An Optimization Model of Short Lanes at Intersections Based on Vehicle Specific Power
To reduce delays and traffic emissions at intersections, the operating characteristics of intersections acquired by VISSIM, a method of calibrating emission factors during signal at intersection, is proposed on basis of VSP. Combined with operations research and traffic engineering theory, an optimization model of short lane length is established. The objectives of the model are to minimize vehicle delays and emissions. Considering pollutants of CO, HC, and NOx in car exhaust, simulation experiments are designed by VISSIM. Considering the vehicle data, the algorithms of calibrating the model parameters and solving the optimization models are programmed and calibrated by MATLAB. The results show the optimal length makes the average delay and traffic emissions decrease by 11% and 6.7%, respectively. The research can effectively decrease vehicle delays, reduce emissions at intersections, and provide a theory for intersection design and channelization optimization model connected with traffic emission.
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Availability:
- Find a library where document is available. Order URL: http://worldcat.org/isbn/9780784481523
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Supplemental Notes:
- © 2018 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:
- Hao, Yalan
- Chen, Hong
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Conference:
- 18th COTA International Conference of Transportation Professionals
- Location: Beijing , China
- Date: 2018-7-5 to 2018-7-8
- Publication Date: 2018-7
Language
- English
Media Info
- Media Type: Web
- Pagination: pp 2385-2394
- Monograph Title: CICTP 2018: Intelligence, Connectivity, and Mobility
Subject/Index Terms
- TRT Terms: Environmental protection; Intersections; Pollutants; Traffic delays; Traffic lanes
- Subject Areas: Environment; Highways; Operations and Traffic Management;
Filing Info
- Accession Number: 01871956
- Record Type: Publication
- ISBN: 9780784481523
- Files: TRIS, ASCE
- Created Date: Jan 27 2023 10:55AM