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为了提供一种多原则指导下的交通流建模及求解方法,针对非两类极端条件下(用户最优、系统最优)的交通流分配问题展开研究,着重解决追求系统总体最优而忽视个体出行者承受多余开销导致的服从意愿较差的问题。引入距离和时间2种因素重新定义了车辆综合开销,从增强诱导信息影响效果的角度,将个人因服从诱导信息所新增的开销引入动态分配模型的约束条件中,以一种启发式的免回溯求解算法降低计算复杂度,并分析了近似比。研究结果表明:模型在以系统最优为主要目标的前提下可帮助出行者以较低的绕行开销避开拥堵,提高用户对诱导信息的遵从程度;在5类指标方面的表现显著优于DUO及最短路径模型;近似算法以接近线性的计算复杂度达到了DSO系统最优模型90%以上的效果。
In order to provide a traffic flow modeling and solution method under the guidance of multiple principles, aiming at the problem of traffic flow distribution under non-two kinds of extreme conditions (user optimal and system optimal), this paper focuses on solving the problem of pursuing the optimal and ignoring system Individual travelers are subject to the problem of poor compliance due to excessive expenses. The introduction of distance and time redefines the vehicle overhead by two factors. From the perspective of enhancing the effect of the induced information, the introduction of the new overhead of obedience to the information into the constraints of the dynamic allocation model to a heuristic The backtracking algorithm reduces the computational complexity and analyzes the approximate ratio. The results show that the model can help travelers to avoid congestion and improve the user’s compliance with induced information under the premise of system optimization as the main objective. The performance of the five types of indicators is significantly better than DUO and the shortest path model. The approximate algorithm achieves more than 90% of the optimal model of DSO with the computational complexity close to linear.