Connected Vehicle Based Traffic Signal Optimization
Connected vehicles (CVs) in smart cities, including vehicle to vehicle (V2V), vehicle to infrastructure (V2I), and vehicle to anything (V2X) communications, can provide more opportunities and impose more challenges for urban traffic signal control. This project aims to develop a framework, including modeling techniques, algorithms, and testing strategies, for urban traffic signal optimization with CVs. This framework is able to optimize traffic signal timing for a single intersection or along a corridor. More specifically, the major tasks of this project include: (1) Development of CV-based traffic signal timing optimization methods utilizing individual vehicles’ trajectories (i.e., second-by-second vehicle locations and speeds). This includes methods for timing plan optimization (of a single intersection) and coordination optimization among multiple intersections. The proposed method evaluates the total weighted sum of travel times and fuel consumption of all vehicles in the study area in the optimal green time and offset determination. (2) Propose solution methods for CV-based traffic signal optimization, which includes dynamic programming (DP) with two-step method for intersection level optimization (phase duration optimization) and a prediction-based solution method for the two-level problem (offset optimization) under corridor level optimization. (3) Comprehensive testing and validation of the proposed methods in traffic simulation. Various combinations of travel demands and types of CVs are tested for the proposed signal timing optimization methods. The testing tasks should validate that the developed methods are computationally manageable and have the potential to be implemented in CV-based traffic signal applications in the real world.
- Record URL:
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Supplemental Notes:
- This document was sponsored by the U.S. Department of Transportation, University Transportation Centers Program.
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Corporate Authors:
University of Washington
,Connected Cities for Smart Mobility towards Accessible and Resilient Transportation Center (C2SMART)
New York University
Tandon School of Engineering
Brooklyn, NY United StatesOffice of the Assistant Secretary for Research and Technology
University Transportation Centers Program
Department of Transportation
Washington, DC United States 20590 -
Authors:
- Ban, Xuegang (Jeff)
- 0000-0003-3605-971X
- Li, Wan
- Publication Date: 2018-4
Language
- English
Media Info
- Media Type: Digital/other
- Features: Figures; References; Tables;
- Pagination: 54p
Subject/Index Terms
- TRT Terms: Algorithms; Connected vehicles; Optimization; Test procedures; Traffic signal control systems; Traffic signal timing; Traffic simulation; Travel demand; Urban areas; Validation; Vehicle trajectories
- Subject Areas: Highways; Operations and Traffic Management; Planning and Forecasting; Vehicles and Equipment;
Filing Info
- Accession Number: 01677559
- Record Type: Publication
- Files: UTC, TRIS, ATRI, USDOT
- Created Date: Aug 8 2018 5:09PM