This paper studies a new form of transportation network design problem. In urban transportation network, unreasonable phenomenon can occur in certain traffic period （e.g. on/off duty period）, which demonstrates that...This paper studies a new form of transportation network design problem. In urban transportation network, unreasonable phenomenon can occur in certain traffic period （e.g. on/off duty period）, which demonstrates that the flows of opposite directions on a two-way road are seriously asymmetric; one traffic link of a two-way road congest heavily but the other is hardly used. In order to reduce transportation congestion and make full use of the existing road resources, we propose a lane reallocating approach in peak period, and establish a discrete hi-level programming model for the decision-making. Then, based on particle swarm optimization （PSO） technique, a heuristic solution algorithm for the hi-level model is designed. Finally, the lane reallocating approach is demonstrated through a simple transportation network.展开更多
基金This work was supported in part by National Natural Science Foundation of China under Grant Nos. 70631001, 70481088 and 7067.1008, and by Doctoral Station Grant No.（20050004005） of Ministry of Education, China.
文摘This paper studies a new form of transportation network design problem. In urban transportation network, unreasonable phenomenon can occur in certain traffic period （e.g. on/off duty period）, which demonstrates that the flows of opposite directions on a two-way road are seriously asymmetric; one traffic link of a two-way road congest heavily but the other is hardly used. In order to reduce transportation congestion and make full use of the existing road resources, we propose a lane reallocating approach in peak period, and establish a discrete hi-level programming model for the decision-making. Then, based on particle swarm optimization （PSO） technique, a heuristic solution algorithm for the hi-level model is designed. Finally, the lane reallocating approach is demonstrated through a simple transportation network.
