日变交通路径调整模型与算法研究

发布时间：2018-09-05 13:11

【摘要】：论文针对现有研究不足,借助行为动力学建模、数值模拟与数学优化理论等方法,从日变交通路径调整模型、调整算法与交通信息发布策略三个层面系统地展开研究。论文的主要创新工作总结如下： (1)通过指证经典比例调整过程的两个行为不足(即弱鲁棒性与过度调整问题),建立了基于对向行为准则的非线性对向调整动力学(NPSD)模型,然后以此为基础,进一步探讨了受多日出行经历影响、有限理性情形及最短路导向行为准则下的交通路径调整行为,分别建立了多日NPSD (MNPSD)模型、有限理性NPSD (BRNPSD)模型以及最短路导向的非线性调整动力学(NMSD)模型。研究发现：i)以上四种路径调整模型均能避免弱鲁棒性与过度调整问题,进而维持迭代解集不变,同时各自的稳定路径流模式与其对应的用户均衡等价；ii) NPSD与NMSD均为理性行为调整过程,并且二者的连续型模型是全局稳定的。数值结果表明：i)用户反应灵敏度对网络交通流演化过程与结果具有重要影响；ii)路径调整中过分依赖过往出行经验反而可能增加网络的不稳定风险；iii)有限理性下的网络演化稳定性并非总比完美理性强；iv) DNPSD的稳定性优于DNMSD,并且前者更适用于开发交通流均衡求解算法。 (2)通过引入风险倾向型路径旅行时间测度MBTT,并将其与风险规避型测度METT进行凸组合,构建了可描述各种风险态度的路径旅行时间测度CMTT,再将其纳入旅行时间可靠性测度(RM)框架,提出了基于RM的NPSD (RMNPSD)模型,再将反应灵敏度回溯算子引入其中,提出了求解可靠性用户均衡(RMUE)的非线性对向调整算法(NPSA). NPSA无需参数可行性试错过程,且不依赖于导数也无需搜索迭代方向与步长。数值结果显示NPSA的计算效率较高、可作为其他局部收敛算法的初始点搜索方法。 (3)基于出行者的有限感知记忆能力假设,提出并建立了日变事后交通信息的适度矫正发布策略及其动态规划模型,鉴于模型目标函数非线性、连续不光滑且无封闭的显式表达式,论文视其为一个静态非线性规划,并提出一种改进型罗盘搜索算法对其进行求解。基于简单现实路网的数值模拟结果表明事后信息矫正发布策略可提升网络运行效率,并且改进型罗盘搜索具有良好的寻优能力。
[Abstract]:Aiming at the deficiency of the existing research, this paper systematically studies the daily variable traffic path adjustment model, the adjustment algorithm and the traffic information release strategy with the help of behavioral dynamics modeling, numerical simulation and mathematical optimization theory. The main innovations of this paper are summarized as follows: (1) by pointing out the two shortcomings of the classical proportional adjustment process (that is, weak robustness and excessive adjustment), the nonlinear counter-direction behavior based on the counter-directional behavior criterion is established. (NPSD) model of adjusting dynamics, On the basis of this, this paper further discusses the traffic path adjustment behavior under the influence of multi-day travel experience, limited rationality and shortest path guidance behavior, and establishes the multi-day NPSD (MNPSD) model, respectively. The finite rational NPSD (BRNPSD) model and the shortest path oriented nonlinear adjusting dynamics (NMSD) model. It is found that the above four path adjustment models can avoid the problem of weak robustness and excessive adjustment, and then keep the iterative solution set unchanged, and their stable path flow patterns are equivalent to their corresponding user equilibrium. Both ii) NPSD and NMSD are rational behavior adjustment processes, and their continuous models are globally stable. The numerical results show that the sensitivity of user response has an important influence on the evolution process and result of network traffic flow. II) the excessive reliance on past travel experience in path adjustment may increase the risk of network instability. Iii) the evolutionary stability of the network is not always better than that of perfect rationality. The stability of iv) DNPSD is better than that of DNMSD, and the former is more suitable for developing traffic flow equilibrium algorithm. (2) by introducing the risk-based path travel time measure MBTT, and combining it with the risk-averse measure METT, A path travel time measure (CMTT,), which can describe various risk attitudes, is constructed and incorporated into the travel time reliability measure (RM) framework. The NPSD (RMNPSD) model based on RM is proposed, and the reaction sensitivity traceback operator is introduced into it. In this paper, a nonlinear counterbalancing algorithm, (NPSA)., is proposed to solve the reliability user equilibrium (RMUE). NPSA does not need parameter feasibility trial and error process, and does not depend on derivative, and does not need to search the direction and step of iteration. Numerical results show that NPSA is more efficient and can be used as an initial point search method for other local convergence algorithms. (3) based on the assumption of limited perceptual memory ability of travelers, In this paper, an appropriate corrective release strategy and its dynamic programming model for traffic information after daily change are proposed and established. In view of the nonlinear objective function of the model, the explicit expression of continuous non-smooth and unclosed, the paper regards it as a static nonlinear programming. An improved compass search algorithm is proposed to solve the problem. The numerical simulation results based on the simple reality road network show that the post-event information correction and release strategy can improve the efficiency of the network and the improved compass search has a good ability to search for optimal results.
【学位授予单位】：北京交通大学
【学位级别】：博士
【学位授予年份】：2014
【分类号】：U491

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