Signal Time Optimization Model and Solution for Minimum Energy Consumption at Intersections
To address the problem of signal timing at signalized intersections, this study set the average energy consumption of all vehicles through an intersection as the optimization objective. Under the constraints of the saturation level per intersection approach, the movement of pedestrians passing through intersections and the signal timing range, a signal timing optimization model for signalized intersection is established. The signal cycle and green time length of each phase are taken as decision variables in solving the signal timing optimization model using the artificial bee colony algorithm for minimum vehicle energy consumption. Experimental analysis shows that the artificial bee colony algorithm can effectively solve the signal timing optimization model. The timing results of this model are more conducive to reducing the energy consumption of vehicles through signalized intersections compared with the results of other signal timing methods.
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Availability:
- Find a library where document is available. Order URL: http://worldcat.org/isbn/9780784482292
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Supplemental Notes:
- © 2019 American Society of Civil Engineers.
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Corporate Authors:
American Society of Civil Engineers
1801 Alexander Bell Drive
Reston, VA United States 20191-4400 -
Authors:
- Zhao, Hong-Xing
- He, Rui-Chun
- Yang, Liu-Meng
- Ma, Chang-Xi
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Conference:
- 19th COTA International Conference of Transportation Professionals
- Location: Nanjing , China
- Date: 2019-7-6 to 2019-7-8
- Publication Date: 2019-7
Language
- English
Media Info
- Media Type: Web
- Features: References;
- Monograph Title: CICTP 2019: Transportation in China—Connecting the World
Subject/Index Terms
- TRT Terms: Algorithms; Energy consumption; Optimization; Signalized intersections; Traffic signal timing
- Uncontrolled Terms: Bee colony optimization
- Subject Areas: Energy; Highways; Operations and Traffic Management;
Filing Info
- Accession Number: 01714476
- Record Type: Publication
- ISBN: 9780784482292
- Files: TRIS, ASCE
- Created Date: Aug 22 2019 4:41PM