Reliable Shortest Path Guidance in Stochastic Road Networks Using Convolution-Based Path Finding Algorithm
Most existing research on routing guidance only pays attention to the average value of path travel time, which fails to consider travel time variability (TTV) and travel time reliability preferences by different travelers. In this study, a convolution-based modified genetic algorithm (CMGA) is proposed to find the reliable shortest path in stochastic road networks. By accounting for traveler risk tolerance, the algorithm enables the provision of personalized routing guidance for individual travelers. To support online applications in a large-scale network, reasonable heuristic constraints are imposed to help reduce the computational workload and accelerate the convergence speed of the search process. Numerical case studies based on a grid network with random offsets are provided, and the results help verify that the algorithm has the potential to solve reliable shortest path searching problems in a large-scale network with desirable efficiency.
- Record URL:
-
Availability:
- Find a library where document is available. Order URL: http://worldcat.org/isbn/9780784481523
-
Supplemental Notes:
- © 2018 American Society of Civil Engineers.
-
Corporate Authors:
American Society of Civil Engineers
1801 Alexander Bell Drive
Reston, VA United States 20191-4400 -
Authors:
- Chen, Peng
- Tong, Rui
- Lu, Guangquan
- Wang, Yunpeng
-
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
- Features: References;
- Pagination: pp 1342-1351
- Monograph Title: CICTP 2018: Intelligence, Connectivity, and Mobility
Subject/Index Terms
- TRT Terms: Genetic algorithms; Highway travel; Route guidance; Shortest path algorithms; Stochastic processes; Travel time
- Subject Areas: Highways; Planning and Forecasting;
Filing Info
- Accession Number: 01868284
- Record Type: Publication
- ISBN: 9780784481523
- Files: TRIS, ASCE
- Created Date: Dec 23 2022 10:04AM