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应用交通网络平衡模型和边际成本收费理论相结合的方法,研究了运行时间可靠度下的随机系统最优拥挤收费问题,建立了运行时间可靠度及内生ATIS市场渗透率条件下随机系统最优交通拥挤收费模型.分析了基于运行时间可靠度下的随机系统最优拥挤收费对用户出行行为的影响.发现了与确定性网络用户平衡流中的情形类似,对于考虑运行时间可靠度下的随机交通网络,边际成本收费理论仍然适用,即采用边际社会成本流函数代替单位路段成本流函数,可以使随机网络随机用户平衡流变为随机网络随机系统最优流.算例分析结果表明:在传统的拥挤收费模型中,拥挤收费仅与路径(路段)运行时间和路径(路段)流量有关.现实中,在确定他们的出行路线时,用户往往还会考虑网络运行时间可靠度因素,而不仅仅是路径运行时间或成本.用户对于运行时间可靠度的置信度要求越高,传统的拥挤收费执行效果越不理想.因此,现实生活中传统的拥挤收费不一定能使网络效益达到最优或缓解交通拥挤.
By using the method of traffic network equilibrium model and marginal cost charging theory, the optimal crowding charging problem of stochastic system under operating reliability is studied. The optimal stochastic system optimality under operating time reliability and endogenous ATIS market penetration is established. Traffic congestion charging model.Analyzed the impact of optimal crowding charging based on runtime reliability on user travel behavior.It is found that similar to the situation in deterministic network user balance flow, Traffic network and marginal cost charging theory are still applicable, that is, the marginal cost of social function can be used to replace the cost function of unit road section, so that the stochastic user equilibrium in stochastic networks can be transformed into the optimal stochastic network stochastic system. Of congestion pricing models, congestion charges are related only to the path (link) runtime and path (link) traffic.Reality, in determining their travel routes, users often consider network runtime reliability factors, not just Is the path run time or cost The user’s confidence level for runtime reliability , The traditional effect of the implementation of congestion pricing is not satisfactory. Therefore, in real life traditional network congestion pricing does not necessarily make for optimal efficiency or ease traffic congestion.