基于前景理论的出行者风险条件下路径选择行为研究

发布时间：2018-05-04 17:15

本文选题：交通分配 + 路径选择　；参考：《天津大学》2016年博士论文

【摘要】：出行者路径选择行为分析是预测城市交通状态、制定有效的交通控制诱导策略以及实施交通基础设置布局与优化的重要基础。城市交通路网由于交通供给和需求等在时空分布上的随机性而充满了不确定性,出行者在随机和不确定路网环境下会表现出不同的有限理性路径选择行为。本文以前景理论模型为基础,围绕“风险和不确定环境下的出行者有限理性路径选择行为建模与分析”这一主题,分别从出行者的路网感知、路径评价和路径决策等逻辑阶段描述和改进了出行者的有限理性认知和路径决策行为模型和相应的网络均衡模型,然后结合理论和算例分析了不同有限理性因素对路网均衡预测的影响和作用规律。具体内容包括以下几个方面:(1)研究随机感知偏差对个体旅行时间感知及出行路径决策的影响和作用方式。分析随机感知偏差对个体感知旅行时间分布的影响,用其替代累积前景理论中的概率权重分布,构建了基于感知旅行时间分布的前景理论模型。感知旅行时间分布在保证概率的基本性质的同时,放松了对路径旅行时间分布类型的假设(在城市路网中较难获得)。算例分析表明随机感知偏差的均值参数通过影响感知旅行时间的均值和方差,随机感知偏差的方差参数通过影响感知旅行时间分布的方差来灵活地刻画出行者在时间感知上的有限理性行为。在感知旅行时间分布下,路网的均衡流量分布预测会受到影响,同时路网期望总旅行时间和路段期望流量/通行能力之比呈现出相反的趋势波动。(2)考虑出行者在路径决策阶段的有限理性行为。假设出行者采用基于排序的决策机制从满足阈值要求的方案中进行方案决策,并分析了这种决策机制在描述个体和群体决策方案规模及决策阶段有限理性方面的灵活性。然后结合排序决策机制构建了拥挤路网下考虑旅行时间-固定收费的双因素用户均衡模型,其中用连续分布的旅行时间价值参数来描述出行者对两种因素的偏好异质性,并给出了均衡问题的变分不等式模型。新模型可以灵活描述出行者在路径决策阶段的有限理性行为,可以作为基于“阈值---无差异区间”的有限理性行为理论的潜在替代理论模型。(3)综合(1)和(2)的研究构造了风险条件下复杂个体路径选择行为模型,提出两种多因素参照点模型,即基于单因素分别最优的理想参照点和基于路径的参照点模型。数值算例分析发现出行者在方案决策阶段表现出的有限理性行为可能会带来路网性能指标(总旅行时间和总收费)的改进;而假设出行者采用理想参照点不一定会带来路网性能指标的改善。同时,本文根据提出的模型的性质分别设计了不同的求解算法,并结合数值算例展示了算法的有效性。最后,本文总结分析了本文的研究不足和未来的研究方向。
[Abstract]:The analysis of travelers' path choice behavior is an important basis for predicting urban traffic conditions, formulating effective traffic control and guidance strategies, and implementing layout and optimization of traffic infrastructure. Due to the randomness of traffic supply and demand in time and space distribution, urban traffic network is full of uncertainty, and travelers will show different behavior of limited rational path selection under random and uncertain road network environment. Based on the foreground theory model, this paper focuses on the theme of "Modeling and analyzing the behavior of traveler's limited rational path selection in the environment of risk and uncertainty", and respectively from the perspective of the road network perception. The logical stages, such as path evaluation and path decision, describe and improve the behavior model of bounded rational cognition and path decision and the corresponding network equilibrium model. Then the influence of different finite rational factors on road network equilibrium prediction is analyzed by combining theory and numerical examples. The specific contents include the following aspects: 1) to study the impact of random perception bias on individual travel time perception and travel path decision. This paper analyzes the influence of random perception bias on individual perceived travel time distribution, and uses it to replace the probability weight distribution in cumulative foreground theory, and constructs a foreground theory model based on perceptual travel time distribution. The perceived travel time distribution not only guarantees the basic properties of the probability, but also loosens the assumptions about the type of path travel time distribution (which is difficult to obtain in urban road networks). Numerical examples show that the mean parameters of random perceptual deviations affect the mean and variance of perceived travel time. The variance parameters of random perceptual deviations can flexibly describe the limited rational behavior of travelers in time perception through the variance that affects the distribution of perceptual travel time. Under the distribution of perceived travel time, the prediction of the equilibrium flow distribution of the road network will be affected. At the same time, the total travel time of road network and the ratio of expected road flow to capacity show the opposite trend. 2) considering the limited rational behavior of the traveler in the path decision stage. It is assumed that the decision mechanism based on ranking is used to make scheme decision from the scheme that meets the threshold requirement, and the flexibility of this decision mechanism in describing the scale of individual and group decision scheme and the limited rationality of decision stage is analyzed. Then, a two-factor user equilibrium model considering travel time and fixed charge under congested road network is constructed, in which continuous distribution of travel time value parameter is used to describe the preference heterogeneity between the two factors. The variational inequality model of equilibrium problem is given. The new model can describe the limited rational behavior of the traveler in the path decision stage flexibly. It can be used as a potential substitute theory model of bounded rational behavior theory based on "threshold-no difference interval". (1) and (2) A complex individual path choice behavior model under risk conditions is constructed, and two multifactor reference point models are proposed. That is, ideal reference point model based on single factor and optimal reference point model based on path. Numerical examples show that the limited rational behavior of travelers in the decision-making stage may lead to the improvement of road network performance indicators (total travel time and total charges). Assuming that travelers adopt ideal reference points will not necessarily lead to the improvement of road network performance. At the same time, different algorithms are designed according to the properties of the proposed model, and numerical examples show the effectiveness of the algorithm. Finally, this paper summarizes and analyzes the lack of research and future research direction.
【学位授予单位】：天津大学
【学位级别】：博士
【学位授予年份】：2016
【分类号】：F224;F590

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