Coe, D. Beddows, Z. L. Fleming, M. J. Flynn, et al. "Size distribution, mixing state and source apportionment of black carbon aerosol in London during wintertime." Atmospheric Chemistry and Physics 14, no. 18 (September 22, 2014): 10061–84. http://dx.doi.org/10.5194/acp-14-10061-2014.
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Abstract. Black carbon aerosols (BC) at a London urban site were characterised in both winter- and summertime 2012 during the Clean Air for London (ClearfLo) project. Positive matrix factorisation (PMF) factors of organic aerosol mass spectra measured by a high-resolution aerosol mass spectrometer (HR-AMS) showed traffic-dominant sources in summer but in winter the influence of additional non-traffic sources became more important, mainly from solid fuel sources (SF). Measurements using a single particle soot photometer (SP2, DMT), showed the traffic-dominant BC exhibited an almost uniform BC core size (Dc) distribution with very thin coating thickness throughout the detectable range of Dc. However, the size distribution of Dc (project average mass median Dc = 149 ± 22 nm in winter, and 120 ± 6 nm in summer) and BC coating thickness varied significantly in winter. A novel methodology was developed to attribute the BC number concentrations and mass abundances from traffic (BCtr) and from SF (BCsf), by using a 2-D histogram of the particle optical properties as a function of BC core size, as measured by the SP2. The BCtr and BCsf showed distinctly different Dc distributions and coating thicknesses, with BCsf displaying larger Dc and larger coating thickness compared to BCtr. BC particles from different sources were also apportioned by applying a multiple linear regression between the total BC mass and each AMS-PMF factor (BC–AMS–PMF method), and also attributed by applying the absorption spectral dependence of carbonaceous aerosols to 7-wavelength Aethalometer measurements (Aethalometer method). Air masses that originated from westerly (W), southeasterly (SE), and easterly (E) sectors showed BCsf fractions that ranged from low to high, and whose mass median Dc values were 137 ± 10 nm, 143 ± 11 nm and 169 ± 29 nm, respectively. The corresponding bulk relative coating thickness of BC (coated particle size/BC core – Dp/Dc) for these same sectors was 1.28 ± 0.07, 1.45 ± 0.16 and 1.65 ± 0.19. For W, SE and E air masses, the number fraction of BCsf ranged from 6 ± 2% to 11 ± 5% to 18 ± 10%, respectively, but importantly the larger BC core sizes lead to an increased fraction of BCsf in terms of mass than number (for W, SE and E air masses, the BCsf mass fractions ranged from 16 ± 6%, 24 ± 10% and 39 ± 14%, respectively). An increased fraction of non-BC particles (particles that did not contain a BC core) was also observed when SF sources were more significant. The BC mass attribution by the SP2 method agreed well with the BC–AMS–PMF multiple linear regression method (BC–AMS–PMF : SP2 ratio = 1.05, r2 = 0.80) over the entire experimental period. Good agreement was found between BCsf attributed with the Aethalometer model and the SP2. However, the assumed absorption Ångström exponent (αwb) had to be changed according to the different air mass sectors to yield the best comparison with the SP2. This could be due to influences of fuel type or burn phase.
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Diehl, T., A. Heil, M. Chin, X. Pan, D. Streets, M. Schultz, and S. Kinne. "Anthropogenic, biomass burning, and volcanic emissions of black carbon, organic carbon, and SO<sub>2</sub> from 1980 to 2010 for hindcast model experiments." Atmospheric Chemistry and Physics Discussions 12, no. 9 (September 21, 2012): 24895–954. http://dx.doi.org/10.5194/acpd-12-24895-2012.
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Abstract. Two historical emission inventories of black carbon (BC), primary organic carbon (OC), and SO2 emissions from land-based anthropogenic sources, ocean-going vessels, air traffic, biomass burning, and volcanoes are presented and discussed for the period 1980–2010. These gridded inventories are provided to the internationally coordinated AeroCom Phase II multi-model hindcast experiments. The horizontal resolution is 0.5°×0.5° and 1.0°×1.0°, while the temporal resolution varies from daily for volcanoes to monthly for biomass burning and aircraft emissions, and annual averages for land-based and ship emissions. One inventory is based on inter-annually varying activity rates of land-based anthropogenic emissions and shows strong variability within a decade, while the other one is derived from interpolation between decadal endpoints and thus exhibits linear trends within a decade. Both datasets capture the major trends of decreasing anthropogenic emissions over the USA and Western Europe since 1980, a sharp decrease around 1990 over Eastern Europe and the former USSR, and a steep increase after 2000 over East and South Asia. The inventory differences for the combined anthropogenic and biomass burning emissions in the year 2005 are 34% for BC, 46% for OC, and 13% for SO2. They vary strongly depending on species, year and region, from about 10% to 40% in most cases, but in some cases the inventories differ by 100% or more. Differences in emissions from wild-land fires are caused only by different choices of the emission factors for years after 1996 which vary by a factor of about 1 to 2 for OC depending on region, and by a combination of emission factors and the amount of dry mass burned for years up to 1996. Volcanic SO2 emissions, which are only provided in one inventory, include emissions from explosive, effusive, and quiescent degassing events for 1167 volcanoes.
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Garavello, Mauro, and Francesca Marcellini. "The Godunov method for a 2-phase model." Communications in Applied and Industrial Mathematics 8, no. 1 (March 28, 2017): 149–64. http://dx.doi.org/10.1515/caim-2017-0008.
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Abstract We consider the Godunov numerical method to the phase-transition trafic model, proposed in [1], by Colombo, Marcellini, and Rascle. Numerical tests are shown to prove the validity of the method. Moreover we highlight the differences between such model and the one proposed in [2], by Blandin, Work, Goatin, Piccoli, and Bayen.
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Nagatani, Takashi. "Phase transition and scaling in the generalized traffic flow model." Physica A: Statistical Mechanics and its Applications 246, no. 3-4 (December 1997): 460–70. http://dx.doi.org/10.1016/s0378-4371(97)00376-2.
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Nagatani, Takashi. "Phase transition and critical phenomenon in traffic flow model with velocity-dependent sensitivity." Physica A: Statistical Mechanics and its Applications 253, no. 1-4 (May 1998): 353–65. http://dx.doi.org/10.1016/s0378-4371(97)00660-2.
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Pottmeier, A., R. Barlovic, W. Knospe, A. Schadschneider, and M. Schreckenberg. "Localized defects in a cellular automaton model for traffic flow with phase separation." Physica A: Statistical Mechanics and its Applications 308, no. 1-4 (May 2002): 471–82. http://dx.doi.org/10.1016/s0378-4371(02)00547-2.
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Xue, Yu, Xue Wang, Bing-ling Cen, Peng Zhang, and Hong-di He. "Study on fuel consumption in the Kerner–Klenov–Wolf three-phase cellular automaton traffic flow model." Nonlinear Dynamics 102, no. 1 (September 2020): 393–402. http://dx.doi.org/10.1007/s11071-020-05947-2.
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Галкин, В. А. "Mathematical Problems of Collaborating Robotic Vehicle Traffic." Успехи кибернетики / Russian Journal of Cybernetics, no. 4(8) (November 30, 2021): 67–74. http://dx.doi.org/10.51790/2712-9942-2021-2-4-7.
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Предложен подход для моделирования динамики транспортных потоков для взаимодействующих аппаратов на основе теории самосогласованного поля, основанного на уравнениях А.А. Власова. Сформулированы проблемы применимости таких моделей для описания коллективных явлений трафика в связи с задачами поведения «стаи» роботизированных однородных взаимодействующих аппаратов в фазовом пространстве на основе кинетического подхода. An approach to the simulation of time-dependent collaborating vehicle traffic flows based on the self-consistent field theory and A. Vlasov equations are proposed. The problems of the simulation model applicability to collaborative traffic processes such as the behavior of a swarm of identical collaborating vehicles in phase space using the kinetic approach are stated.
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Rosario, Maximillian, Rizwan Romee, Stephanie E. Schneider, Jeffrey W. Leong, Ryan P. Sullivan, and Todd A. Fehniger. "Human Cytokine-Induced Memory-like (CIML) NK Cells Are Active Against Myeloid Leukemia in Vitro and in Vivo." Blood 124, no. 21 (December 6, 2014): 1117. http://dx.doi.org/10.1182/blood.v124.21.1117.1117.
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Abstract NK cells are innate lymphoid cells that mediate anti-leukemia responses. The ability of MHC-haploidentical NK cells to recognize and eliminate AML blasts have been established in the setting of stem cell transplantation and early phase adoptive NK cell immunotherapy trials. However, the optimal approach to prepare human NK cells for maximal anti-leukemia capacity is unclear. As one form of innate NK cell memory, cytokine-induced memory-like (CIML) NK cells are induced by a brief (16 hour) pre-activation of human NK cells with the combination of IL-12, IL-15, and IL-18, while control NK cells from the same donor are activated by IL-15 only. In published work, this combined IL-12, IL-15, and IL-18 pre-activation results in enhanced proliferation and augmented IFN-gamma responses to cytokine or activating receptor-based re-stimulation following a rest period of 1 – 6 weeks. We hypothesized that CIML NK cells exhibit improved anti-leukemia properties compared to control NK cells from the same individual. Purified primary human CIML NK cells [both CD56bright and CD56dim subsets] produce more IFN-gamma, compared to control NK cells, upon re-stimulation with K562 cells or primary AML blasts after 7 days of rest (p<0.05 and p<0.001, N=5). CIML NK cells also exhibit higher granzyme B protein expression (p<0.01; N=8), and increased cytotoxicity against K562 leukemia targets in vitro (p<0.001, 2.5:1 and 5:1 E:T ratios). We next established a NOD-SCID-gamma-c-/- (NSG) xenograft model to investigate primary human CIML NK cell responses in vivo, with survival supported by low dose IL-2 administered every other day. Seven days following injection of 4 million NK cells / mouse, human CIML NK cells traffic to the bone marrow, spleen, liver and blood, and exhibited better in vivo expansion and persistence, compared to control NK cells (p=0.05 in the blood and bone marrow). Further, the characteristic enhanced functionality of CIML compared to control NK cells when restimulated with K562 targets was retained when assessed ex vivo 7 days post-transfer (p<0.05). Next, we investigated the ability of CIML versus control NK cells from the same donor to clear K562 AML cells in vivo. First, luciferase expressing K562 cells (1 million / mouse) were engrafted into sub-lethally irradiated (250 cGy) NSG mice. On day 3 after K562 challenge, primary human CIML or control NK cells from the same donor (4 million / mouse) were injected, which were supported in vivo using low dose IL-2. CIML NK cells exhibited significantly improved in vivo leukemia clearance as evidenced by whole mouse bioluminescence imaging (see Figure, P=0.03, N=7 mice per group). Thus, human CIML NK cells exhibit enhanced in vitro and in vivo anti-leukemia effects, compared to control NK cells. Based on these findings, a first-in-human phase 1 study of CIML NK cells in relapsed/refractory AML is currently underway. Figure 1 Figure 1. Disclosures No relevant conflicts of interest to declare.
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Gu, Jaun, Minhyuck Lee, Chulmin Jun, Yohee Han, Youngchan Kim, and Junwon Kim. "Traffic Signal Optimization for Multiple Intersections Based on Reinforcement Learning." Applied Sciences 11, no. 22 (November 12, 2021): 10688. http://dx.doi.org/10.3390/app112210688.
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In order to deal with dynamic traffic flow, adaptive traffic signal controls using reinforcement learning are being studied. However, most of the related studies are difficult to apply to the real field considering only mathematical optimization. In this study, we propose a reinforcement learning-based signal optimization model with constraints. The proposed model maintains the sequence of typical signal phases and considers the minimum green time. The model was trained using Simulation of Urban MObility (SUMO), a microscopic traffic simulator. The model was evaluated in the virtual environment similar to a real road with multiple intersections connected. The performance of the proposed model was analyzed by comparing the delay and number of stops with a reinforcement learning model that did not consider constraints and a fixed-time model. In a peak hour, the proposed model reduced the delay from 3 min 15 s to 2 min 15 s and the number of stops from 11 to 4.7 compared to the fixed-time model.
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Županović, Dino, Mario Anžek, and Goran Kos. "Optimisation of Signal-controlled Intersection Capacity." PROMET - Traffic&Transportation 22, no. 6 (March 2, 2012): 419–31. http://dx.doi.org/10.7307/ptt.v22i6.207.
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Road traffic safety is a complex system which combines movement of entities in precisely determined space and time dimension. Each of the entities, with their different properties, sets different requirements to road traffic system, including also other entities. Due to the large number of entities and their characteristic requirements, their interaction results in extremely complex relations which determine the behaviour of the road traffic system. The entities are combined according to their common features into certain groups, the movements of which usually result in conflicts. In such situations it is necessary to ensure the movement of a group of entities. This method of insurance necessarily creates negative consequences for all the entities that participate in road traffic system. In order to mitigate as much as possible these consequences, it is necessary to find an adequate method of optimising road traffic system according to a given criterion. The paper uses the results of the analysis of more than 100 road traffic system models and presents the methodology of determining the level of their interconnection. The level of influence of the basic traffic values on the final effect, i.e. the possibility of optimising signal-controlled intersections has been found and described. KEYWORDS: traffic flow, signalized intersection, pretimedsystem, optimization, 2-phase system, 4-phase system, volume-to-capacity, lost time
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Min, Dongsoon, Trevor Waite, and Birsen Donmez. "Collision Risk Assessment Using Naturalistic Data from a Rent-A-Car Fleet." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 63, no. 1 (November 2019): 2030. http://dx.doi.org/10.1177/1071181319631481.
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We analyzed commercial fleet operations data collected by a South Korean rent-a-car company, SK Networks Co. Ltd., to evaluate the differences between collision-free and collision-involved drivers with the ultimate goal of predicting driver collision risk. The first objective was to identify critical variables related to collision risk. The second objective was to build and compare classification models to predict the colli-sion involvement of a driver. Data used in the analysis were collected through Long-Range (LoRa) Internet of Things (IoT) modem-Fleet management system (FMS) devices, a first commercial implementation of LoRa modems in the vehicle. These devices have five main built-in modules, i.e., On-Board Diagnostics (OBD-II) Connector, GPS, LoRa modem, Gravity sensor, and Bluetooth. They can communicate with the vehi-cle, the driver’s smartphone, and the host server. Data from 3,854 drivers with a total of 2.19 million trips recorded in 2018 were explored. Out of these 3,854 drivers, 514 (13.3%) were involved in at least one collision. Predictor variables were selected based on previous research that uti-lized naturalistic data to identify factors affecting collision risk (Dingus et al., 2016; Tselentis, Yannis, & Vlahogianni, 2016; Bian, Yang, Zhao, & Liang, 2018; Jin et al., 2018). Forty-eight predictor variables that may affect collision risk were selected, which can be categorized into two groups: 27 variables were related to the business and the environment, characterized by how much drivers traveled, in what type of vehicles, on what types of roads, and during what times of the day; the other 22 variables were driving behavior-related variables, capturing overspeeding, potential fatigue, rapid speed changes, and counts of traffic regulation violations. After a feature selection phase based on univariate analysis, nine variables were select-ed to be used in the classification models. These selected vari-ables are running driving time (driving time excluding idling time), trip frequency per thousand kilometer driving, accumu-lated count of violation, accumulated amount of fine, the per-centage of trips driving a compact car (<1,000 cc), the per-centage of trips driving older than a 2016 car model, the per-centage of trips during 6 a.m.-9 a.m., the percentage of trips that ended during 2 a.m.-7 a.m., and the sum of rapid accelera-tion and deceleration frequencies per kilometer. A total of twenty classification models were built and compared to classify collision-involved and non-collision in-volved drivers: 5 classification modeling techniques (Logistic Regression (LR), Random Forest (RF), k-Nearest Neighbor (kNN), Support Vector Machine (SVM) and Gradient boosted trees (GBT)) x 4 sampling methods (Up, Down, Smote, and No-sampling). The GBT-down sampled model showed the best classification performance according to Area under the Curve (0.804) and Area under the Precision and Recall Curve (0.406) statistics. Comparing relative variable importance val-ues for the best three classification models (GBT, RF, and LR), both running driving time and violation count were found to be the most influential variables, followed by the sum of rapid acceleration and deceleration frequencies, accumulated amount of fine, trip frequency per thousand kilometer driving, and the percentage of trips driving a compact car. These re-sults agree with the results of previous naturalistic studies: driver behavior-related variables are highly related to collision likelihood, although running driving time in our dataset was likely dictated by businesses. This dataset provided us with a unique opportunity to take an in-depth look at the relationship between collisions and business, environment, and driving behavior-related variables by using naturalistic data from newly-invented LoRa IoT-FMS devices. To the best of our knowledge, this study was the first naturalistic study connecting both driving data and various types of traffic violations (e.g., overspeeding, lane, sign, park-ing, toll fees, and fine amount). Interestingly, non-driving-related violation types such as parking or toll-fee violation counts were also strongly correlated with collision involve-ment; suggesting that collision-involvement is likely not just a skill issue but also an attitude issue regarding the law. In terms of industrial applications, this study suggests multiple oppor-tunities. Through a better understanding of the influential vari-ables related to collision-involvement (e.g., accumulated vio-lations), fleet operators can build policies to enhance their fleet safety, reducing collision rates and the associated costs. Further, in the long-term, this study can provide a framework for developing a Usage-Based Rent-a-car (UBR) service for car rental field, similar to Usage-Based Insurance (UBI), which can reduce drivers’ rental fees based on their driving behaviors.
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Chen, Deqi, Xuedong Yan, Feng Liu, Xiaobing Liu, Liwei Wang, and Jiechao Zhang. "Evaluating and Diagnosing Road Intersection Operation Performance Using Floating Car Data." Sensors 19, no. 10 (May 15, 2019): 2256. http://dx.doi.org/10.3390/s19102256.
Full textAbstract:
Urban road intersections play an important role in deciding the total travel time and the overall travel efficiency. In this paper, an innovative traffic grid model has been proposed, which evaluates and diagnoses the traffic status and the time delay at intersections across whole urban road networks. This method is grounded on a massive amount of floating car data sampled at a rate of 3 s, and it is composed of three major parts. (1) A grid model is built to transform intersections into discrete cells, and the floating car data are matched to the grids through a simple assignment process. (2) Based on the grid model, a set of key traffic parameters (e.g., the total time delay of all the directions of the intersection and the average speed of each direction) is derived. (3) Using these parameters, intersections are evaluated and the ones with the longest traffic delays are identified. The obtained intersections are further examined in terms of the traffic flow ratio and the green time ratio as well as the difference between these two variables. Using the central area of Beijing as the case study, the potential and feasibility of the proposed method are demonstrated and the unreasonable signal timing phases are detected. The developed method can be easily transferred to other cities, making it a useful and practical tool for traffic managers to evaluate and diagnose urban signal intersections as well as to design optimal measures for reducing traffic delay and increase operation efficiency at the intersections.
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Petetin, Hervé, Dene Bowdalo, Albert Soret, Marc Guevara, Oriol Jorba, Kim Serradell, and Carlos Pérez García-Pando. "Meteorology-normalized impact of the COVID-19 lockdown upon NO<sub>2</sub> pollution in Spain." Atmospheric Chemistry and Physics 20, no. 18 (September 29, 2020): 11119–41. http://dx.doi.org/10.5194/acp-20-11119-2020.
Full textAbstract:
Abstract. The spread of the new coronavirus SARS-CoV-2 that causes COVID-19 forced the Spanish Government to implement extensive lockdown measures to reduce the number of hospital admissions, starting on 14 March 2020. Over the following days and weeks, strong reductions in nitrogen dioxide (NO2) pollution were reported in many regions of Spain. A substantial part of these reductions was obviously due to decreased local and regional anthropogenic emissions. Yet, the confounding effect of meteorological variability hinders a reliable quantification of the lockdown's impact upon the observed pollution levels. Our study uses machine-learning (ML) models fed by meteorological data along with other time features to estimate the “business-as-usual” NO2 mixing ratios that would have been observed in the absence of the lockdown. We then quantify the so-called meteorology-normalized NO2 reductions induced by the lockdown measures by comparing the estimated business-as-usual values with the observed NO2 mixing ratios. We applied this analysis for a selection of urban background and traffic stations covering the more than 50 Spanish provinces and islands. The ML predictive models were found to perform remarkably well in most locations, with an overall bias, root mean square error and correlation of +4 %, 29 % and 0.86, respectively. During the period of study, from the enforcement of the state of alarm in Spain on 14 March to 23 April, we found the lockdown measures to be responsible for a 50 % reduction in NO2 levels on average over all provinces and islands. The lockdown in Spain has gone through several phases with different levels of severity with respect to mobility restrictions. As expected, the meteorology-normalized change in NO2 was found to be stronger during phase II (the most stringent phase) and phase III of the lockdown than during phase I. In the largest agglomerations, where both urban background and traffic stations were available, a stronger meteorology-normalized NO2 change is highlighted at traffic stations compared with urban background sites. Our results are consistent with foreseen (although still uncertain) changes in anthropogenic emissions induced by the lockdown. We also show the importance of taking the meteorological variability into account for accurately assessing the impact of the lockdown on NO2 levels, in particular at fine spatial and temporal scales. Meteorology-normalized estimates such as those presented here are crucial to reliably quantify the health implications of the lockdown due to reduced air pollution.
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Cutolo, A., C. D'Apice, and R. Manzo. "Traffic Optimization at Junctions to Improve Vehicular Flows." ISRN Applied Mathematics 2011 (September 25, 2011): 1–19. http://dx.doi.org/10.5402/2011/679056.
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The aim of this work is to improve urban traffic viability through an appropriate choice of yielding and stop signs or red and green phases for traffic lights in junctions with two entering and one exiting roads (junctions of 2×1 type). We consider a macroscopic fluid-dynamic model able to capture the traffic evolution. We analyze different functionals measuring networks performance in terms of average velocity, average traveling time, total flux, density, stop and go waves, average traveling time, weighted with the number of cars moving on roads, and kinetic energy. Right of way parameters which optimize the latter two functionals are obtained. Simulations of simple junctions of 2×1type have been used to test the correctness of the analytical results. Then, global performance of optimization procedures has been investigated on Re di Roma Square, in Italy. In particular, we discuss cases in which the functionals are optimized locally at each junction for different values of right of way parameters. We show that for the chosen initial data the only algorithm for the maximization of velocity assures globally the best performance for the network, also in terms of average traveling times and kinetic energy.
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Mu’azam, Imran B., Nor Fatihah Ismail, Salama A. Mostafa, Zirawani Baharum, Taufik Gusman, and Dewi Nasien. "Classifying Vehicle Types from Video Streams for Traffic Flow Analysis Systems." JOIV : International Journal on Informatics Visualization 6, no. 1 (March 25, 2022): 19. http://dx.doi.org/10.30630/joiv.6.1.739.
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This paper proposes a vehicle types classification modelfrom video streams for improving Traffic Flow Analysis (TFA) systems. A Video Content-based Vehicles Classification (VC-VC) model is used to support optimization for traffic signal control via online identification of vehicle types.The VC-VC model extends several methods to extract TFA parameters, including the background image processing, object detection, size of the object measurement, attention to the area of interest, objects clash or overlap handling, and tracking objects. The VC-VC model undergoes the main processing phases: preprocessing, segmentation, classification, and tracks. The main video and image processing methods are the Gaussian function, active contour, bilateral filter, and Kalman filter. The model is evaluated based on a comparison between the actual classification by the model and ground truth. Four formulas are applied in this project to evaluate the VC-VC model’s performance: error, average error, accuracy, and precision. The valid classification is counted to show the overall results. The VC-VC model detects and classifies vehicles accurately. For three tested videos, it achieves a high classification accuracy of 85.94% on average. The precession for the classification of the three tested videos is 92.87%. The results show that video 1 and video 3 have the most accurate vehicle classification results compared to video 2. It is because video 2 has more difficult camera positioning and recording angle and more challenging scenarios than the other two. The results show that it is difficult to classify vehicles based on objects size measures. The object's size is adjustable based on the camera altitude and zoom setting. This adjustment is affecting the accuracy of vehicles classification.
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Tarasyan, V. S., and A. O. Gryaznov. "Applicability of genetic algorithms for confi guring fuzzy traÈ c control systems at intersections." Herald of the Ural State University of Railway Transport, no. 3 (2020): 4–11. http://dx.doi.org/10.20291/2079-0392-2020-3-4-11.
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The paper demonstrates a method for optimizing a fuzzy controller through a genetic algorithm that uses an elitism strategy. A simplified model of a regulated four-way intersection was used as the object of regulation, describing an intersection with one lane of traffic in each direction. A series of computer experiments on optimization of the fuzzy controller was performed for the set values of the traffic intensity. The results of several runs, each with the duration of the simulation was limited to ten generations, demonstrated repeatability of the settings, on the basis of which a conclusion about the achievement of the maximum efficiency control method was made. The results of modeling traffic light regulation in three variants are compared: 1) fixed duration of traffic light phases, 2) the rule base for the fuzzy controller is compiled by an expert method, and 3) the rule base for the fuzzy controller is optimized by a special evolutionary algorithm. It is shown that the average tube length for the optimized regulator in the experiments sought to the minimum value (about 11 vehicles, which is almost twice less than in the preparation of the expert rule base of a fuzzy controller and about four times less than for a fixed cycle traffic light).
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Iwanowicz, Damian. "Assessment of selected methods of estimating the maximum back-of-queue size on a signal-controlled intersection approach." Journal of Civil Engineering and Transport 4, no. 2 (December 31, 2022): 49–63. http://dx.doi.org/10.24136/tren.2022.008.
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The article presents the characteristics and evaluation of the accuracy of estimating the maximum length of the queue of vehicles at signalized intersections by commonly used methods in the world. The analyzes were based on the latest editions of the guidelines in the United States, Canada, Australia, Germany and Poland. In order to carry out accuracy analyzes, traffic tests were carried out at 5 intersection inlets in three different cities in Poland (Bydgoszcz, Torun, Warsaw), covering all phases of vehicle queue formation during individual periods of the signaling cycle (effective red and green signal). In total, the analysis had the results of tests from 81 hours of observation ~23,000 behaviors of vehicle drivers. Based on the analyzes it was found in particular: (1) slight differences in the construction of mathematical models of the considered calculation methods, with the exception of the US HCM model from 2016; (2) small errors in estimating the maximum queue length in unsaturated vehicle flow states (~3-5 vehicles/cycle and ~2-6 vehicles/15 minutes interval); (3) quite large errors in estimating the maximum queue length in saturated and oversaturated vehicle flow states (~11-16 vehicles/cycle and ~15-18 vehicles/15 minutes interval); (4) the main impact on estimation errors in oversaturation traffic states is not taking into account or incorrect determination of the 'so-called' initial queue length of the period preceding the analyzed period.
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Abu-Lebdeh, Ghassan, Rahim F. Benekohal, and Bashar Al-Omari. "Models for Right-Turn-on-Red and Their Effects on Intersection Delay." Transportation Research Record: Journal of the Transportation Research Board 1572, no. 1 (January 1997): 131–39. http://dx.doi.org/10.3141/1572-16.
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Models to estimate right-turn-on-red (RTOR) volumes at intersections with exclusive right-turn (RT) lanes are developed, and the effects of RTOR volumes on computed delay are assessed. The important variables in these models are the RT volume, followed by green-time-to-cycle (G/C) ratio, volume of conflicting traffic, and whether there is a protected phase for opposing left-turning vehicles. The estimated RTOR increased as the RTs increased. However, it decreased as G/C and the volume of conflicting traffic increased. Results show that not accounting for RTOR volumes can lead to a significant difference in delay estimates for RT lanes and, to a lesser extent, on the corresponding approaches. For RT lanes, in one-half of the cases the difference was greater than 5 percent, in more than one-quarter of the cases the difference was greater than 10 percent, and in at least one of eight cases the difference was greater than 20 percent. Differences for individual cases ranged between 0 and 130 percent, with an average of 12 percent. For approaches, the average delay difference was 4 percent, and for individual cases the difference ranged between −2 and 78 percent. As recommended by the Highway Capacity Manual, actual field counts of RTOR volume should be used whenever available. However, in the absence of such counts, the models developed here can be used and hence should be considered in capacity analysis procedures.
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Zamanifar, Milad, and Timo Hartmann. "Optimization-based decision-making models for disaster recovery and reconstruction planning of transportation networks." Natural Hazards 104, no. 1 (July 26, 2020): 1–25. http://dx.doi.org/10.1007/s11069-020-04192-5.
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Abstract The purpose of this study is to analyze optimization-based decision-making models for the problem of Disaster Recovery Planning of Transportation Networks (DRPTN). In the past three decades, seminal optimization problems have been structured and solved for the critical and sensitive problem of DRPTN. The extent of our knowledge on the practicality of the methods and performance of results is however limited. To evaluate the applicability of those context-sensitive models in real-world situations, there is a need to examine the conceptual and technical structure behind the existing body of work. To this end, this paper performs a systematic search targeting DRPTN publications. Thereafter, we review the identified literature based on the four phases of the optimization-based decision-making modeling process as problem definition, problem formulation, problem-solving, and model validation. Then, through content analysis and descriptive statistics, we investigate the methodology of studies within each of these phases. Eventually, we detect and discuss four research improvement areas as [1] developing conceptual or systematic decision support in the selection of decision attributes and problem structuring, [2] integrating recovery problems with traffic management models, [3] avoiding uncertainty due to the type of solving algorithms, and [4] reducing subjectivity in the validation process of disaster recovery models. Finally, we provide suggestions as well as possible directions for future research.