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Improving Traffic State Prediction Model for Variable Speed Limit Control by Introducing Stochastic Supply and Demand
Joint Authors
Zhang, Can
Qiu, Tony Z.
Bie, Yuwei
Seraj, Mudasser
Source
Journal of Advanced Transportation
Issue
Vol. 2018, Issue 2018 (31 Dec. 2018), pp.1-12, 12 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2018-08-05
Country of Publication
Egypt
No. of Pages
12
Main Subjects
Abstract EN
Variable speed limit (VSL) is becoming recognized as an effective way to improve traffic throughput and road safety.
In particular, methods based on traffic state prediction exhibit promising potential to prevent future traffic congestion and collisions.
However, field observations indicate that the traffic state prediction model results in nonnegligible error that impacts the next step decision making of VSL.
Thus, this paper investigates how to eliminate this prediction error within a VSL environment.
In this study, the traffic state prediction model is a second-order traffic flow model named METANET, while the VSL control is model predictive control (MPC) based, and the VSL decision is discrete optimized choice.
A simplified version of the switching mode stochastic cell transmission model (SCTM) is integrated with the METANET model to eliminate the prediction error.
The performance of the proposed method is assessed using field data from a VSL pilot test in Edmonton, Canada, and is compared with the prediction results of the baseline METANET model during the road test.
The results show that during the most congested period the proposed SCTM-METANET model significantly improves the prediction accuracy of regular METANET model.
American Psychological Association (APA)
Bie, Yuwei& Seraj, Mudasser& Zhang, Can& Qiu, Tony Z.. 2018. Improving Traffic State Prediction Model for Variable Speed Limit Control by Introducing Stochastic Supply and Demand. Journal of Advanced Transportation،Vol. 2018, no. 2018, pp.1-12.
https://search.emarefa.net/detail/BIM-1181694
Modern Language Association (MLA)
Bie, Yuwei…[et al.]. Improving Traffic State Prediction Model for Variable Speed Limit Control by Introducing Stochastic Supply and Demand. Journal of Advanced Transportation No. 2018 (2018), pp.1-12.
https://search.emarefa.net/detail/BIM-1181694
American Medical Association (AMA)
Bie, Yuwei& Seraj, Mudasser& Zhang, Can& Qiu, Tony Z.. Improving Traffic State Prediction Model for Variable Speed Limit Control by Introducing Stochastic Supply and Demand. Journal of Advanced Transportation. 2018. Vol. 2018, no. 2018, pp.1-12.
https://search.emarefa.net/detail/BIM-1181694
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1181694