基于服务水平可靠性的连续交通网络设计模型与算法

传统路网设计很少同时考虑交通供需的随机性和服务水平可靠性对交通运行效率的影响,难以获得鲁棒性好、可靠度高的路网设计方案。针对此缺陷,假定路网中的交通需求服从对数正态分布,通过双层规划理论构建了考虑需求随机性及路网可靠性的连续均衡交通网络设计模型;其中上层规划是在满足投资预算的约束条件下使得系统期望的总阻抗最小,下层规划通过用户均衡交通分配模型来刻画出行者的路径选择行为。根据模型特点,设计了一种带罚函数的、基于蒙特卡洛仿真的多种群遗传求解算法;并用算例验证模型和算法的有效性。结果表明该模型能较好地解决交通供需的随机性和服务水平可靠性对交通运行效率的要求。

Continuous Road Network Design Model and Algorithm Based on Reliability of Service Level

Traditional network design seldom simultaneously taken the randomness of traffic demand and supply and the impact of reliability of service level for traffic operation efficiency into account, it is difficult to obtain highly robust and reliable network design. In view of the defect, assumed that the traffic demand follows a log-normal distribution, a continuous equilibrium traffic network design model with stochastic demand and road network reliability is constructed by using the bi-level programming. The upper level programming is to minimize the expected total system travel times meeting the constraints of the investment budget constraints, while the lower model is to determine the traveler"s route choice behavior through the traditional user equilibrium traffic assignment model. According to the characteristics of the model, a Monte Carlo simulation-based multiple population genetic algorithm with penalty function is provided to solve the proposed model and some numerical studies on a small test network are carried out to demonstrate the validity of the model and algorithm.