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1
Chien, Steven I. J., Xiaobo Liu, and Kaan Ozbay. "Predicting Travel Times for the South Jersey Real-Time Motorist Information System." Transportation Research Record: Journal of the Transportation Research Board 1855, no. 1 (January 2003): 32–40. http://dx.doi.org/10.3141/1855-04.
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A dynamic travel-time prediction model was developed for the South Jersey (southern New Jersey) motorist real-time information system. During development and evaluation of the model, the integration of traffic flow theory, measurement and application of collected data, and traffic simulation were considered. Reliable prediction results can be generated with limited historical real-time traffic data. In the study, acoustic sensors were installed at potential congested places to monitor traffic congestion. A developed simulation model was calibrated with the data collected from the sensors, and this was applied to emulate traffic operations and evaluate the proposed prediction model under time-varying traffic conditions. With emulated real–time information (travel times) generated by the simulation model, an algorithm based on Kalman filtering was developed and applied to forecast travel times for specific origin-destination pairs over different periods. Prediction accuracy was evaluated by the simulation model. Results show that the developed travel-time predictive model demonstrates satisfactory performance.
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De Palma, André, Fabrice Marchal, and Yurii Nesterov. "METROPOLIS: Modular System for Dynamic Traffic Simulation." Transportation Research Record: Journal of the Transportation Research Board 1607, no. 1 (January 1997): 178–84. http://dx.doi.org/10.3141/1607-24.
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METROPOLIS proposes an interactive environment that simulates automobile traffic in large urban areas. The core of the system is a dynamic simulator that integrates commuters’ departure time and route choice behaviors over large networks: Drivers are assumed to minimize a generalized travel cost function that depends on travel time and schedule delay. This simulator is based on a behavioral driver information process. It allows real-time and off-line simulations. The system also includes a scenario builder and a graphical results viewer. The main ideas underlying METROPOLIS are presented, and preliminary computer simulation experiments are discussed for Geneva, Switzerland.
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Liu, Zhiguang, Tomio Miwa, Weiliang Zeng, Michael G. H. Bell, and Takayuki Morikawa. "Shared Autonomous Taxi System and Utilization of Collected Travel-Time Information." Journal of Advanced Transportation 2018 (August 8, 2018): 1–13. http://dx.doi.org/10.1155/2018/8919721.
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Shared autonomous taxi systems (SATS) are being regarded as a promising means of improving travel flexibility. Each shared autonomous taxi (SAT) requires very precise traffic information to independently and accurately select its route. In this study, taxis were replaced with ride-sharing autonomous vehicles, and the potential benefits of utilizing collected travel-time information for path finding in the new taxi system examined. Specifically, four categories of available SATs for every taxi request were considered: currently empty, expected-empty, currently sharable, and expected-sharable. Two simulation scenarios—one based on historical traffic information and the other based on real-time traffic information—were developed to examine the performance of information use in a SATS. Interestingly, in the historical traffic information-based scenario, the mean travel time for taxi requests and private vehicle users decreased significantly in the first several simulation days and then remained stable as the number of simulation days increased. Conversely, in the real-time information-based scenario, the mean travel time was constant. As the SAT fleet size increased, the total travel time for taxi requests significantly decreased, and convergence occurred earlier in the historical information-based scenario. The results demonstrate that historical traffic information is better than real-time traffic information for path finding in SATS.
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Thomas, Natacha, and Bader Hafeez. "Simulation of an Arterial Incident Environment with Probe Reporting Capability." Transportation Research Record: Journal of the Transportation Research Board 1644, no. 1 (January 1998): 116–23. http://dx.doi.org/10.3141/1644-12.
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Intelligent transportation systems have created new traffic monitoring approaches and fueled new interests in automated incident detection systems. One new monitoring approach utilizes actual travel times experienced by vehicles, called probes, equipped to transmit this information in real time to a control center. The database needed to design and calibrate arterial incident detection systems based on probe travel times is nonexistent. A microscopic traffic simulation package, Integrated Traffic Simulation, was selected and enhanced to generate vehicle travel times for the incident and incident-free conditions on an arterial. We evaluated the enhanced model. Significant variations in probe travel times were observed in the event of incidents. Average travel time, contrary to average occupancy, may increase, decrease, or remain constant on arterial streets downstream of an incident.
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Kwon, Jaimyoung, Benjamin Coifman, and Peter Bickel. "Day-to-Day Travel-Time Trends and Travel-Time Prediction from Loop-Detector Data." Transportation Research Record: Journal of the Transportation Research Board 1717, no. 1 (January 2000): 120–29. http://dx.doi.org/10.3141/1717-15.
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An approach is presented for estimating future travel times on a freeway using flow and occupancy data from single-loop detectors and historical travel-time information. Linear regression, with the stepwise-variable-selection method and more advanced tree-based methods, is used. The analysis considers forecasts ranging from a few minutes into the future up to an hour ahead. Leave-a-day-out cross-validation was used to evaluate the prediction errors without underestimation. The current traffic state proved to be a good predictor for the near future, up to 20 min, whereas historical data are more informative for longer-range predictions. Tree-based methods and linear regression both performed satisfactorily, showing slightly different qualitative behaviors for each condition examined in this analysis. Unlike preceding works that rely on simulation, real traffic data were used. Although the current implementation uses measured travel times from probe vehicles, the ultimate goal is an autonomous system that relies strictly on detector data. In the course of presenting the prediction system, the manner in which travel times change from day to day was examined, and several metrics to quantify these changes were developed. The metrics can be used as input for travel-time prediction, but they also should be beneficial for other applications, such as calibrating traffic models and planning models.
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Zhang, Kuilin, Hani S. Mahmassani, and Chung-Cheng Lu. "Probit-Based Time-Dependent Stochastic User Equilibrium Traffic Assignment Model." Transportation Research Record: Journal of the Transportation Research Board 2085, no. 1 (January 2008): 86–94. http://dx.doi.org/10.3141/2085-10.
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This study presents a time-dependent stochastic user equilibrium (TDSUE) traffic assignment model within a probit-based path choice decision framework that explicitly takes into account temporal and spatial correlation (traveler interactions) in travel disutilities across a set of paths. The TDSUE problem, which aims to find time-dependent SUE path flows, is formulated as a fixed-point problem and solved by a simulation-based method of successive averages algorithm. A mesoscopic traffic simulator is employed to determine (experienced) time-dependent travel disutilities. A time-dependent shortest-path algorithm is applied to generate new paths and augment a grand path set. Two vehicle-based implementation techniques are proposed and compared in order to show their impact on solution quality and computational efficiency. One uses the classical Monte Carlo simulation approach to explicitly compute path choice probabilities, and the other determines probabilities by sampling vehicles’ path travel costs from an assumed perception error distribution (also using a Monte Carlo simulation process). Moreover, two types of variance-covariance error structures are discussed: one considers temporal and spatial path choice correlation (due to path overlapping) in terms of aggregated path travel times, and the other uses experienced (or empirical) path travel times from a sample of individual vehicle trajectories. A set of numerical experiments are conducted to investigate the convergence pattern of the solution algorithms and to examine the impact of temporal and spatial correlation on path choice behavior.
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Kühne, Reinhart D., Karin Langbein-Euchner, Martin Hilliges, and Norbert Koch. "Evaluation of Compliance Rates and Travel Time Calculation for Automatic Alternative Route Guidance Systems on Freeways." Transportation Research Record: Journal of the Transportation Research Board 1554, no. 1 (January 1996): 153–61. http://dx.doi.org/10.1177/0361198196155400119.
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This study outlines the concept of extending an available simulation model for evaluation of freeway route guidance systems using the compliance rates of drivers with alternative route recommendations based on measurements from the freeway subnetwork near Munich, Germany. The system works with variable direction signs that automatically display routing instructions to prevent congestion on the main road. The effectiveness of the system is assessed by calculating the travel times with and without an alternative route guidance system in operation. The result is a decrease in individual travel times on the main road and overall travel time savings for all traffic participants of the system. The simulation indicates a high sensitivity of diverting portions of traffic that allows an exact validation. The diverted traffic affects not only travel time and the congested area but also the destinations, which permits the use of the compliance rate as an accurate fit parameter for exact description of traffic patterns from measurement data.
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Wu, Zifeng, Laurence R. Rilett, and Yifeng Chen. "Evaluating the Impact of Highway-Railway Grade Crossings on Travel Time Reliability on a Highway Network Level." Transportation Research Record: Journal of the Transportation Research Board 2672, no. 10 (August 20, 2018): 1–11. http://dx.doi.org/10.1177/0361198118792756.
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Highway-rail grade crossings (HRGCs) have a range of safety and operational impacts on highway traffic networks. This paper illustrates a methodology for evaluating travel-time reliability for the routes and networks affected by trains traveling through HRGCs. A sub-area network including three HRGCs is used as the study network, and a simulation model calibrated to local traffic conditions and signal preemption strategies using field data is used as the platform to generate travel time data for analysis. Time-dependent reliability intervals for route travel time are generated based on route travel-time means and standard deviations. OD level reliability is calculated using a generic reliability engineering approach for parallel and series systems. The route travel time reliability results can be provided as real-time traffic information to assist drivers’ route-choice decisions. The OD level reliability is a way to quantify the impact of HRGCs on highway network operation. This effort fills the gap of reliability research for HRGCs on the route and sub-area network level, and contributes to improving the efficiency of decision-making for both traffic engineers and drivers.
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Ma, Zhengfeng, Darong Huang, Changguang Li, and Jianhua Guo. "Travel Time Reliability-Based Signal Timing Optimization for Urban Road Traffic Network Control." Mathematical Problems in Engineering 2020 (December 1, 2020): 1–11. http://dx.doi.org/10.1155/2020/8898062.
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Due to increasing traffic demand, many metropolitan areas are experiencing extensive traffic congestion, which demands for efficient traffic signal timing and optimization. However, conventional efficiency measure-based signal optimization cannot handle the ubiquitous uncertainty in the road networks, demanding for the incorporation of reliability measures into signal optimization, which is still in its early stage. Therefore, targeting this issue, based on the recent studies on recognizing travel time reliability (TRR) as an important reliability measure of road networks, a travel time reliability-based urban road traffic network signal timing optimization model is proposed in this paper, with the objective function to optimize a TTR measure, i.e., buffer time index. The proposed optimization model is solved using the heuristic particle swarm optimization approach. A case study is conducted using microscopic traffic simulation for a road network in the City of Nanjing, China. Results demonstrate that the proposed optimization model can improve travel time reliability of the road traffic network and the efficiency of the road traffic network as well. Future studies are recommended to expand the integration of travel time reliability into traffic signal timing optimization.
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Jayan, Akhilesh, and Sasidharan Premakumari Anusha. "Travel Time Prediction under Mixed Traffic Conditions Using RFID and Bluetooth Sensors." Periodica Polytechnica Transportation Engineering 48, no. 3 (December 16, 2019): 276–89. http://dx.doi.org/10.3311/pptr.13779.
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Travel time information is an integral part in various ITS applications such as Advanced Traveler Information System, Advanced Traffic Management Systems etc. Travel time data can be collected manually or by using advanced sensors. In this study, suitability of Bluetooth and RFID (Radio Frequency Identifier) sensors for data collection under mixed traffic conditions as prevailing in India is explored. Reliability analysis was carried out using Cumulative Frequency Diagrams (CFDs) and buffer time index along with evaluation of penetration rate and match rate of RFID and Bluetooth sensors. Further, travel time of cars for a subsequent week was predicted using the travel time data obtained from RFID sensors for the present week as input in ARIMA modeling method. For predicting the travel time of different vehicle categories, relationships were framed between travel time of different vehicle categories and travel time of cars determined from RFID sensors. The stream travel time was then determined considering the travel time of all vehicle categories. The R-Square and MAPE values were used as performance measure for checking the accuracy of the developed models and were closer to one and lower respectively, indicating the suitability of the RFID sensors for travel time prediction under mixed traffic conditions. The developed estimation schemes can be used as part of travel time information applications in real time Intelligent Transportation System (ITS) implementations.
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Chen, Mei, and Steven I. J. Chien. "Determining the Number of Probe Vehicles for Freeway Travel Time Estimation by Microscopic Simulation." Transportation Research Record: Journal of the Transportation Research Board 1719, no. 1 (January 2000): 61–68. http://dx.doi.org/10.3141/1719-08.
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Using probe vehicles to collect real-time traffic information is considered an efficient method in real-world applications. How to determine the minimum number of probe vehicles required for accurate estimate of link travel time is a question of increasing interest. Although it usually is assumed that link travel time is normally distributed, it is shown, on the basis of simulation results, that sometimes this is not true. A heuristic of determining the minimum number of probe vehicles required is developed to accommodate this situation. In addition, the impact of traffic volume on the required probe vehicle number is discussed.
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Shehada, Mohammad K. H., and Alexandra Kondyli. "Evaluation of Ramp Metering Impacts on Travel Time Reliability and Traffic Operations through Simulation." Journal of Advanced Transportation 2019 (January 20, 2019): 1–12. http://dx.doi.org/10.1155/2019/8740158.
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Ramp metering has been found to improve traffic conditions on the freeway mainline by breaking the platoons of ramp vehicles minimizing turbulence at the merge locations. The majority of the ramp metering evaluation studies have examined traffic performance under specific demand conditions, whereas travel time reliability and variability aspects have not been adequately addressed. This paper focuses on evaluating two well-known ramp metering algorithms in terms of travel time reliability as well as other performance measures such as queue lengths, throughput, and congestion duration, looking at a wide range of traffic demands throughout a calendar year. The evaluation was done through simulating an 8-mile corridor in Kansas City, KS. The results showed localized improvements due to ramp metering at the northern section of the facility, in terms of travel time reliability, throughput, and congestion duration. It was also shown that ramp metering may cause a new (possibly “hidden”) bottleneck to occur downstream, thus diluting its overall benefits when looking at an entire freeway facility. It is further noted that although ALINEA performed better than HERO on the mainline, traffic operations on the on-ramps significantly deteriorated using isolated control.
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El Esawey, Mohamed, and Tarek Sayed. "Travel time estimation in urban networks using limited probes data." Canadian Journal of Civil Engineering 38, no. 3 (March 2011): 305–18. http://dx.doi.org/10.1139/l11-001.
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Travel time is a simple and robust network performance measure that is well understood by the public. However, travel time data collection can be costly especially if the analysis area is large. This research proposes a solution to the problem of limited network sensor coverage caused by insufficient sample size of probe vehicles or inadequate numbers of fixed sensors. Within a homogeneous road network, nearby links of similar character are exposed to comparable traffic conditions, and therefore, their travel times are likely to be positively correlated. This correlation can be useful in developing travel time relationships between nearby links so that if data becomes available on a subset of these links, travel times of their neighbours can be estimated. A methodology is proposed to estimate link travel times using available data from neighbouring links. To test the proposed methodology, a case study was undertaken using a VISSIM micro-simulation model of downtown Vancouver. The simulation model was calibrated and validated using field traffic volumes and travel time data. Neighbour links travel time estimation accuracy was assessed using different error measurements and the results were satisfactory. Overall, the results of this research demonstrate the feasibility of using neighbour links data as an additional source of information to estimate travel time, especially in case of limited coverage.
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Suzuki, Hironori, Takashi Nakatsuji, Yordphol Tanaboriboon, and Kiyoshi Takahashi. "Dynamic Estimation of Origin-Destination Travel Time and Flow on a Long Freeway Corridor: Neural Kalman Filter." Transportation Research Record: Journal of the Transportation Research Board 1739, no. 1 (January 2000): 67–75. http://dx.doi.org/10.3141/1739-09.
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A model was formulated for estimating dynamic origin-destination (O-D) travel time and flow on a long freeway with a neural Kalman filter originally developed by the authors. The model predicts O-D travel times and flows simultaneously by using traffic detector data such as link traffic volumes, spot speeds, and off-ramp volumes. The model is based on a Kalman filter that consists of two equations: state and measurement. First, the state and measurement equations of the Kalman filter were modified to consider the influence of traffic states for some previous time steps. Then artificial neural network models were integrated with the Kalman filter to enable nonlinear formulations of the state and measurement equations. Finally, a macroscopic traffic flow simulation model was introduced to simulate traffic states on a freeway in advance and predict traffic variables such as O-D travel times, link traffic volumes, spot speeds, and off-ramp volumes. The new model was compared with a regression Kalman filter in which the state and measurement equations are defined by regression models. The numerical analysis indicated that the new model was capable of estimating nonlinearity of dynamic O-D travel time and flow and helped to improve their estimation precision under free-flow traffic states as well as congested flow states.
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Hansen, Blake G., Peter T. Martin, and H. Joseph Perrin. "SCOOT Real-Time Adaptive Control in a CORSIM Simulation Environment." Transportation Research Record: Journal of the Transportation Research Board 1727, no. 1 (January 2000): 27–30. http://dx.doi.org/10.3141/1727-04.
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The manner in which the adaptive signal control system SCOOT (Split, Cycle, Offset Optimization Technique) has been connected to the CORSIM traffic simulation model is described. To demonstrate the connection, CORSIM simulates the traffic activity of a six-node traffic network under SCOOT’s adaptive traffic signal control. CORSIM’s “virtual detectors” provide the necessary data for SCOOT optimization in real time. In a completed loop, the optimized signal timing is then communicated from SCOOT to CORSIM, which implements the timing and updates the traffic simulation. This means that SCOOT is now functioning in an entirely simulated environment. A comparison of delay and travel time is presented for a six-intersection street network under SCOOT control and under fixed-time area control optimized with TRANSYT-7F. The results show reductions in delay and numbers of stops of 20 to 30 percent. Previously, the measurement of the benefit of adaptive control has been limited to evaluations of systems after implementation. It is shown how SCOOT can now be evaluated under various network traffic conditions in a simulation environment and tested on a specific city network to evaluate the benefits before capital costs are committed.
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Cortés, Cristián E., Riju Lavanya, Jun-Seok Oh, and R. Jayakrishnan. "General-Purpose Methodology for Estimating Link Travel Time with Multiple-Point Detection of Traffic." Transportation Research Record: Journal of the Transportation Research Board 1802, no. 1 (January 2002): 181–89. http://dx.doi.org/10.3141/1802-20.
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A methodology was developed to find appropriate travel times for highway links using data from point detectors that could be at various points within the link or could even be outside the link. The travel times were found using a definition that the appropriate value is the one experienced by a virtual vehicle reaching the midpoint of the link at the midpoint of the time step. A simple iterative scheme was proposed to find the travel time profiles. The accuracy of the scheme depends on whether aggregated detector data or individual vehicle spot speeds are used. Comparison of estimated travel times with actual experienced travel times of all vehicles in a microscopic simulation showed the technique to give very good results, comparable with having a high number of probe vehicles reporting travel times.
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Mittal, Archak, Hani S. Mahmassani, and Alireza Talebpour. "Network Flow Relations and Travel Time Reliability in a Connected Environment." Transportation Research Record: Journal of the Transportation Research Board 2622, no. 1 (January 2017): 24–37. http://dx.doi.org/10.3141/2622-03.
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Connected vehicle technology provides the opportunity to create a connected network of vehicles and infrastructure. In such a network, individual vehicles can communicate with each other and with the infrastructure, including a traffic management center. The effects of connectivity on reducing congestion and improving throughput and reliability have been extensively investigated at the segment (facility) level. To complement the segment-level studies and to assess the large-scale effects of connectivity, this paper presents a networkwide evaluation of the effect of connectivity on travel time reliability. This study uses a microscopic simulation framework to establish the speed–density relationships at different market penetration rates (MPRs) of connected vehicles. Calibrated speed–density relationships are then used as inputs to the mesoscopic simulation tools to simulate the networkwide effects of connectivity. The Chicago, Illinois, and Salt Lake City, Utah, networks are simulated. Numerical results from the simulations confirm that the linear relationship between distance-weighted travel time rate and standard deviation holds for both networks and is not affected by either the demand level or the MPR of connected vehicles. In addition, with an increase in the MPR of connected vehicles, the network attains a lower maximum density and gets an increased flow rate for the same density level. Highly connected environment has the potential to help a congested network to recover from a breakdown and avoid gridlock. It is shown that a connected environment can improve a system’s performance by providing increased traffic flow rate and better travel time reliability at all demand levels.
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Wang, Chen, and Chengcheng Xu. "On the Effects of Various Measures of Performance Selections on Simulation Model Calibration Performance." Journal of Advanced Transportation 2018 (December 20, 2018): 1–16. http://dx.doi.org/10.1155/2018/3839814.
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Objective. This paper examines the effects of various measures of performance (MOP) selections on simulation model calibration performance, in terms of reflecting actual traffic conditions and vehicle interactions. Method. Two intersections in Shanghai were selected for simulation model calibration, one for testing and another for validation. Three effective MOPs were utilized, including average travel time (i.e., time passing the intersection), average queue length, and vehicle headway distribution. The counts of three types of traffic conflicts (i.e., crossing, rear-end, and lane change) were used as safety MOPs. Those MOPs, as calibration objectives, were examined and compared. Results. The results of the testing site showed that different effective MOPs had their own advantages: average travel time appeared to be the best in reflecting lane change and rear-end conflicts while headway distribution performed the best consistency between simulated and actual crossing conflicts. Compared to the safety MOPs, average travel time and headway distribution still performed better, in terms of resulting in more similar simulated conflict metrics (e.g., TTC, PET) to actual ones. A multicriteria calibration strategy based on average travel time and headway distribution generally had better performances in reflecting actual traffic conditions and vehicle interactions than using any single effective or safety MOP. Similar results were found for the validation site. Conclusion. To simulate actual traffic conditions and vehicle interactions, multiple effective MOPs could be simultaneously considered for model calibration, instead of using safety MOPs.
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Kim, Seung-Jun, Wonho Kim, and L. R. Rilett. "Calibration of Microsimulation Models Using Nonparametric Statistical Techniques." Transportation Research Record: Journal of the Transportation Research Board 1935, no. 1 (January 2005): 111–19. http://dx.doi.org/10.1177/0361198105193500113.
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The calibration of traffic microsimulation models has received widespread attention in transportation modeling. A recent concern is whether these models can simulate traffic conditions realistically. The recent widespread deployment of intelligent transportation systems in North America has provided an opportunity to obtain traffic-related data. In some cases the distribution of the traffic data rather than simple measures of central tendency such as the mean, is available. This paper examines a method for calibrating traffic microsimulation models so that simulation results, such as travel time, represent observed distributions obtained from the field. The approach is based on developing a statistically based objective function for use in an automated calibration procedure. The Wilcoxon rank–sum test, the Moses test and the Kolmogorov–Smirnov test are used to test the hypothesis that the travel time distribution of the simulated and the observed travel times are statistically identical. The approach is tested on a signalized arterial roadway in Houston, Texas. It is shown that potentially many different parameter sets result in statistically valid simulation results. More important, it is shown that using simple metrics, such as the mean absolute error, may lead to erroneous calibration results.
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Juri, Natalia Ruiz, Avinash Unnikrishnan, and S. Travis Waller. "Integrated Traffic Simulation–Statistical Analysis Framework for Online Prediction of Freeway Travel Time." Transportation Research Record: Journal of the Transportation Research Board 2039, no. 1 (January 2007): 24–31. http://dx.doi.org/10.3141/2039-03.
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Lim, Sung Han. "Analysis on an Effect from the Build-up of Incident Management System." Advanced Materials Research 271-273 (July 2011): 651–56. http://dx.doi.org/10.4028/www.scientific.net/amr.271-273.651.
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If an incident occurs on the road, the normal flow of traffic stream is interrupted and the road capacity reduces. This thus leads to huge social, economical losses, such as traffic congestion, air pollution, etc. This study was conducted to examine an effect on an incident management system by carrying out an simulation analysis and an social cost analysis. For the simulation analysis, incidents in a normal situation were compared with those in an incidental situation and thus travel time, queue length, and accident duration were selected as an evaluation indicator. It was analyzed that after an incident situation occurs, the length of vehicle in waiting rapidly increases and thus travel time also largely increases. To make an social cost analysis, vehicle operation cost (VOC) and vehicle operation time (VOT) were used an index. The results showed that travel time cost per driver and vehicle in an incidental situation all increased, compared with that in a normal situation. It was also observed that the longer the lasting hours are, the higher the travel time increases.
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Mehrara Molan, Amirarsalan, and Joseph E. Hummer. "Simulation Modeling of Pedestrian Performance in the New Synchronized and Milwaukee B Interchanges versus Existing Designs." Transportation Research Record: Journal of the Transportation Research Board 2672, no. 35 (June 17, 2018): 151–60. http://dx.doi.org/10.1177/0361198118781652.
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Most U.S. highway agencies recognize the importance of designing safe, short, and comfortable paths for pedestrians. Providing such an acceptable condition for pedestrians requires specific attention at intersections and service interchanges due to their interaction with other modes of transportation. The main objective of this research was to analyze pedestrian operation at two new service interchanges—the synchronized and Milwaukee B interchanges—in comparison with four existing designs. The analysis consists of three main parts: (1) a general comparison among the designs for pedestrian performances in terms of safety, travel time, and the level of service; (2) investigation of the effects of vehicles on pedestrian performance; and (3) modeling the impact of pedestrians on the traffic operation of vehicles. A comprehensive series of simulation tests were run using VISSIM and Synchro to study the pedestrian performance of interchanges in various situations of traffic volume, turning traffic ratio, traffic distribution, and percentage of heavy vehicles. The results indicated that a relatively safe condition is expected for pedestrians in the proposed new designs in comparison with the existing interchanges; however, the pedestrians’ travel time was lower in all the existing designs than in the new designs except the diverging diamond interchange (DDI). The DDI, one of the most popular alternative interchanges, showed the worst performance in all the aspects of the pedestrian analysis. Despite the very good performance of conventional diamond interchange regarding pedestrian travel time and safety, pedestrians could have a significant negative impact on vehicle travel time through a diamond.
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Shokrolah Shirazi, Mohammad, Hung-Fu Chang, and Shahab Tayeb. "Turning Movement Count Data Integration Methods for Intersection Analysis and Traffic Signal Design." Sensors 22, no. 19 (September 20, 2022): 7111. http://dx.doi.org/10.3390/s22197111.
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Traffic simulation is widely used for modeling, planning, and analyzing different strategies for traffic control and road development in a cost-efficient manner. In order to perform an intersection simulation, random vehicle trip data are typically applied to an intersection network, making them unrealistic. In this paper, we address this issue by presenting two different methods of incorporating actual turning movement count (TMC) data and comparing their similarity for intersection simulation and analysis. The TMC of three intersections in Las Vegas are estimated separately for one hour using a developed vision-based tracking system and they are incorporated into Simulation of Urban MObility (SUMO) for estimating traffic measurements and traffic signal design. t-tests with a 95% confidence interval on the simulation variables demonstrate the importance of using a route-based creation method which injects vehicles into a simulation environment based on the frame-level departure time. The intersection analyses and comparisons are performed based on estimated traffic measurements such as travel time, density, lane density, occupancy, and normalized waiting time. Since the critical edge of each intersection network is identified based on a higher normalized waiting time, new traffic signal designs are suggested based on the actual critical turning movements and improvements in vehicle travel time are achieved to better accommodate the actual traffic demand.
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Bhattacharyya, Kinjal, Bhargab Maitra, and Manfred Boltze. "Calibration of Micro-Simulation Model Parameters for Heterogeneous Traffic using Mode-Specific Performance Measure." Transportation Research Record: Journal of the Transportation Research Board 2674, no. 1 (January 2020): 135–47. http://dx.doi.org/10.1177/0361198119900130.
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Calibration is an essential prerequisite to scenario evaluations using traffic micro-simulation models (TMMs). In the context of mixed-traffic operations, where different fast and slow moving vehicular modes form a heterogeneous environment, a well-calibrated model needs to give adequate importance to each mode to realistically replicate the complex interactions in the traffic stream. This paper presents a methodology for calibrating TMMs for such mixed-traffic conditions. A combination of vehicle mode-specific travel time distributions is adopted as the performance measure for the calibration. To aid practitioners, each step of the methodology is demonstrated using a VISSIM simulator considering a signalized corridor in the Kolkata metro city, India. The work includes genetic algorithm (GA)-based optimization for obtaining mode-specific parameter sets. The Kolmogorov-Smirnov test is carried out to compare the travel time distributions of different modes. The calibrated model is also validated considering several signalized approaches along the calibrated study corridor. The results show that the methodology is successful in developing a model for non-lane based mixed-traffic operations with vehicle mode-specific optimized parameter sets.
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Zhang, Jian, Yang Cheng, Shanglu He, and Bin Ran. "Improving method of real-time offset tuning for arterial signal coordination using probe trajectory data." Advances in Mechanical Engineering 9, no. 1 (January 2017): 168781401668335. http://dx.doi.org/10.1177/1687814016683355.
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In the environment of intelligent transportation systems, traffic condition data would have higher resolution in time and space, which is especially valuable for managing the interrupted traffic at signalized intersections. There exist a lot of algorithms for offset tuning, but few of them take the advantage of modern traffic detection methods such as probe vehicle data. This study proposes a method using probe trajectory data to optimize and adjust offsets in real time. The critical point, representing the changing vehicle dynamics, is first defined as the basis of this approach. Using the critical points related to different states of traffic conditions, such as free flow, queue formation, and dissipation, various traffic status parameters can be estimated, including actual travel speed, queue dissipation rate, and standing queue length. The offset can then be adjusted on a cycle-by-cycle basis. The performance of this approach is evaluated using a simulation network. The results show that the trajectory-based approach can reduce travel time of the coordinated traffic flow when compared with using well-defined offline offset.
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Zhao, Jiandong, Yujie Guo, and Xiaohong Duan. "Dynamic Path Planning of Emergency Vehicles Based on Travel Time Prediction." Journal of Advanced Transportation 2017 (2017): 1–14. http://dx.doi.org/10.1155/2017/9184891.
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The dynamic paths planning problem of emergency vehicles is usually constrained by the factors including time efficiency, resources requirement, and reliability of the road network. Therefore, a two-stage model of dynamic paths planning of emergency vehicles is built with the goal of the shortest travel time and the minimum degree of traffic congestion. Firstly, according to the dynamic characteristics of road network traffic, a polyline-shaped speed function is constructed. And then, based on the real-time and historical data of travel speed, a new kernel clustering algorithm based on shuffled frog leaping algorithm is designed to predict the travel time. Secondly, combined with the expected travel time, the traffic congestion index is defined to measure the reliability of the route. Thirdly, aimed at the problem of solving two-stage target model, a two-stage shortest path algorithm is proposed, which is composed of K-paths algorithm and shuffled frog leaping algorithm. Finally, based on the data of floating vehicles of expressway in Beijing, a simulation case is used to verify the above methods. The results show that the optimization path algorithm meets the needs of the multiple constraints.
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Marchal, Fabrice, and André de Palma. "Measurement of Uncertainty Costs with Dynamic Traffic Simulations." Transportation Research Record: Journal of the Transportation Research Board 2085, no. 1 (January 2008): 67–75. http://dx.doi.org/10.3141/2085-08.
Full textAbstract:
Nonrecurrent congestion in transportation networks occurs as a consequence of stochastic factors affecting demand and supply. Intelligent transportation systems such as advanced traveler information systems and advanced traffic management systems are designed to reduce the impacts of nonrecurrent congestion by providing information to a fraction of users or by controlling the variability of traffic flows. For these reasons, the design of these systems requires a reliable forecast of nonrecurrent congestion. A new method is proposed to measure the impacts of nonrecurrent congestion on travel costs by taking risk aversion into account. The traffic model is based on the dynamic traffic simulation model METROPOLIS. Incidents are generated randomly by reducing the capacity of the network. Users can instantaneously adapt to the unexpected travel conditions or can also change their behavior through a day-to-day adjustment process. Comparisons with incident-free simulations provide a benchmark for potential travel time savings that can be brought about by a state-of-the-art information system. The impact of variable travel conditions is measured by describing the willingness to pay to avoid risky or unreliable journeys. Indeed, for risk-averse drivers, any uncertainty corresponds to a utility loss. This utility loss is computed for several levels of network disruption. The main result of the study is that the utility loss due to uncertainty is of the same order of magnitude as the total travel costs.
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Liu, Qingwu, and Hongwen He. "The velocity regulation of power consumption with traffic lights for electric vehicles." Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering 233, no. 9 (August 2019): 2312–22. http://dx.doi.org/10.1177/0954407019856220.
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Traffic conditions, especially at traffic crossings, have a great impact on the power consumption of vehicles. Regulating velocity using the information between vehicles and traffic systems can decrease the power consumption. This article mainly focuses on an electric vehicle equipped with radar sensors, which can get the traffic information from upto a 100-m-long distance between the controlled vehicle and the traffic lights. Using the information gathered from sensors, the top-level control unit regulates the velocity aiming at lower power consumption. When traveling through crossings, two different traffic conditions are discussed. For the first condition, no other vehicles run between the controlled vehicle and the traffic lights. Only the traffic lights information is considered. For the second condition, the controlled vehicle follows other vehicles to go through the crossing. The information of the nearest front vehicle and traffic lights is taken into consideration. In summary, the traffic lights information, including the controlled vehicle current state, the traffic lights remaining time, and the velocity and distance of the nearest former vehicle (for the second condition) are sent to the top-level control unit. Then, the control unit calculates a velocity list, which will be sent to the vehicle control unit. A simulation is conducted using a traffic simulation software named “Simulation of Urban Mobility” to verify the algorithm. The simulation results indicate that the energy efficiency is improved. For the first condition, the travel time is reduced by 8.27%, and the power consumption is reduced by 18.7%. For the second condition, the power consumption is reduced by 2.96%. Finally, for a 5.8-km driving cycle containing both conditions, the travel time is reduced by 6.9% and electricity consumption is reduced by 9.51%.
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Di, Shan, Changxuan Pan, and Bin Ran. "Stochastic Multiclass Traffic Assignment with Consideration of Risk-Taking Behaviors." Transportation Research Record: Journal of the Transportation Research Board 2085, no. 1 (January 2008): 111–23. http://dx.doi.org/10.3141/2085-13.
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A study of the problem of predicting traffic flows under traffic equilibrium in a stochastic transportation network is presented. Travelers’ risk-taking behaviors are explicitly modeled with respect to probabilistic travel times. Traveling risks are quantified from the travel time distributions directly and are embedded in the route choice conditions. The classification of risk-neutral, risk-averse, and risk-prone travelers is based on their preferred traveling risks. The formulation of the model clarifies that travelers with different risk preferences have the same objective–to save travel time cost–though they may make different route choices. The proposed solution algorithm is applicable for networks with normal distribution link travel times theoretically. Further simulation analysis shows that it can also be applied to approximate the equilibrium network flows for other frequently used travel time distribution families: gamma, Weibull, and log-normal. The proposed model was applied to a test network and a medium-sized transportation network. The results demonstrate that the model captures travelers’ risk-taking behaviors more realistically and flexibly compared with existing stochastic traffic equilibrium models.
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Sun, Lu, Wenjun Gu, and Hani Mahmassani. "Estimation of expected travel time using the method of moment." Canadian Journal of Civil Engineering 38, no. 2 (February 2011): 154–65. http://dx.doi.org/10.1139/l10-115.
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Daily travel time is cast into a framework of nonstationary stochastic process. For a fixed value of departure time in a day, travel time given origin, destination, and route information, is treated as a random variable. For a specific date, travel time is treated as a deterministic function of departure time t. Under this framework, the expected travel time for a given departure time is defined as an ensemble mean travel time (EMTT) over a number of days. The method of moment is proposed to compute EMTT based on a hypothetical piecewise constant speed trajectory for travel time estimation. The advantage of the method of moment for EMTT estimation is that it only requires ensemble mean and ensemble variance of spot speed information at point detectors, which is much easier and cost-effective to get than obtaining collections of massive spot speed data per se. The result is compared against Monte Carlo simulation and direct sampling based simulation. The proposed method of moment approach provides accurate estimation of EMTT (e.g., the expected travel time estimation) under a wide range of traffic conditions (e.g., free flow and congestion).
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Fimbombaya, Haji Said, Nerey H. Mvungi, Ndyetabura Y. Hamisi, and Hashimu U. Iddi. "Performance Evaluation of Magnetic Wireless Sensor Networks Algorithm for Traffic Flow Monitoring in Chaotic Cities." Modelling and Simulation in Engineering 2018 (October 16, 2018): 1–11. http://dx.doi.org/10.1155/2018/2591304.
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Traffic flow monitoring involves the capturing and dissemination of real-time traffic flow information for a road network. When a vehicle, a ferromagnetic object, travels along a road, it disturbs the ambient Earth’s magnetic field, causing its distortion. The resulting distortion carries vehicle signature containing traffic flow related information such as speed, count, direction, and classification. To extract such information in chaotic cities, a novel algorithm based on the resulting magnetic field distortion was developed using nonintrusive sensor localization. The algorithm extracts traffic flow information from resulting magnetic field distortions sensed by magnetic wireless sensor nodes located on the sides of the road. The model magnetic wireless sensor networks algorithm for local Earth’s magnetic field performance was evaluated through simulation using Dar es Salaam City traffic flow conditions. Simulation results for vehicular detection and count showed 93% and 87% success rates during normal and congested traffic states, respectively. Travel Time Index (TTI) was used as a congestion indicator, where different levels of congestion were evaluated depending on the traffic state with a performance of 87% and 88% success rates during normal and congested traffic flow, respectively.
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Hellinga, Bruce, and Michel Van Aerde. "An overview of a simulation study of the Highway 401 freeway traffic management system." Canadian Journal of Civil Engineering 21, no. 3 (June 1, 1994): 439–54. http://dx.doi.org/10.1139/l94-048.
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This paper discusses the application of the network traffic simulation model INTEGRATION to a 35-km section of Highway 401 in Toronto, Canada. Results for the eastbound direction from 4 a.m. to 12 noon are presented. Existing freeway conditions are quantified using data from the COMPASS freeway traffic management system and from a floating car travel time survey. Variations that exist in observed link flows and trip travel durations over time of day and day of week are examined. The extent to which COMPASS data meets the data requirements of the INTEGRATION model is examined. Since the current COMPASS system encompassed less than 50% of the network analyzed, complications arise in accurately estimating the prevailing time-varying origin–destination demands, as well as in comprehensively validating the simulation model's results. The present level of model calibration results in a correlation coefficient of estimated and observed link flows of 97.23%. This level of discrepancy is generally within the natural day-to-day variations that are inherent within the system. However, travel times estimated by the simulation model tend to be underestimated, particularly for the express lanes. Further model calibration, to improve the model's results, is deferred until more of the network is covered by COMPASS. Key words: traffic simulation, COMPASS, model calibration, model validation, speed–flow relationship.
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Deng, Wen, Li Min Jia, and Hong Hui Dong. "Multi-Objective Optimization Model for Urban Traffic Intersection Control Based on Data Fusion." Advanced Materials Research 156-157 (October 2010): 505–10. http://dx.doi.org/10.4028/www.scientific.net/amr.156-157.505.
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A new multi-objective optimization control strategy for urban intersection is proposed, which takes the degree of smooth and the degree of equilibrium as objectives. The new method is not limited to the traditional basic traffic parameters, such as delay and queue length.etc, but Applying data fusion technology, by multiple integrating on the basic traffic parameters, the real-time multi-objective values are achieved. The degree of the smooth quantitatively denotes the forced travel time extension because of traffic signal control, saturated traffic flow.ect. The degree of equilibrium denotes the equilibrium degree of traffic flow in space. Illustrating an intersection in Beijing, a simulation model in Paramics is built. The simulation results show that the proposed multi-objective control methods can not only reduce the traffic flow delay, but also makes traffic flow distributing equilibrium in each phase of intersection. This approach is consistent with Chinese saturated traffic flow characteristics.
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Chen, Rongsheng, and Michael W. Levin. "Dynamic User Equilibrium of Mobility-on-Demand System with Linear Programming Rebalancing Strategy." Transportation Research Record: Journal of the Transportation Research Board 2673, no. 1 (January 2019): 447–59. http://dx.doi.org/10.1177/0361198118821629.
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Mobility-on-demand (MoD) services are provided by multiple competing companies. In their competition for travelers, they need to provide minimum travel costs, or travelers will switch to competitors. This study developed a dynamic traffic assignment of MoD systems. A static traffic assignment (STA) model is first defined. When demand is asymmetric, empty rebalancing trips are required to move vehicles to traveler origins, and the optimal rebalancing flows are found by a linear program. Because of the time-dependent nature of traveler demand, the model was converted to dynamic traffic assignment (DTA). The method of successive averages, which is provably convergent for STA, was used to find dynamic user equilibrium (DUE). The simulation was conducted on two networks. The MoD system was simulated with different fleet sizes and demands. The results showed that the average total delay and travel distance decreased with the increase in fleet size whereas the average on-road travel time increased with the fleet size. The result of traffic assignment of one network with MoD system was compared with a network where all travelers use private vehicles. The results showed that the network with MoD system created more trips but less traffic congestion.
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LIN, Peiqun, Chuhao ZHOU, and Yang CHENG. "A Systematic Cooperation Method for In-Car Navigation Based on Future Time Windows." Promet - Traffic&Transportation 34, no. 3 (May 31, 2022): 381–96. http://dx.doi.org/10.7307/ptt.v34i3.3946.
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Traffic congestion has become a severe problem, af-fecting travellers both mentally and economically. To al-leviate traffic congestion, this paper proposes a method using a concept of future time windows to estimate the future state of the road network for navigation. Through our method, we can estimate the travel time not only based on the current traffic state, but the state that ve-hicles will arrive in the future. To test our method, we conduct experiments based on Simulation of Urban MO-bility (SUMO). The experimental results show that the proposed method can significantly reduce the overall travel time of all vehicles, compared to the benchmark Dijkstra algorithm. We also compared our method to the Dynamic User Equilibrium (DUE) provided by SUMO. The experimental results show that the performance of our method is a little better than the DUE. In practice, the proposed method takes less time for computation and is insensitive to low driver compliance: with as low as 40% compliance rate, our method can significantly im-prove the efficiency of the unsignalised road network. We also verify the effectiveness of our method in a signalised road network. It also demonstrates that our method can assign traffic efficiently.
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Zhou, Weiyi, Mofeng Yang, Minha Lee, and Lei Zhang. "Q-Learning-Based Coordinated Variable Speed Limit and Hard Shoulder Running Control Strategy to Reduce Travel Time at Freeway Corridor." Transportation Research Record: Journal of the Transportation Research Board 2674, no. 11 (September 16, 2020): 915–25. http://dx.doi.org/10.1177/0361198120949875.
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To increase traffic mobility and safety, several types of active traffic management (ATM) strategies, such as variable speed limit (VSL), ramp metering, dynamic message signs, and hard shoulder running (HSR), are adopted in many countries. While all kinds of ATM strategies show promise in releasing traffic congestion, many studies indicate that stand-alone strategies have very limited capability. To remedy the defects of stand-alone strategies, cooperative ATM strategies have caught researchers’ attention and different combinations have been studied. In this paper, a coordinated VSL and HSR control strategy based on a reinforcement learning technique—Q-learning—is proposed. The proposed control strategy bridges up a direct connection between the traffic flow data and the ATM control strategies via intensive self-learning processes, thus reducing the need for human knowledge. A typical congested interstate highway, I-270 in Maryland, United States, was selected as the study area to evaluate the proposed strategy. A dynamic traffic assignment simulation model was introduced to calibrate the network with real-world data and was used to evaluate the regional impact of the proposed algorithm. Simulation results indicated that the proposed coordinated control could reduce corridor travel time by up to 27%. The performance of various control strategies were also compared. The results suggested that the proposed strategy outperformed the stand-alone control strategies and the traditional feedback-based VSL strategy in mitigating congestion and reducing travel time on the freeway corridor.
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Dwivedi, Avinash, Ramoo Ram, and Ravi Kant Pareek. "Microscopic Simulation-Based Model analysis at Jaipur." International Journal for Research in Applied Science and Engineering Technology 10, no. 4 (April 30, 2022): 470–79. http://dx.doi.org/10.22214/ijraset.2022.41290.
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Abstract: Socio-Economic development of a country includes sustainable transportation system. As simulation is safer, less expensive and faster than field implementation and testing, Microscopic simulation models have been widely used in transportation operations and management analysis. The accuracy and reliability decide the usefulness of these models in making design and traffic control. Nowin India, VISSIM which is microscopic traffic simulation software is used. However, modifications to the default behavioral parameters are essential to effectively simulate Indian heterogeneous traffic conditions. In this study, the queue length and travel time of link connected to Narayan Singh Circle and Trimurti Circle intersection is analyzed before and after transfer the bus stop at Narayan Singh Circle to the periphery of city. For this, intersections are designed in VISSIM software and traffic flow performance is validated via VISSIM. Then average vehicular delay under different traffic volumes was analyzed. The results are finally compared before and after transfer the bus stop at Narayan Singh Circle to the peripheryof city. Keywords: Non-destructive Testing, Concrete, Structural Health Monitoring, Ultrasonic Pulse Velocity,Rebound Hammer.
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Toledo, Tomer, Omar Mansour, and Jack Haddad. "Optimal Dynamic Tolls for Managed Lanes." Transportation Research Record: Journal of the Transportation Research Board 2606, no. 1 (January 2017): 28–37. http://dx.doi.org/10.3141/2606-04.
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This paper presents a real-time simulation-based control framework to determine dynamic toll rates to optimize an operator's objective subject to various operational and contractual constraints, such as smooth toll rate changes and maintenance of prescribed levels of service on the toll lane. The toll-setting system incorporates models to predict both the vehicle arrival process upstream of the toll lane facility and drivers’ choice whether to use the toll lanes as a function of the toll rate and travel times presented to drivers within the information system. A macroscopic traffic simulation model is used to predict the flow conditions within the prediction horizon. The travel times provided to users as information and the travel times predicted by the traffic flow model are iterated until consistency between them is obtained. The whole process is embedded within an optimization algorithm that sets tolls to optimize a given objective function. Several case studies demonstrate the use of this framework and its potential to provide useful toll settings.
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Wang, Xu, Tony Z. Qiu, Lei Niu, Ruhua Zhang, and Lu Wang. "A micro-simulation study on proactive coordinated ramp metering for relieving freeway congestion." Canadian Journal of Civil Engineering 43, no. 7 (July 2016): 599–608. http://dx.doi.org/10.1139/cjce-2016-0050.
Full textAbstract:
To relieve freeway congestion during peak periods, ramp metering (RM) is often implemented to control the input flow from onramps on freeways. Many studies focus on proactive coordinated RM controls; however, successful implementation of proactive RM control still requires a more accurate prediction model and a less complex control algorithm. To this end, this study tests a proactive RM approach in micro-simulation, with goals to improve network-wide travel time and traffic flow. A METANET-based dynamic traffic model was adopted as a prediction model within a predictive control framework. The evaluation revealed a 6.50% amelioration in total travel time on the mainline and a 2.52% reduction of total time spent in the network. The applied algorithm was compared with the HERO algorithm and implemented in various peak demand scenarios. This analysis could lead to efficient and effective field applications of proactive coordinated RM control to improve freeway operation.
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Smith, Tony E., Chao-Che Hsu, and Yueh-Ling Hsu. "Stochastic User Equilibrium Model with Implicit Travel Time Budget Constraint." Transportation Research Record: Journal of the Transportation Research Board 2085, no. 1 (January 2008): 95–103. http://dx.doi.org/10.3141/2085-11.
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Although time constraints on travel behavior have been widely recognized, little effort has been made to incorporate such constraints into the traditional stochastic user equilibrium (SUE) framework. The major objective of this research is to fill this gap by incorporating travel time constraints into the SUE model by means of a nonlinear perceived travel time function. This modified model, designated the travel time budget model, focuses primarily on discretionary travel behavior (such as shopping trips) and hence also allows the possibility of deferring travel decisions by incorporating an additional choice alternative designated the shop-less-frequently alternative. This model is compared with the traditional SUE model by using a simulated travel scenario on a test network designed to reflect a practical planning situation. The simulation shows that when attractiveness levels are increased by the introduction of a new shopping opportunity, the presence of travel time constraints can lead to significantly smaller predicted travel volumes than those of the traditional SUE model. More important, it shows that the overall pattern of travel can be quite different. In particular, travel to the shopping destination with enhanced attractiveness can actually decrease for some origin locations. The findings suggest that when an attempt is made to evaluate the impact of planning alternatives on future traffic patterns, it is vital to consider not only the cost of time itself but also the time trade-offs between travel and other human activities.
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Rahimi, Amir Masoud, Maxim A. Dulebenets, and Arash Mazaheri. "Evaluation of Microsimulation Models for Roadway Segments with Different Functional Classifications in Northern Iran." Infrastructures 6, no. 3 (March 15, 2021): 46. http://dx.doi.org/10.3390/infrastructures6030046.
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Industrialization, urban development, and population growth in the last decades caused a significant increase in congestion of transportation networks across the world. Increasing congestion of transportation networks and limitations of the traditional methods in analyzing and evaluating the congestion mitigation strategies led many transportation professionals to the use of traffic simulation techniques. Nowadays, traffic simulation is heavily used in a variety of applications, including the design of transportation facilities, traffic flow management, and intelligent transportation systems. The literature review, conducted as a part of this study, shows that many different traffic simulation packages with various features have been developed to date. The present study specifically focuses on a comprehensive comparative analysis of the advanced interactive microscopic simulator for urban and non-urban networks (AIMSUN) and SimTraffic microsimulation models, which have been widely used in the literature and practice. The evaluation of microsimulation models is performed for the four roadway sections with different functional classifications, which are located in the northern part of Iran. The SimTraffic and AIMSUN microsimulation models are compared in terms of the major transportation network performance indicators. The results from the conducted analysis indicate that AIMSUN returned smaller errors for the vehicle flow, travel speed, and total travel distance. On the other hand, SimTraffic provided more accurate values of the travel time. Both microsimulation models were able to effectively identify traffic bottlenecks. Findings from this study will be useful for the researchers and practitioners, who heavily rely on microsimulation models in transportation planning.
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Frechette, Luc A., and Ata M. Khan. "Bayesian Regression-Based Urban Traffic Models." Transportation Research Record: Journal of the Transportation Research Board 1644, no. 1 (January 1998): 157–65. http://dx.doi.org/10.3141/1644-17.
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A Bayesian regression approach is used to develop equations for predicting travel time on central area streets with contributory variables that are intuitive and for which data are readily available in most transportation agencies. In development of multivariate regression models, two disparate sources of information are used: ( a) a priori (what is known before an experiment), and ( b) experimental data (information derived from an experiment). Output of traffic simulation obtained from NETSIM was used as the source of a priori information, whereas the experimental data were obtained from video recordings of traffic operations on selected central business district streets. Bayesian regression software was used in a systematic framework for predictive model development. The developed equations were assessed and results were interpreted from a Bayesian perspective in relation to the various model iterations attempted. The final models provide reasonable predictions of actual travel times that drivers would experience during peak traffic periods in medium to large central business districts.
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Oh, Simon, Ravi Seshadri, Carlos Lima Azevedo, and Moshe E. Ben-Akiva. "Demand Calibration of Multimodal Microscopic Traffic Simulation using Weighted Discrete SPSA." Transportation Research Record: Journal of the Transportation Research Board 2673, no. 5 (April 8, 2019): 503–14. http://dx.doi.org/10.1177/0361198119842107.
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This paper presents a stochastic approximation framework to solve a generalized problem of off-line calibration of demand for a multimodal microscopic (or mesoscopic) network simulation using aggregated sensor data. A key feature of this problem is that demand, although typically treated as a continuous variable is in fact discrete, particularly in the context of agent-based simulation. To address this, we first use a discrete version of the weighted simultaneous perturbation stochastic approximation (W-DSPSA) algorithm for minimizing a generalized least squares (GLS) objective (that measures the distance between simulated and observed measurements), defined over discrete sets. The algorithm computes the gradient at each iteration using a symmetric discrete perturbation of the calibration parameters and a multimodal weight matrix to improve the accuracy of the gradient estimate. The W-DSPSA algorithm is then applied to the large-scale calibration of multimodal origin–destination (OD) flows (including private vehicle (PVT) and public transit (PT) trips) in a microscopic network simulation model of Singapore. The results indicate that an acceptable margin of error on the vehicle loop count (VLC) and bus passenger count (BPC) are achieved at convergence with an improvement of 60%~80% in root mean squared errors. Lastly, we validate the calibration results with observed travel times on the network. Statistical comparison shows good agreements on both point-to-point travel time (PTT) and public buses’ stop-to-stop ride-time (SRT) with the field observations.
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Rakha, Hesham A., and Michel W. Van Aerde. "Comparison of Simulation Modules of TRANSYT and INTEGRATION Models." Transportation Research Record: Journal of the Transportation Research Board 1566, no. 1 (January 1996): 1–7. http://dx.doi.org/10.1177/0361198196156600101.
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The TRANSYT simulation/optimization model serves as an unofficial international standard against which many measure the efficiency of other methods of coordinating networks of traffic signals that operate at a constant and common cycle length. However, dynamics due to traffic rerouting, the simultaneous operation of adjacent traffic signals at different cycle lengths, the effect of queue spillbacks on the capacity of upstream links, and various forms of real-time intersection control cannot be modeled using a static model such as TRANSYT. This has created a unique niche for a more dynamic signal network simulation tool. Before modeling such special dynamic scenarios, there first exists a need to validate the static signal control features of such a model and to determine if its unique dynamic features still permit it to yield credible static results. This study has two objectives. First, it attempts to illustrate the extent to which estimates of vehicle travel time, vehicle delay, and number of vehicle stops are related when a standard static signal network is examined using both TRANSYT and INTEGRATION. Second, it strives to illustrate that the types of more complex signal timing problems, which at present cannot be examined by the TRANSYT model, can be examined using the dynamic features of INTEGRATION. The results are intended to permit a better appreciation of both their differences and similarities and permit a more informed decision as to when and where each model should be used. Also demonstrated is that INTEGRATION simulates traffic-signalized networks in a manner that is consistent with TRANSYT for conditions in which TRANSYT is valid. Specifically, the difference in total travel time and percentage of vehicle stops is within 5 percent. In addition, it is also shown that INTEGRATION can simulate conditions that represent the limitations to the current TRANSYT model, such as degrees of saturation in excess of 95 percent and adjacent signals operating at different cycle length durations. This analysis of the simulation features of TRANSYT and INTEGRATION is intended to be a precursor to a comparison of their respective optimization routines.
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Vandebona, U., and P. K. Upadhyay. "Simulation Modeling of Route Guidance Concept." Transportation Research Record: Journal of the Transportation Research Board 1573, no. 1 (January 1997): 44–51. http://dx.doi.org/10.3141/1573-07.
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The methodology of a simulation model developed at the University of New South Wales, Australia, for the evaluation of performance of Dynamic Route Guidance Systems (DRGS) is described. The microscopic simulation model adopts the event update simulation method and allows assessment of route guidance performance under different scenarios such as varying levels of participation in guidance technologies and different intensities of travel demand. This research is important for marketing, costing, and introducing route guidance and can assist planners in identifying suitable networks and traffic conditions for such systems. The example application investigates selected operating scenarios of intersection delay conditions under different compositions of participation rates in route guidance. Preliminary investigations indicate that the effectiveness of route guidance is related to the level of intersection delays. An interesting outcome of this application is the identification that in networks with intersection delays which vary with time, those motorists without guidance assistance strive to make better forecasts of travel time in order to assist their route selection. At low levels of intersection delays, some motorists appear to make more than one nonoptimal route selection.
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Li, Qing Yin, Rui Tang, and Zhang Lu Tan. "Based on Transcad of the Shortest Path Assignment Method." Advanced Materials Research 219-220 (March 2011): 1105–8. http://dx.doi.org/10.4028/www.scientific.net/amr.219-220.1105.
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Based on the Transcad all-or-nothing assignment model is a kind of static method; do not consider the travel time will be affected by traffic flow. The insufficient is that it does not conform to reality. In order to solve the all-or-nothing assignment model that to putting all of traffic flow on the shortest path, the text through the defining of the effective path and the traffic flow of the effective path to improve all-or-nothing assignment model. So the other road traffic flow can also assign and the results can reflect the assignment of urban traffic directly. It can be used to study the dynamic traffic assignment and traffic simulation analysis.
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Li, Yongyi, Shiqi Wang, Xiaorui Zhang, and Mengxing Lv. "Estimation and Reliability Research of Post-Earthquake Traffic Travel Time Distribution Based on Floating Car Data." Applied Sciences 12, no. 18 (September 11, 2022): 9129. http://dx.doi.org/10.3390/app12189129.
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To carry out the estimation and reliability research of post-earthquake traffic travel time, which has the great influence for efficient allocation of relief materials. By analyzing the relationship among floating vehicle trajectory, target path and road network path, the intermediate parameters of converting floating vehicle trajectory data into target path travel time were defined and improved. In addition, the road damage identification method relying on lane detection is applied for evaluating the damage of road after the earthquake through the image information. Then, Bayesian average adaptive kernel density estimation method was used to estimate the distribution of post-earthquake road travel time, and a new formula for calculating the reliability of road travel time after earthquake was proposed. According to the example simulation and analysis, the proposed post-earthquake road travel time distribution estimation and its reliability are verified. The results show that when the threshold value is determined, the travel time of the path before the earthquake is the most dependable, and with the increase in the earthquake damage index, the travel time of this road section becomes increasingly unreliable. However, after the earthquake, the peak probability density of road travel time distribution weakens, and the overall probability shifts to the direction of long time.
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Stathopoulos, Fotis G., and Robert B. Noland. "Induced Travel and Emissions from Traffic Flow Improvement Projects." Transportation Research Record: Journal of the Transportation Research Board 1842, no. 1 (January 2003): 57–63. http://dx.doi.org/10.3141/1842-07.
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Two scenarios for improving traffic flow are simulated and analyzed using the VISSIM microsimulation model and the Comprehensive Modal Emissions Model. Short-run and long-run emissions of CO, HC, NOx, and CO2 and fuel consumption are estimated. In the short run, with traffic volumes held constant, results demonstrate that the smoothing of traffic flow will result in reduced emissions. Long-run emissions are simulated by synthetically generating new trips into the simulated networks to represent potential induced travel. This is done until a “break-even” level of emissions for each pollutant and fuel consumption is reached that is equivalent to the base level before the traffic flow improvement was added. By also calculating short-run changes in travel time from the improvement, the travel time elasticity equivalents for each pollutant are calculated. These values are compared with travel time elasticities in the literature to evaluate whether long-run emissions benefits are likely to endure. Simulations are conducted using different assumptions of vehicle soak time to simulate cold-start and hot-stabilized operating modes. Results indicate that, in most cases, long-run emissions reductions are unlikely to be achieved under the two scenarios evaluated.
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Cho, Joongmin, Young-Joo Lee, Seongkwan Mark Lee, Ki Han Song, and Wonho Suh. "Analysis of Macroscopic Traffic Network Impacted by Structural Damage to Bridges from Earthquakes." Applied Sciences 11, no. 7 (April 3, 2021): 3226. http://dx.doi.org/10.3390/app11073226.
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Highway systems play a key role in providing mobility to society, especially during emergency situations, including earthquakes. Bridges in highway systems are susceptible to damage from earthquakes, causing traffic capacity loss leading to a serious impact on surrounding areas. To better prepare for such scenarios, it is important to estimate capacity loss and traffic disruptions from earthquakes. For this purpose, a traffic-capacity-analysisbased methodology was developed to model the performance of a transportation network immediately following an earthquake using a macroscopic multi-level urban traffic planning simulation model EMME4. This method employs the second order linear approximation (SOLA) traffic assignment and calculates total system travel time for various capacity loss scenarios due to bridge damage from earthquakes. It has been applied to Pohang City in Korea to evaluate the performance of traffic networks in various situations. The results indicate a significant increase in travel time and a decrease in travel speed as the intensity of an earthquake increases. However, the impact on traffic volume varies depending on the bridges. It is assumed that the location of the bridges and traffic routing patterns might be the main reason. The results are expected to help estimate the impact on transportation networks when earthquakes cause traffic capacity loss on bridges.
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Chen, Juan, Vijayan Sugumaran, and Peiyan Qu. "Connected and automated vehicle control at unsignalized intersection based on deep reinforcement learning in vehicle-to-infrastructure environment." International Journal of Distributed Sensor Networks 18, no. 7 (July 2022): 155013292211140. http://dx.doi.org/10.1177/15501329221114060.
Full textAbstract:
In order to reduce the number of vehicle collisions and average travel time when vehicles pass through an unsignalized intersection with connected and automated vehicle, an improved Double Dueling Deep Q Network method with Convolutional Neutral Network and Long Short-Term Memory is presented in this article. This method designs a multi-step reward and penalty method to alleviate the sparse reward problem using positive and negative reward experience replay buffer. The proposed method is validated in a simulation environment with different traffic flow and market penetration under the mixed traffic conditions of automated vehicles and human-driving vehicles. The results show that compared with traditional signal control methods, the proposed method can effectively improve the convergence and stability of the algorithm, reduce the number of collisions, and reduce the average travel time under different traffic conditions.