基于均衡流量的城市停车费用优化模型

Optimization model of urban parking fare based on equilibrium flow

基于随机用户平衡原则,分析了出行者的路径选择和停车选择行为,建立了满足Logit关系的城市道路停车流量分配模型。基于收益管理思想,以停车收益最大为决策目标,建立了城市停车费用的双层规划模型,并以7个节点和2个停车场的小型网络进行实例验证。分析结果表明:当停车需求为10 000pcu·h-1时,随着停车场2停车费用的提高,停车流量不断向停车场1转移,停车场1在停车费用不变的情况下收益不断增加,当停车场2的停车费用为4元·h-1时,总的停车收益达到最大;当停车需求为20 000pcu·h-1时,随着停车费用的上升,总的停车收益将持续增加;2个停车场之间存在博弈关系,停车费用存在纳什均衡点,当停车需求为10 000pcu·h-1时,2个停车场的最优停车费用均为5元·h-1;当停车需求为20 000pcu·h-1时,2个停车场的最优停车费用均为最高限价10元·h-1。

Based on stochastic user equilibrium principle, the route choice and parking choice behaviors of travelers were analyzed, and the urban road parking assignment model meeting the logit relation was set up. Based on the revenue management ideology, the maximum parking revenue was taken as decision target, the bi-level programming model of urban parking fare was set up, and the example verification was carried out by using a small-size network with 7 nodes and 2 parking plots. Analysis result shows that when parking demand is 10 000 pcu · h^-1, the parking flow will continue to shift from parking plot 2 to parking plot 1 with the increase of parking fare of plot 2, the parking revenue of parking plot 1 increases unceasing though its fare has no change. The total parking revenue reaches the maximum value when the parking fare of plot 2 is 4 yuan · h^-1. When parking demand is 20 000 pcu · h^-1 , the total parking revenue will continue to increase with the increase of parking fare. On the other hand, the game relation exists between the two parking plots and there is a Nash equilibrium point. In the case of 10 000 pcu · h^-1 , the optimal fare is 5 yuan· h^-1 for the two parking plots, while the optimal fare is ceiling price 10 yuan · h^-1 in the ease of 20 000 pcu · h^-1. 4 tabs, 11 figs, 21 refs.