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Title: Connected Vehicle-Enabled Proactive Signal Control for Congestion Mitigation on Arterial Corridors
Accession Number: 01660500
Record Type: Component
Abstract: Traffic congestion results in increasing delay in daily commutes and unreliable transportation services. Traffic signal control on arterial corridors attracts strong research and implementation attention due to its advancement on direct traffic management and coordination for congestion mitigation. With increasing penetration rates of connected vehicles, signals are able to interact with real-time traffic conditions and to be operated more proactively with traffic prediction models to mitigate road congestions, to improve road capacities, and to enhance transportation network efficiency. This paper develops a proactive signal control system based on connected vehicles to minimize vehicle delay at signalized intersections. The system utilizes connected vehicles to make a short-term prediction about the overall vehicle delays at different movements accurately. The optimal signal phasing and timing plan is estimated to minimize the total vehicle delay at the intersection. Two road segments with one isolated intersection and three consecutive intersections are simulated with the INTEGRATION microscopic traffic simulator to validate the proposed system. The result obtained under the proactive control system is compared to a well-tuned fully actuated control. Applying the proactive control system, the total vehicle delay can be reduced by up to 59%, the vehicle stops by 40%, and the fuel consumption by 18%.
Supplemental Notes: This paper was sponsored by TRB committee AHB25 Standing Committee on Traffic Signal Systems.
Report/Paper Numbers: 18-03520
Language: English
Authors: Yang, HaoHaque, MmWu, XingPagination: 23p
Publication Date: 2018
Conference:
Transportation Research Board 97th Annual Meeting
Location:
Washington DC, United States Media Type: Digital/other
Features: Figures; Maps; References; Tables
TRT Terms: Subject Areas: Highways; Operations and Traffic Management
Source Data: Transportation Research Board Annual Meeting 2018 Paper #18-03520
Files: TRIS, TRB, ATRI
Created Date: Jan 8 2018 10:52AM
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