Modelling mode choice for freight transport using advanced choice experiments

In this paper we use advanced choice modelling techniques to analyse demand for freight transport in a context of modal choice. To this end, a stated preference (SP) survey was conducted in order to estimate freight shipper preferences for the main attributes that define the service offered by the different transport modes. From a methodological point of view, we focus on two critical issues in the construction of efficient choice experiments. Firstly, in obtaining good quality prior information about the parameters; and secondly, in the improved quality of the experimental data by tailoring a specific efficient design for every respondent in the sample.With these data, different mixed logit models incorporating panel correlation effects and accounting for systematic and random taste heterogeneity are estimated. For the best model specification we obtain the willingness to pay for improving the level of service and the elasticity of the choice probabilities for the different attributes. Our model provide interesting results that can be used to analyse the potential diversion of traffic from road (the current option) to alternative modes, rail or maritime, as well as to help in the obtaining of the modal distribution of commercial traffic between Spain and the European Union, currently passing through the Pyrenees.     

Drivers’ parking location choice under uncertain parking availability and search times: A stated preference experiment

To assess parking pricing policies and parking information and reservation systems, it is essential to understand how drivers choose their parking location. A key aspect is how drivers’ behave towards uncertainties towards associated search times and finding a vacant parking spot. This study presents the results from a stated preference experiment on the choice behaviour of drivers, in light of these uncertainties. The attribute set was selected based on a literature review, and appended with the probabilities of finding a vacant parking spot upon arrival and after 8 min (and initially also after 4 min, but later dropped to reduce the survey complexity). Efficient Designs were used to create the survey design, where two rounds of pilot studies were conducted to estimate prior coefficients. Data was successfully collected from 397 respondents. Various random utility maximisation (RUM) choice models were estimated, including multinomial logit, nested logit, and mixed logit, as well as models accounting for panel effects. These model analyses show how drivers appear to accept spending time on searching for a vacant parking spot, where parking availability after 8 min ranks second most important factor in determining drivers’ parking decisions, whilst parking availability upon arrival ranks fourth. Furthermore, the inclusion of heterogeneity in preferences and inter-driver differences is found to increase the predictive power of the parking location choice model. The study concludes with an outlook of how these insights into drivers’ parking behaviour can be incorporated into traffic assignment models and used to support parking systems.     

Estimation of a route choice model for urban public transport using smart card data

This paper describes a logit model of route choice for urban public transport and explains how the archived data from a smart card-based fare payment system can be used for the choice set generation and model estimation. It demonstrates the feasibility and simplicity of applying a trip-chaining method to infer passenger journeys from smart card transactions data. Not only origins and destinations of passenger journeys can be inferred but also the interchanges between the segments of a linked journey can be recognised. The attributes of the corresponding routes, such as in-vehicle travel time, transfer walking time and to get from alighting stop to trip destination, the need to change, and the time headway of the first transportation line, can be determined by the combination of smart card data with other data sources, such as a street map and timetable. The smart card data represent a large volume of revealed preference data that allows travellers' behaviour to be modelled with higher accuracy than by using traditional survey data. A multinomial route choice model is proposed and estimated by the maximum likelihood method, using urban public transport in ?ilina, the Slovak Republic, as a case study     

Route Choice Behaviour of Freeway Travellers Under Real-time Traffic Information Provision – Application of the Best Route and the Habitual Route Choice Mechanisms

Abstract

This paper investigates route choice behaviour on freeways between Taipei and Taichung in Taiwan under the provision of real-time traffic information. Two types of route choice selection rules (the best-route and habitual-route) are analysed using ordered probit models to identify the major influences on freeway travellers’ route choice behaviour. The level of service associated with each route is defined as a generalised cost saving (GCS) and specified non-linearly with a threshold inherent to travellers. The marginal (dis)utility thresholds in the ‘best’ and ‘habitual’ behaviour models are identified through a goodness-of-fit grid. The results confirm that the thresholds for changing the inertia behaviour of drivers should be larger than the ones for choosing the best routes. In addition, the drivers are more likely to choose either the best or the habitual routes once the GCS are greater than the identified threshold values.     

基于面板数据的乘用车购买偏好分析

基于2009-2019年中国乘用车销售面板数据,结合车辆特性构建Logit模型,分析车辆特性衍变对消费者需求的响应,对比中国和瑞士乘用车的消费偏好。研究结果显示：发动机燃油效率更高,功率更大的乘用车市场份额占比更高;重型车比轻型车更受中国消费者青睐;燃油效率的边际值在大功率汽车细分市场中较小,即最可能产生更多污染排放的消费者对汽车燃油效率的敏感性较低;仍处于乘用车快速普及阶段的中国与处于复数保有阶段(千人保有超过250辆)的瑞士,消费者偏好有明显差异,中国消费者对省油、大功率和重型乘用车的偏好在逐渐加深,瑞士消费者对省油、大功率和轻型车用车的偏好在逐步降低。     

城市轨道交通新线开通对出行方式选择的影响研究

为研究城市轨道交通新线开通对出行方式选择的影响,开展了出行方式转换的SP(Stated Preference)调查,构建全目的和通勤出行方式选择的MNL模型(Multinomial Logit model)。定量分析了个体属性和交通方式属性对出行者交通方式选择的影响。研究表明：乘客感知的轨道交通全目的出行时耗负效用为相同时耗公交的91%,而通勤时耗负效用为全目的出行的1.89倍;轨道交通出行总时耗对分担率影响最显著,前者增减50%时,后者变动约10%;公交是轨道交通的主要竞争方式,当前者出行耗时提高50%时,后者分担率将增加6.8%;停车费小幅提高和出行时耗增加不能显著促使小汽车使用者转向轨道交通,交通需求管理是引导出行转移的重要途径。     

The evaluation of high occupancy vehicle lanes on sun yat‐sen freeway in Taiwan

This study proposes a methodological framework to incorporate latent factors, including direct and indirect perceptions, as the explanatory variables in a discrete choice models using revealed preference and stated preference data sets. The methodology requires the estimation of a model system comprising of a discrete choice model and the structural and measurement equations of a latent variable model. The application involves the evaluation of responses to the new high occupancy vehicle (HOV) lanes on the Sun Yat‐Sen Freeway in Taiwan. The results obtained from this study provide valuable insights into the planning and assessment of HOV lanes.     

综合管廊投资运营模式选择模型构建研究

为从当前国内常用的投资运营模式中遴选出与综合管廊项目特征契合的模式，保障综合管廊实现成功运营，通过对国内常用的几种投资运营模式进行分析，建立以项目特征、工作效能、社会效益、经济效益和项目风险为准则层、包含18个指标的综合管廊投资运营模式选择指标体系，选择逼近理想解对指标进行量化计算。运用层次分析法与逼近理想解相结合的方法克服逼近理想解无法确定指标权重的缺点，并引入云模型对层次分析法和逼近理想解分别加以改进，充分考虑模式选择过程中专家评价语言的不确定性，构建基于云模型改进AHP-TOPSIS的综合管廊投资运营模式选择模型，同时以西安市某综合管廊PPP项目Ⅰ标段为案例，验证了该模式选择模型具有较高的拟合度。     

客票数据“受限”条件下旅客选择偏好估计

深入研究客运市场需求,是有效开展客运产品营销工作的前提.区别于既有的以问卷调查为基础的旅客选择行为研究,本文利用客票销售数据研究铁路客运产品选择偏好的估计方法.该方法考虑了部分时段部分列车在供不应求情况下,客票存根数据难以反映旅客真实选择行为的特点,根据预售期内各产品的实时余票数据,对预售期进行划分,建立了分时段的极大似然函数.针对所构建的似然函数,利用EM算法处理流失客流不可获知的问题,从而估计旅客选择偏好.通过实例,估计了徐州东至南京南方向旅客对京沪高铁客运产品的选择偏好.该方法以日常销售数据为基础,能够及时获取旅客选择偏好,具有较强的时效性,可为铁路日常营销工作提供参考.     

Value of leisure time based on individuals' mode choice behavior

Values of time have been defined in various forms such as value of leisure time (shadow price of time), value of travel time, and value of saving time, and are mostly measured based on individuals' travel choice behavior. The main purpose of this study is to estimate the value of leisure time by general mode choice models. The estimated level can be used to evaluate the benefits from the increasing leisure time gained by people in Taiwan after the government has practiced a series of policies to shorten employee's working hours in the last few years. To justify the application, this study reviews and reinterprets the theoretical results of some major works on value of time derivations. Then to practically estimate the value of leisure time, it suggests a method of combining revealed preference and stated preference data for application. Finally, it conducts an empirical study on travelers' mode choices behavior in Taiwan to carry out the method suggested. The value of leisure time is estimated at 56NT$ per hour (around 1.65US$/hr), which is even lower than the minimum wage rate regulated by Taiwan government.