有限理性视野下出行者出行方式选择分层Logit模型研究

在传统分层Logit模型的基础上,放松出行者完全理性的假设,基于有限理性满意决策准则,建立了多方式有限理性分层Logit(BRNL)模型,来描述出行者的方式选择行为.模型假设当方式间的成本差在无差异区间内时,出行者依据偏好或随机进行方式选择;否则,出行者将选择出行成本更小的交通方式.此外,提出了一种嵌套的相继平均算法对模型进行求解.最后,通过一个数值算例验证了模型的合理性和算法的有效性.研究结果表明,出行者并不总是选择出行成本最小的交通方式,其选择行为与出行者的理性程度和偏好有关,且理性程度越低,出行者对方式间的成本差越不敏感.     

基于混合Logit 模型的网约车选择行为研究

近年来,网约车发展迅速,而现有研究较少从市场角度理解用户对网约车的选择偏 好.本文构建了基于混合Logit选择模型,选取网约车依赖性、出行目的等出行相关属性,年龄等 个人社会经济属性为效用函数特征变量,假设到达时间、在车时间和费用为随机变量并服从对 数正态分布.使用D-efficient效率设计法生成问卷,在成都市开展网约车使用特征与选择偏好的 实证调查.基于观察数据标定模型,参数显著性及符号解释了城市综合交通背景下出行方式选 择的关键因素.对出租车和网约车费用进行边际效应分析,明确了价格变化对出行结构的影响.     

The implications on willingness to pay of respondents ignoring specific attributes

Individuals processing the information in a stated choice experiment are typically assumed to evaluate each and every attribute offered within and between alternatives, and to choose their most preferred alternative. However, it has always been thought that some attributes are ignored in this process for many reasons, including a coping strategy to handle ones perception of the complexity of the choice task. Nonetheless, analysts typically proceed to estimate discrete choice models as if all attributes have influenced the outcome to some degree. The cognitive processes used to evaluate trade-offs are complex with boundaries often placed on the task to assist the respondent. These boundaries can include prioritising attributes and ignoring specific attributes. In this paper we investigate the implications of bounding the information processing task by attribute elimination through ignoring one or more attributes. Using a sample of car commuters in Sydney we estimate mixed logit models that assume all attributes are candidate contributors, and models that assume certain attributes are ignored, the latter based on supplementary information provided by respondents. We compare the value of travel time savings under the alternative attribute processing regimes. Assuming that all attributes are not ignored and duly processed, leads to estimates of parameters which produce significantly different willingness to pay (WTP) to that obtained when the exclusion rule is invoked.     

Modeling household activity–travel interactions as parallel constrained choices

The daily activity-travel patterns of individuals often include interactions with other household members, which we observe in the form of joint activity participation and shared rides. Explicit representation of joint activity patterns is a widespread deficiency in extant travel forecasting models and remains a relatively under-developed area of travel behavior research. In this paper, we identify several spatially defined tour patterns found in weekday household survey data that describe this form of interpersonal decision-making. Using pairs of household decision makers as our subjects, we develop a structural discrete choice model that predicts the separate, parallel choices of full-day tour patterns by both persons, subject to the higher level constraint imposed by their joint selection of one of several spatial interaction patterns, one of which may be no interaction. We apply this model to the household survey data, drawing inferences from the household and person attributes that prove to be significant predictors of pattern choices, such as commitment to work schedules, auto availability, commuting distance and the presence of children in the household. Parameterization of an importance function in the models shows that in making joint activity-travel decisions significantly greater emphasis is placed on the individual utilities of workers relative to non-workers and on the utilities of women in households with very young children. The model and methods are prototypes for tour-based travel forecasting systems that seek to represent the complex interaction between household members in an integrated model structure.     

A tour-based model of travel mode choice

This paper presents a new tour-based mode choice model. The model is agent-based: both households and individuals are modelled within an object-oriented, microsimulation framework. The model is household-based in that inter-personal household constraints on vehicle usage are modelled, and the auto passenger mode is modelled as a joint decision between the driver and the passenger(s) to ride-share. Decisions are modelled using a random utility framework. Utility signals are used to communicate preferences among the agents and to make trade-offs among competing demands. Each person is assumed to choose the best combination of modes available to execute each tour, subject to auto availability constraints that are determined at the household level. The households allocations of resources (i.e., cars to drivers and drivers to ride-sharing passengers) are based on maximizing overall household utility, subject to current household resource levels. The model is activity-based: it is designed for integration within a household-based activity scheduling microsimulator. The model is both chain-based and trip-based. It is trip-based in that the ultimate output of the model is a chosen, feasible travel mode for each trip in the simulation. These trip modes are, however, determined through a chain-based analysis. A key organizing principle in the model is that if a car is to be used on a tour, it must be used for the entire chain, since the car must be returned home at the end of the tour. No such constraint, however, exists with respect to other modes such as walk and transit. The paper presents the full conceptual model and estimation results for an initial empirical prototype. Because of the complex nature of the model decision structure, choice probabilities are simulated from direct generation of random utilities rather than through an analytical probability expression.     

回转体外形的参函数逼近

在文献[4]的基础上,进一步讨论了回转体外形的参函数逼近方法。利用这种方法可以自然满足边界条件,简化逼近计算;可以对给定的型值进行直观的检查和光顺,提高逼近精度;可以显示出节点的合理部位,减少节点选择的盲目性。 作为文献[4]的继续和补充,还给出了圆锥端头截体和平端头截体的数学表达式。     

基于离散选择理论的出行方式/目的地联合模型研究

分析了出行方式/目的地选择的必要性,并以合肥市居民出行调查数据为基础,在对出行目的地空间分布特点进行分析的基础上,提出了减少选择枝个数的目的小区分段抽样策略,并在该抽样策略下建立了方式/目的地联合选择模型,模型结果在数学统计和符号逻辑上均达到要求;最后对联合选择模型和重力模型就本案例数据进行了对比分析,结果表明,联合选择模型及结果与实际统计结果差值更小。     

An Analysis of Weekend Work Activity Patterns in the San Francisco Bay Area

The purpose of this study is to examine the spatial and temporal characteristics of weekend work episodes. Specifically, we examine whether individuals work over the weekend and, if they work, whether they work at home or outside the home. We also model the time of day of weekend work. The empirical analysis in the paper is based on the 2000 San Francisco Bay Area Travel Survey. The results indicate the important effects of day of week/seasonal effects, individual demographics, work-related variables, household characteristics, and location variables on weekend work participation characteristics. The models estimated in the paper may be embedded within a larger weekend activity-travel pattern forecasting model system.     

诱导信息条件下驾驶员路径选择行为研究

驾驶员的路径选择行为是影响交通诱导成效的一个关键因素。建立了诱导信息条件下驾驶员路径选择行为模型,仿真分析了诱导信息和驾驶员的经验对驾驶员路径选择行为、路网交通流分布、系统整体效益的影响。研究结果表明,随着出行次数的增加,2条路径的交通流波动逐步减小,系统总行程时间逐渐减少,逐渐趋于系统均衡。驾驶员的长期经验、诱导信息的长期准确对驾驶员的路径选择行为、系统均衡具有重要影响。     

基于随机用户平衡的混合交通网络流量分离模型

考虑了影响出行者交通选择行为的主要因素(时间、费用、方便性、舒适性等),分析了在多种交通方式(私家车、出租车、公交车、轨道交通以及自行车等)存在条件下城市交通网络中出行者交通选择行为,包括交通方式选择和出行路径选择,并基于随机用户平衡(SUE)理论构造了城市混合交通网络的流量分离和分配综合模型及求解算法。最后通过一个简单算例,得到了当各种影响因素变化时,各种交通方式的流量变化情况。