Affiliations: [a] School of Administration Business, Northeastern University, Shenyang, China
| [b] Institute of Behavioral and Service Operations Management, Northeastern University, Shenyang, China
| [c] Deparment of Mathematics, College of Sciences, Northeastern University, Shenyang, China
| [d] School of Business, Central South University, Changsha, China
| [e] Key Laboratory of Hunan Province for Mobile Business Intelligence, Hunan University of Commerce, Changsha, China
Correspondence:
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Corresponding author. Zhong-Zhong Jiang, School of Administration Business, and Institute of Behavioral and Service Operations Management, Northeastern University, Shenyang 110169, China. E-mail: zzjiang@mail.neu.edu.cn.
Abstract: Intelligent Transportation Systems (ITS) are defined as those systems utilizing synergistic technologies and systems engineering concepts to develop and improve transportation systems. In this paper, a novel route selection problem based on the envisaged driving mode with dynamic signals in ITS is proposed. It belongs to a kind of the shortest path problem of dynamic weight-varying networks, and the arc-weights of the network vary with the arc-chosen, so it cannot be solved by the existing greedy algorithms. According to the characteristics of the proposed problem, firstly, a dynamic programming model for the driving mode on a single path is established. Secondly, two algorithms for solving the route selection problem based on the former mode are developed. One is a brute-force algorithm based on matrix expansion with the computational complexity of O (Nt × n2). The other is an improved adaptive ant colony algorithm with the complexity of O (Nc × m × n2). Finally, the computational experiments show the advantages and disadvantages of the two effective algorithms with numerical examples.
