Relevant bibliographies by topics / Travel time (Traffic engineering) Simulation

Academic literature on the topic 'Travel time (Traffic engineering) Simulation'

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Published: 10 December 2022
Last updated: 29 January 2023

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Journal articles on the topic "Travel time (Traffic engineering) Simulation"

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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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Dissertations / Theses on the topic "Travel time (Traffic engineering) Simulation"

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Lu, Chenxi. "Improving Analytical Travel Time Estimation for Transportation Planning Models." FIU Digital Commons, 2010. http://digitalcommons.fiu.edu/etd/237.

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This dissertation aimed to improve travel time estimation for the purpose of transportation planning by developing a travel time estimation method that incorporates the effects of signal timing plans, which were difficult to consider in planning models. For this purpose, an analytical model has been developed. The model parameters were calibrated based on data from CORSIM microscopic simulation, with signal timing plans optimized using the TRANSYT-7F software. Independent variables in the model are link length, free-flow speed, and traffic volumes from the competing turning movements. The developed model has three advantages compared to traditional link-based or node-based models. First, the model considers the influence of signal timing plans for a variety of traffic volume combinations without requiring signal timing information as input. Second, the model describes the non-uniform spatial distribution of delay along a link, this being able to estimate the impacts of queues at different upstream locations of an intersection and attribute delays to a subject link and upstream link. Third, the model shows promise of improving the accuracy of travel time prediction. The mean absolute percentage error (MAPE) of the model is 13% for a set of field data from Minnesota Department of Transportation (MDOT); this is close to the MAPE of uniform delay in the HCM 2000 method (11%). The HCM is the industrial accepted analytical model in the existing literature, but it requires signal timing information as input for calculating delays. The developed model also outperforms the HCM 2000 method for a set of Miami-Dade County data that represent congested traffic conditions, with a MAPE of 29%, compared to 31% of the HCM 2000 method. The advantages of the proposed model make it feasible for application to a large network without the burden of signal timing input, while improving the accuracy of travel time estimation. An assignment model with the developed travel time estimation method has been implemented in a South Florida planning model, which improved assignment results.
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Henclewood, Dwayne Anthony. "Real-time estimation of arterial performance measures using a data-driven microscopic traffic simulation technique." Diss., Georgia Institute of Technology, 2012. http://hdl.handle.net/1853/44792.

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Traffic congestion is a one hundred billion dollar problem in the US. The cost of congestion has been trending upward over the last few decades, but has experienced slight decreases in recent years partly due to the impact of congestion reduction strategies. The impact of these strategies is however largely experienced on freeways and not arterials. This discrepancy in impact is partially linked to the lack of real-time, arterial traffic information. Toward this end, this research effort seeks to address the lack of arterial traffic information. To address this dearth of information, this effort developed a methodology to provide accurate estimates of arterial performance measures to transportation facility managers and travelers in real-time. This methodology employs transmitted point sensor data to drive an online, microscopic traffic simulation model. The feasibility of this methodology was examined through a series of experiments that were built upon the successes of the previous, while addressing the necessary limitations. The results from each experiment were encouraging. They successfully demonstrated the method's likely feasibility, and the accuracy with which field estimates of performance measures may be obtained. In addition, the method's results support the viability of a "real-world" implementation of the method. An advanced calibration process was also developed as a means of improving the method's accuracy. This process will in turn serve to inform future calibration efforts as the need for more robust and accurate traffic simulation models are needed. The success of this method provides a template for real-time traffic simulation modeling which is capable of adequately addressing the lack of available arterial traffic information. In providing such information, it is hoped that transportation facility managers and travelers will make more informed decisions regarding more efficient management and usage of the nation's transportation network.
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Hodges, Fiona. "Travel time budgets in an urban area /." Connect to thesis, 1994. http://eprints.unimelb.edu.au/archive/00000227.

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Chan, Ping-ching Winnie. "The value of travel time savings in Hong Kong." Hong Kong : University of Hong Kong, 2000. http://sunzi.lib.hku.hk:8888/cgi-bin/hkuto%5Ftoc%5Fpdf?B23425003.

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Wu, Seung Kook. "Adaptive traffic control effect on arterial travel time charateristics." Diss., Atlanta, Ga. : Georgia Institute of Technology, 2009. http://hdl.handle.net/1853/31839.

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Thesis (Ph.D)--Civil and Environmental Engineering, Georgia Institute of Technology, 2010.
Committee Chair: Hunter, Michael; Committee Member: Guensler, Randall; Committee Member: Leonard, John; Committee Member: Rodgers, Michael; Committee Member: Roshan J. Vengazhiyil. Part of the SMARTech Electronic Thesis and Dissertation Collection.
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Misra, Rajul. "Toward a comprehensive representation and analysis framework for non-worker activity-travel pattern modeling /." Digital version accessible at:, 1999. http://wwwlib.umi.com/cr/utexas/main.

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Li, Lok-man Jennifer. "Schedule delay of work trips in Hong Kong an empirical analysis /." Click to view the E-thesis via HKUTO, 2008. http://sunzi.lib.hku.hk/hkuto/record/B40988041.

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Choy, Wing-pong. "A review of the value of travel time in Hong Kong." Click to view the E-thesis via HKUTO, 2005. http://sunzi.lib.hku.hk/hkuto/record/B31937068.

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Chan, Ping-ching Winnie, and 陳冰淸. "The value of travel time savings in Hong Kong." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2000. http://hub.hku.hk/bib/B31954789.

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Adams, David Lewis. "Integrating travel time reliability into management of highways." Access to citation, abstract and download form provided by ProQuest Information and Learning Company; downloadable PDF file, 52 p, 2008. http://proquest.umi.com/pqdweb?did=1459913561&sid=3&Fmt=2&clientId=8331&RQT=309&VName=PQD.

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Books on the topic "Travel time (Traffic engineering) Simulation"

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Rakha, Hesham. Transit signal priority project, phase II: Field and simulation evaluation results. Charlottesville, Va: Virginia Transportation Research Council, 2006.

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Kittelson & Associates. Evaluating alternative operations strategies to improve travel time reliability. Washington, D.C: Transportation Research Board, 2013.

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Second Strategic Highway Research Program (U.S.), Kimley-Horn and Associates, and Parsons Brinckerhoff, eds. Integrating business processes to improve travel time reliability. Washington, D.C: Transportation Research Board, 2011.

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Second Strategic Highway Research Program (U.S.), Kimley-Horn and Associates, and Parsons Brinckerhoff, eds. Guide to integrating business processes to improve travel time reliability. Washington, D.C: Transportation Research Board, 2011.

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Small, Kenneth A. Valuation of travel-time savings and predictability in congested conditions for highway user-cost estimation. Washington, D.C: National Academy Press, 1999.

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United States. Federal Highway Administration., ed. Analysis of national and regional travel trends. Washington, D.C: Dept. of Transportation, Federal Highway Administration, 1986.

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Hyŏn, Pak. Yebi tʻadangsŏng chosa chaengchŏm yŏnʼgu. Sŏul Tʻŭkpyŏlsi: Hanʼguk Kaebal Yŏnʼguwŏn, 2006.

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Arnold, E. D. Changes in travel in the Shirley Highway corridor, 1983-1986. Charlottesville, Va: Virginia Transportation Research Council, in cooperation with the U.S. Dept. of Transportation, Federal Highway Administration, 1987.

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Kralich, Susana. Accesibilidad hogar-trabajo en el Gran Buenos Aires: Un estudio de caso en el partido de La Matanza. Buenos Aires: Instituto de Geografía, Universidad de Buenos Aires, Facultad de Filosofia y Letras, 1993.

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North, American Travel Monitoring Exhibition and Conference (2000 Middleton Wis ). North American Travel Monitoring Exhibition and Conference, TRB Data Committee's mid-year meetings, August 27-31, 2000, Middleton, WI. Madison, Wis: Wisconsin Dept. of Transportation, 2000.

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Book chapters on the topic "Travel time (Traffic engineering) Simulation"

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Amrutsamanvar, Rushikesh, Gaurang Joshi, Shriniwas S. Arkatkar, and Ravi Sekhar Chalumuri. "Empirical Travel Time Reliability Assessment of Indian Urban Roads." In Recent Advances in Traffic Engineering, 165–82. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-3742-4_11.

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Prajapati, N. I., A. K. Sutariya, and H. R. Varia. "Travel Time Delay Study on Congested Urban Road Links of Ahmedabad City." In Recent Advances in Traffic Engineering, 121–37. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-3742-4_8.

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Nguyen, Tuan Nam, and Gerhard Reinelt. "On Travel Time Functions for Mixed Traffic Systems Dominated by Motorcycles." In Modeling, Simulation and Optimization of Complex Processes HPSC 2015, 139–50. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-67168-0_12.

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Saw, Krishna, Bhimaji K. Katti, and Gaurang J. Joshi. "Fuzzy Rule-Based Travel Time Estimation Modelling: A Case Study of Surat City Traffic Corridor." In Recent Advances in Traffic Engineering, 183–98. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-3742-4_12.

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Sen, Saptarshi, and Sudip Kumar Roy. "Quantifying Travel Time Reliability of Air-Conditioned Public Buses in Urban Area: A Case Study of Kolkata." In Recent Advances in Traffic Engineering, 403–20. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-3742-4_25.

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Park, Chulsun, Juho Lee, Tianye Tan, and Sungkown Park. "Simulation of Scheduled Traffic for the IEEE 802.1 Time Sensitive Networking." In Lecture Notes in Electrical Engineering, 75–83. Singapore: Springer Singapore, 2016. http://dx.doi.org/10.1007/978-981-10-0557-2_8.

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Deb Nath, Rudra Pratap, Hyun-Jo Lee, Nihad Karim Chowdhury, and Jae-Woo Chang. "Modified K-Means Clustering for Travel Time Prediction Based on Historical Traffic Data." In Knowledge-Based and Intelligent Information and Engineering Systems, 511–21. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-15387-7_55.

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Ganapathy, Jayanthi, and Fausto Pedro García Márquez. "Travel Time Based Traffic Rerouting by Augmenting Traffic Flow Network with Temporal and Spatial Relations for Congestion Management." In Proceedings of the Fifteenth International Conference on Management Science and Engineering Management, 554–65. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-79203-9_43.

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Lawniczak, Anna T., and Bruno N. Di Stefano. "Development of Road Traffic CA Model of 4-Way Intersection to Study Travel Time." In Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, 2040–49. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-02469-6_80.

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Halyal, Shivaraj, Raviraj H. Mulangi, M. M. Harsha, and Himanshu Laddha. "Study on Travel Time Characteristics of Hubli-Dharwad Bus Rapid Transit System in Comparison with Heterogeneous Traffic Lane." In Recent Advancements in Civil Engineering, 701–12. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-4396-5_61.

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Conference papers on the topic "Travel time (Traffic engineering) Simulation"

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Solomon, J. H., P. Gonzalez-Mohino, F. Amirouche, and D. Zavattero. "Feasibility Analysis and Computer Simulation of an Automated Bus Route." In ASME 2002 International Mechanical Engineering Congress and Exposition. ASMEDC, 2002. http://dx.doi.org/10.1115/imece2002-33186.

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Traffic congestion in major cities is a major problem which is growing steadily every year. It is clear that something must be done to curb this trend. Several different concepts are being investigated which can be used to minimize congestion and improve the traffic flow. Automation of the bus system represents one of those methods, and is the focus of this paper. Currently, public opinion of the quality of bus services is generally not perceived as adequate. Buses generally travel about 60% of the speed of other vehicles, and more often than not adherence to schedule is difficult to achieve. The consequence is that people choose to take personal transportation instead, causing increased congestion. Automation seeks to address this issue by offering decreased travel times, increased schedule adherence, and greater overall convenience compared to the current bus systems. The concept of automation is based on expanding upon the ideas of Bus Rapid Transit (BRT) and making the system as efficient as possible.
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Torres-Cruz, Alberto, Dirk F. de Lange, and Hugo I. Medellín-Castillo. "Development of a Virtual Platform to Evaluate the Performance of an Electrical Vehicle." In ASME 2015 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2015. http://dx.doi.org/10.1115/imece2015-52408.

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Virtual simulations of electrical vehicle performance help to optimize vehicle design, by studying and predicting the effects of parameter variations on the vehicle performance, in order to find an optimum balance between the cost and benefit of design decisions. In this work, the development of a virtual platform to evaluate the performance of an electrical vehicle is presented and applied to the study of public urban transportation. The aim is to analyze the requirements and optimize specifications for a light weight, energy efficient, autonomous vehicle without energy supply along the trajectory, except in the stations. Virtual platforms for vehicle performance have been developed before, and in many cases characteristic velocity profiles are used as a reference, according to the traffic environment in which the vehicle will operate. Vehicle analysis and design is focused on feasibility of the vehicle to be able to follow the prescribed velocity profile. In the present study, the evaluation is instead based on the cost/benefit relationship for an urban transport vehicle on traffic-free trajectories, enabling to adjust and optimize the velocity profiles in order to optimize the energy use while minimizing travel time. Therefore, the virtual platform is focused on the calculation of the net energy usage, the travel time and the system cost corresponding to an electrical vehicle with different battery and ultra-capacitor energy storage capacities, regeneration and storage of brake energy and an automatic governor for autonomous vehicle control. The influence of design parameters, such as the installed motor power, energy storage capacity, vehicle weight, passenger load and vehicle control strategy on the time schedule and energy efficiency is studied. However, the effort does not aim for a straight forward optimization of efficiency or minimization of travel time. In fact, energy optimization often conflicts with the travel time optimization. Therefore, both are analyzed simultaneously in order to assist in the search for an optimum compromise. In addition, the results are interpreted in terms of the overall obtained benefits of travel time reduction or optimization of the energy use, in contrast with the corresponding increment of the investment cost of the vehicle related to the implementation of the studied parameter variation. Specific trajectory profiles, including height profiles can be defined for optimization of the vehicle system for application in specific locations with specific geographic conditions.
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Tang, S., P. Tse, and X. Wang. "The Revelation of Propagating Ultrasonic Guided Waves Through Simulation When They Encountered Defects in a Pipe." In ASME 2009 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2009. http://dx.doi.org/10.1115/detc2009-86380.

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In Hong Kong, there are many gas and water pipelines buried under buildings and roads. A rupture of the water or gas pipeline may cause serious interruption to traffic and even human casualties. Therefore, a single-point based and easy-to-install pipeline inspection system is essential to Hong Kong daily living and crucial to public safety. One of the effective and convenient inspection methods for underground pipeline inspection is the ultrasonic-based guided waves. The success in pipe inspection relies on the emission of proper mode of guided waves to a particular type of pipe. To derive the necessary parameters in helping the selection of optimal mode of waves, one can use simulation or real experiments. The cost and difficulty in conducting live experiments on roads are too high, especially in a dense living area like Hong Kong. Hence, simulation is preferred to minimize the frequency and number of experiments necessary to be conducted. A finite element method (FEM) tool, called ANSYS, was selected to build the required dynamical models. However, several obstacles must be solved prior to the development of 3D models for pipes suffering from various defects. These obstacles include the complexity in simulating high frequency guided waves when they are propagating inside a pipeline, the requirements of huge memory space and intensive computational resources. In this paper, we present detailed descriptions on solving these obstacles. The methods to determine the optimal element size and time step are also reported so that the best trade-off can be achieved in terms of efficiency and computational intensity. To verify the accuracy in simulations, selected experiments were conducted for verification purpose. The results show good agreement between the results of simulations and experiments.
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Hu, Ta-Yin, and Wei-Ming Ho. "Simulation-based travel time prediction model for traffic corridors." In 2009 12th International IEEE Conference on Intelligent Transportation Systems (ITSC). IEEE, 2009. http://dx.doi.org/10.1109/itsc.2009.5309719.

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Ming-Chorng Hwang and Hsun-Jung Cho. "Numerical Simulation of Link Travel Time with Hyperbolic Traffic Behavior." In 2006 IEEE Intelligent Transportation Systems Conference. IEEE, 2006. http://dx.doi.org/10.1109/itsc.2006.1706774.

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Tang, Xiaoyong, Lin Cheng, and Shang Xu. "Consideration of Travel Time Reliability in Traffic Assignment." In Second International Conference on Transportation Engineering. Reston, VA: American Society of Civil Engineers, 2009. http://dx.doi.org/10.1061/41039(345)667.

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Xu, Tiandong, Yuan Hao, and Lijun Sun. "Travel Time Prediction of Urban Expressway in Unstable Traffic Flow." In First International Conference on Transportation Engineering. Reston, VA: American Society of Civil Engineers, 2007. http://dx.doi.org/10.1061/40932(246)361.

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Li, Fazhi, Lei Xiao, and Ke Wang. "Studying Delivery Travel Time Reliability Based on Traffic Flow Fluctuations." In International Conference of Logistics Engineering and Management (ICLEM) 2010. Reston, VA: American Society of Civil Engineers, 2010. http://dx.doi.org/10.1061/41139(387)185.

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Huo, Shuhao, Liangyao Yu, Liangxu Ma, and Lei Zhang. "Ride Comfort Improvement in Post-Braking Phase Using Active Suspension." In ASME 2015 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2015. http://dx.doi.org/10.1115/detc2015-46878.

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Frequent acceleration and deceleration of vehicle especially in urban traffic arouse relative frequent pitch motion accordingly. As the orientation of vehicle acceleration alters, the inertia of human body and the pitch motion transferred by the suspension cause passengers’ body to swing back and forth, thus leading to ride discomfort, even motion sickness. In particular, such ride discomfort is noticeable in the post-braking phase, resulting from the subsequent rebound of the vehicle body after complete stop, according to the subjective experiment in this paper. The suspension characteristics are dominant in the pitch motion of post-braking phase. This paper applies an active suspension based on LQR controller to attenuate the negative rebound effect. Considering the trade-off between rebound time and rebound impact, a LQR optimal controller is proposed to control the active suspension, minimizing the negative pitch motion and improving the braking ride comfort. The simulation result indicates that the vehicle rebound in the post-braking phase is conspicuous around the resonant frequency of the vehicle body. Furthermore, the magnitude of frequency response at this critical area has been decreased and the ride comfort in post-braking phase has been improved with the proposed LQR controller.
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Ding, Hailong, Dalin Xu, Sen Xu, Manwei Chang, and Xinkuan Liu. "Bus travel time prediction based on time-varying adaptive Kalman filter method." In International Conference on Frontiers of Traffic and Transportation Engineering (FTTE 2022), edited by Changxi Ma. SPIE, 2022. http://dx.doi.org/10.1117/12.2652414.

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Reports on the topic "Travel time (Traffic engineering) Simulation"

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Arhin, Stephen, Babin Manandhar, Kevin Obike, and Melissa Anderson. Impact of Dedicated Bus Lanes on Intersection Operations and Travel Time Model Development. Mineta Transportation Institute, June 2022. http://dx.doi.org/10.31979/mti.2022.2040.

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Over the years, public transit agencies have been trying to improve their operations by continuously evaluating best practices to better serve patrons. Washington Metropolitan Area Transit Authority (WMATA) oversees the transit bus operations in the Washington Metropolitan Area (District of Columbia, some parts of Maryland and Virginia). One practice attempted by WMATA to improve bus travel time and transit reliability has been the implementation of designated bus lanes (DBLs). The District Department of Transportation (DDOT) implemented a bus priority program on selected corridors in the District of Columbia leading to the installation of red-painted DBLs on corridors of H Street, NW, and I Street, NW. This study evaluates the impacts on the performance of transit buses along with the general traffic performance at intersections on corridors with DBLs installed in Washington, DC by using a “before” and “after” approach. The team utilized non-intrusive video data to perform vehicular turning movement counts to assess the traffic flow and delays (measures of effectiveness) with a traffic simulation software. Furthermore, the team analyzed the Automatic Vehicle Locator (AVL) data provided by WMATA for buses operating on the study segments to evaluate bus travel time. The statistical analysis showed that the vehicles traveling on H Street and I Street (NW) experienced significantly lower delays during both AM (7:00–9:30 AM) and PM (4:00–6:30 PM) peak hours after the installation of bus lanes. The approximation error metrics (normalized squared errors) for the testing dataset was 0.97, indicating that the model was predicting bus travel times based on unknown data with great accuracy. WMATA can apply this research to other segments with busy bus schedules and multiple routes to evaluate the need for DBLs. Neural network models can also be used to approximate bus travel times on segments by simulating scenarios with DBLs to obtain accurate bus travel times. Such implementation could not only improve WMATA’s bus service and reliability but also alleviate general traffic delays.
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Kodupuganti, Swapneel R., Sonu Mathew, and Srinivas S. Pulugurtha. Modeling Operational Performance of Urban Roads with Heterogeneous Traffic Conditions. Mineta Transportation Institute, January 2021. http://dx.doi.org/10.31979/mti.2021.1802.

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The rapid growth in population and related demand for travel during the past few decades has had a catalytic effect on traffic congestion, air quality, and safety in many urban areas. Transportation managers and planners have planned for new facilities to cater to the needs of users of alternative modes of transportation (e.g., public transportation, walking, and bicycling) over the next decade. However, there are no widely accepted methods, nor there is enough evidence to justify whether such plans are instrumental in improving mobility of the transportation system. Therefore, this project researches the operational performance of urban roads with heterogeneous traffic conditions to improve the mobility and reliability of people and goods. A 4-mile stretch of the Blue Line light rail transit (LRT) extension, which connects Old Concord Rd and the University of North Carolina at Charlotte’s main campus on N Tryon St in Charlotte, North Carolina, was considered for travel time reliability analysis. The influence of crosswalks, sidewalks, trails, greenways, on-street bicycle lanes, bus/LRT routes and stops/stations, and street network characteristics on travel time reliability were comprehensively considered from a multimodal perspective. Likewise, a 2.5-mile-long section of the Blue Line LRT extension, which connects University City Blvd and Mallard Creek Church Rd on N Tryon St in Charlotte, North Carolina, was considered for simulation-based operational analysis. Vissim traffic simulation software was used to compute and compare delay, queue length, and maximum queue length at nine intersections to evaluate the influence of vehicles, LRT, pedestrians, and bicyclists, individually and/or combined. The statistical significance of variations in travel time reliability were particularly less in the case of links on N Tryon St with the Blue Line LRT extension. However, a decrease in travel time reliability on some links was observed on the parallel route (I-85) and cross-streets. While a decrease in vehicle delay on northbound and southbound approaches of N Tryon St was observed in most cases after the LRT is in operation, the cross-streets of N Tryon St incurred a relatively higher increase in delay after the LRT is in operation. The current pedestrian and bicycling activity levels seemed insignificant to have an influence on vehicle delay at intersections. The methodological approaches from this research can be used to assess the performance of a transportation facility and identify remedial solutions from a multimodal perspective.
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