Li, Chao ORCID: https://orcid.org/0000-0003-1972-356X, Karimi, Mohammad and Alecsandru, Ciprian ORCID: https://orcid.org/0000-0001-7529-7660 (2018) Microscopic Simulation-Based High Occupancy Vehicle Lane Safety and Operation Assessment: A Case Study. Journal of Advanced Transportation, 2018 . pp. 1-12. ISSN 0197-6729
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Official URL: http://dx.doi.org/10.1155/2018/5262514
Abstract
This study proposes two general alternative designs to enhance the operation and safety of High Occupancy Vehicle (HOV) lanes at junctions with bus terminals or parking lots. A series of analysis tools, including microscopic simulation, video-based vehicle tracking technique, and Surrogate Safety Assessment Model (SSAM), are applied to model and test the safety and operational efficiency of an HOV road segment near a bus terminal in Québec as a case study. A metaheuristic optimization algorithm (i.e., Whale Optimization Algorithm) is employed to calibrate the microscopic model while deviation from the observed headway distribution is considered as a cost function. The results indicate that this type of HOV configurations exhibits significant safety problems (high number of crossing conflicts) and operational issues (high value of total delay) due to the terminal-bound buses that frequently need to travel across the main road. It is shown that the proposed alternative geometry design efficiently ameliorates the traffic conflicts issues. In addition, the alternative control design scheme significantly reduces the public transit delay. It is expected that this methodology can be applied to other reserved lane configurations similar to the investigated case study.
Divisions: | Concordia University > Gina Cody School of Engineering and Computer Science > Building, Civil and Environmental Engineering |
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Item Type: | Article |
Refereed: | Yes |
Authors: | Li, Chao and Karimi, Mohammad and Alecsandru, Ciprian |
Journal or Publication: | Journal of Advanced Transportation |
Date: | 2018 |
Funders: |
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Digital Object Identifier (DOI): | 10.1155/2018/5262514 |
ID Code: | 983718 |
Deposited By: | Danielle Dennie |
Deposited On: | 10 Apr 2018 20:23 |
Last Modified: | 10 Apr 2018 20:23 |
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