Paper Info
Title
A Strategy To Alleviate Rush Hour Traffics In Urban Areas Based On School-Trip Commute Information
Abstract
As one of the main social issues in the 21st century, urban traffic congestion has become a severe challenge, especially during rush hours. Investigation indicates relationships between school-trip commutes, i.e., students' trips to and from school, and traffic congestion. Therefore, optimizing traffic in terms of the school-trip commute is considered as an important practice of smart cities. This article proposes a long-coding adapted genetic algorithm for large-scale school district replanning. Moreover, the fitness function takes into account both the congestion coefficient model and the grayscale difference model, which can reduce the traffic congestion as well as balance the traffic load on school-trip routes. Based on the above results, the school-trip route optimization is formulated as the school bus routing problem (SBRP) and the split demand school bus routing problem (SDSBRP). A max-min ant system with a pheromone smoothing mechanism is proposed for the SBRP and the SDSBRP. Considering the large scale of the problem, a high-compactness K-means algorithm is proposed to determine bus stops before school bus routing. Besides, a public bus allocation strategy is proposed to allocate a fleet of public buses to serve school-trip routes with low allocation costs. The proposed algorithms are tested on a realistic and challenging dataset from real world. Experimental research results show the advantage of our proposed strategies in reducing overall rush-hour traffic and optimizing school-trip routes.
Year
DOI
Venue
2021
10.1109/JSYST.2020.3021005
IEEE SYSTEMS JOURNAL
Keywords
DocType
Volume
Routing, Urban areas, Gray-scale, Planning, Load modeling, Clustering algorithms, Adaptation models, Heuristic algorithm, school-trip planning, traffic congestion, transportation system, vehicle routing problem (VRP)
Journal
15
Issue
ISSN
Citations 
2
1932-8184
0
PageRank 
References 
Authors
0.34
0
7
Name
Order
Citations
PageRank
Yuanyan Xie100.68
Yu Guo265.89
Tong Zhou344876.83
Zhenqiang Mi456.54
yang yang5476.29
Balqies Sadoun614221.32
Mohammad S. Obaidat72190315.70