Bike route choice modeling using GPS data without choice sets of paths

Concerned by the nuisances of motorized travel on urban life, policy makers are faced with the challenge of making cycling a more attractive alternative for everyday transportation. Route choice models can help achieve this objective by gaining insights into the trade-offs cyclists make when choosing their routes and by allowing the effect of infrastructure improvements to be analyzed. We estimate a link-based bike route choice model from a sample of GPS observations in the city of Eugene on a network comprising over 40,000 links. The so-called recursive logit (RL) model (Fosgerau et al., 2013) does not require to sample any choice set of paths. We show the advantages of this approach in the context of prediction by focusing on two applications of the model: link flows and accessibility measures. Compared to the path-based approach which requires to generate choice sets, the RL model proves to make significant gains in computational time and to avoid paradoxical accessibility measure results discussed in previous works, e.g. Nassir et al. (2014).     

Japanese perspective of driver information systems

A perspective view of of Japanese R&D activities of Driver Information Systems is given from the standpoint of developing joint projects by public and private sectors. First, a brief history of the R&D activities is illustrated from above mentioned standpoint. Then, two major projects, AMTICS and RACS, and the social backgrounds of these projects are explained. In order to give a clear idea of both projects some technical details are treated.Based on the history and the present status of the developments, the basic design conceptions of Japanese Driver Information Systems are explained and several factors or reasons which have influenced to the design conception are discussed. Then, the promoting systems of the R&D activities are generally explained and present status of the projects and future problems in developing more advanced systems are also handled. A brief discussion on the establishment of international standard is also mentioned as a final comment.     

大城市客运交通结构优化模型研究

城市客运交通结构是关系城市交通系统发展方向的核心问题。从城市交通可持续发展角度出发建立了大城市客运交通结构优化的线性规划模型,其中决策变量为城市客运交通系统中各种交通方式的周转量。该模型的目标为最大化城市客运交通效率,该交通效率不是简单的各种交通方式客运周转量的函数,而是由各种交通方式的客运周转量和各种交通方式对城市客运交通效率贡献率共同决定。同时考虑客运交通结构优化过程中应满足的出行需求总量约束、可达性约束、占地约束、能耗约束、环境容量约束和各种交通方式发展规模约束等。该模型在实际应用中取得了良好的效果。     

多模式拥挤交通网络中的路径分配与收费定价模型

根据城市混合交通拥挤的特点,提出了在收费路段对不同的交通方式收取不同费用,以此控制各种交通方式的分担量,鼓励人们更多地选用公共的交通工具,从而达到缓解交通拥挤的目的,并以此为出发点建立了一个关于多模式收费定价的双层规划模型.     

基于路段能力可靠性的城市交通网络设计

在介绍城市交通网络设计和概率用户平衡配流模型基本思想和内容的基础上,建立了考虑可靠性条件的城市交通网络设计双层规划模型,上层模型在投资约束条件下寻求系统总阻抗最小,下层模型兼顾路段能力可靠性与用户平衡配流条件,从而使城市交通网络备用能力最大,并针对该问题设计了可求得局部或全局最优解的混沌优化启发式算法,最后选用一个小型网络作为算例进行验证。结果说明该模型有一定的实际应用价值且设计的混沌优化算法也较为有效。     

信号控制对动态路线选择的影响研究

以动态路线选择模型为基础的先进的出行者信息系统（ＡＴＩＳ）的实施必然对城市交通控制系统产生影响，同时交通控制系统的控制方案对路线诱导信息“运行时间”的估计也发生作用，影响用户对最优路线的造选择。对两系统的相互关系进行了分析，并建立了两系统相互关系模型最后给出了实际案例分析。     

Modeling heterogeneous risk-taking behavior in route choice: A stochastic dominance approach

This paper proposes a unified approach to modeling heterogonous risk-taking behavior in route choice based on the theory of stochastic dominance (SD). Specifically, the first-, second-, and third-order stochastic dominance (FSD, SSD, TSD) are respectively linked to insatiability, risk-aversion and ruin-aversion within the framework of utility maximization. The paths that may be selected by travelers of different risk-taking preferences can be obtained from the corresponding SD-admissible paths, which can be generated using general dynamic programming. This paper also analyzes the relationship between the SD-based approach and other route choice models that consider risk-taking behavior. These route choice models employ a variety of reliability indexes, which often make the problem of finding optimal paths intractable. We show that the optimal paths with respect to these reliability indexes often belong to one of the three SD-admissible path sets. This finding offers not only an interpretation of risk-taking behavior consistent with the SD theory for these route choice models, but also a unified and computationally viable solution approach through SD-admissible path sets, which are usually small and can be generated without having to enumerate all paths. A generic label-correcting algorithm is proposed to generate FSD-, SSD-, and TSD-admissible paths, and numerical experiments are conducted to test the algorithm and to verify the analytical results.     

非线性最小二乘参数平差的非线性规划算法研究

讨论了非线性最小二乘参数平差可行的5种非线性规划算法－牛顿法、最速下降法、离散牛顿法、拟牛顿法和SQPM算法,通过分析、比较和实算证实SQPM算法是求解非线性最小二乘参数平差问题的最为有力的工具,且使SQPM算法成为无需精确计算参数概略值的非线性最小二乘参数平差法。     

考虑出行者损失厌恶的后悔随机用户均衡模型

在经典随机后悔最小化模型的基础上,通过引入出行者获益损失的不对称偏好,建立了考虑出行者损失厌恶的属性水平的后悔函数及基于Logit形式的随机用户均衡模型.在提出的属性水平的后悔函数中,等尺度的获益和损失所产生的欣喜和后悔的差异,受后悔欣喜偏好参数和出行者损失厌恶共同影响.此外,与上述随机用户均衡模型等价的变分不等式问题被给出,并用相继平均法求解.最后,用1个算例网络来验证所提出模型的合理性和算法的可行性.结果表明,出行者的损失厌恶对其路径选择行为具有较大的影响,并且随着损失厌恶程度的增大,出行者更倾向于选择最短路径.     

交通网络最优路径搜索的蚁群算法

针对交通网络中最优路径搜索问题,本文提出一种基于蚁群算法的新的求解方法。首先从剖析最优路径问题的求解要求出发,探讨蚁群算法求解的优势,由于其并行性、正反馈、协作性等特点,能在较短的时间内发现较优解。然后,根据交通网络的特性,在基本蚁群算法的基础上,引入信息素限定规则,采用平滑机制进行局部更新,改进了全局更新模型等,使该算法更能满足交通系统最优路径的求解要求,降低了路径选择的复杂性,从而提高计算效率。对改进的模型进行的模拟实验和比较分析表明,该模型与算法的效果良好。该研究为交通系统最优路径问题开创了一条新的途径,同时显示出蚁群算法在交通分配中的良好使用前景。