Lane Management with Variable Lane Width and Model Calibration for Connected Automated Vehicles
Connected autonomous vehicles (CAVs) may be able to operate with less longitudinal and lateral spacing than traditional human-driven vehicles (HVs) due to fast and precise control technologies and cooperative maneuvers. With this appealing feature, it is possible to allocate specific narrower highway lanes to CAVs to increase traffic throughput. This paper proposes an analytical lane management framework that determines the optimal number of CAV lanes needed for a highway segment to maximize its throughput considering the narrowed width of CAV lanes. The proposed optimization model investigates three types of vehicles, including CAVs and human-driven light-duty and human-driven heavy-duty vehicles. It takes into account varying mixed-traffic demand levels, CAV market penetration rates, platooning intensities, and CAV technology scenarios. The results from the numerical experiments reveal that the proposed lane management framework with the narrowed CAV lane width increases highway throughput for various parameter settings in different CAV technology scenarios. In order to bring the developed lane management model to the implementation stage, this paper proposes an analytical methodology on how to estimate model parameters (e.g., CAV market penetration rate, platooning intensity, and average headway) with mixed-traffic trajectories when they become available in the near future. The authors illustrate the application of the developed calibration method with synthetic mixed-traffic data adapted from a data set.
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Availability:
- Find a library where document is available. Order URL: http://worldcat.org/issn/24732907
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Supplemental Notes:
- © 2019 American Society of Civil Engineers.
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Authors:
- Ghiasi, Amir
- Hussain, Omar
- Qian, Zhen "Sean"
- Li, Xiaopeng "Shaw"
- Publication Date: 2020-3
Language
- English
Media Info
- Media Type: Web
- Features: References;
- Pagination: 04019075
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Serial:
- Journal of Transportation Engineering, Part A: Systems
- Volume: 146
- Issue Number: 3
- Publisher: American Society of Civil Engineers
- ISSN: 2473-2907
- EISSN: 2473-2893
- Serial URL: http://ascelibrary.org/journal/jtepbs
Subject/Index Terms
- TRT Terms: Autonomous vehicles; Calibration; Connected vehicles; Intelligent vehicles; Managed lanes; Optimization; Traffic models; Traffic volume; Vehicle mix
- Subject Areas: Data and Information Technology; Highways; Operations and Traffic Management; Vehicles and Equipment;
Filing Info
- Accession Number: 01728787
- Record Type: Publication
- Files: TRIS, ASCE
- Created Date: Jan 28 2020 9:47AM