Toll product preferences and implications for alternative payment options and going cashless

There has been a great deal of research on deriving estimates of the value of travel time savings (VTTS) as a way of converting travel time benefits of toll roads relative to free routes into monetary units, the major user benefit in the development of forecasts of traffic and hence revenue streams. By contrast there has been almost no consideration given to identifying the role that various tollroad products play in establishing preferences for toll routes over non-tolled routes. Increasingly tollroads give users the option to pay by cash at a toll booth, by electronic tolling or by a pre- or post-paid debit and credit account system involving vehicle identification. The efficiency gained by electronic tolling for both the users and the operator have resulted in moves in many jurisdictions to eliminate cash collection entirely (or not introduce it when introducing a new tolled road facility), and to introduce a range of pre- and post-payment options. This has been accompanied by a growing move to distance-based charging in some contexts which is more cumbersome to structure with a cash option. This paper investigates current and potential travellers’ preferences for a range of toll products and how much individual’s are willing to pay for very specific toll products. Data from a stated choice experiment is used in a mixed logit model to establish the role that toll products play in the context of offered times and costs of alternative routes, in choosing between alternative ways of paying for the use of tolled routes.

基于混合Logit模型的旅客对短途高速铁路列车选择行为

以南京到上海和南京到杭州的短途高速铁路客流为背景,应用行为调查法与意向调查法开展客流调查,获取客流数据.基于选择行为理论,以旅客对列车的选择作为因变量,旅客个体特征、出行特征、列车服务水平作为白变量,基于多项式Logit模型构建混合Logit模型,拟合客流调查数据.结果 表明:混合Logit模型的拟合优度高于多项式Lo...     

引入旅游偏好的城际客运出行分布预测模型

针对目前城际客运出行分布预测过程中对城际旅游关联性考虑不足的问题，借助手机信 令数据，对长三角26个城市5A和4A级景点的城际游客客源地分布进行分析发现，在同一个城市 中，无论是从单个头部景点层面还是全部5A和4A级景点总体层面上来看，城际游客客源地分布 规律均较为相近，且在非节日的不同日期，这种分布也非常稳定。基于这种特性，借助亲景度指 标提出一个可以表征两个城市间旅游关联性的旅游偏好变量，并将其引入基本重力模型中构建 城际客运出行分布预测模型。基于长三角26个城市出行分布现状数据对模型系数进行标定后的 结果表明，模型拟合程度显著提高，标准误差大幅下降，75%的OD对预测结果得到改善。因此， 可以认为引入旅游偏好变量有利于提高城际客运出行分布预测模型的精度。     

Eliciting preferences for adoption of fully automated vehicles using best-worst analysis

Autonomous mobility is one of the rapidly evolving aspects of smart transportation which carries the potential of reshaping both demand and supply sides of transportation systems. While understanding public opinions about autonomous vehicles (AVs) is a compelling step towards their successful implementation, still little is known about to which extent people will embrace this new technology and how the vehicle features will affect their adoption decision. This study presents a new approach for modeling the adoption behavior of fully AVs using the profile-case best-worst scaling model. In this approach, an AV profile which is characterized in terms of the main vehicle attributes and their associated levels is presented to the decision maker and he/she is asked to select the most and the least attractive attributes. Further, a binary adoption question at the end of the choice task inquires if the respondent is willing to purchase the described AV. Utilizing this method, we can recognize the difference between the intrinsic impacts of the vehicle attributes and the impact of the attribute levels on the adoption decision. Results of the analysis indicate that people are much more sensitive to the purchase price and incentive policies such as taking liability away from the “driver” in case of accidents and provision of exclusive lanes for AVs compared to other factors such as fuel efficiency, safety, or environmental friendliness. Further, it is found that millennials with higher income, those who live in the downtown area, and the majority of people who have experienced an accident in the past have greater interests in adopting this technology.     

The influence of attitude towards individuals’ choice for a remotely piloted commercial flight: A latent class logit approach

The Remotely Piloted Commercial Passenger Aircraft Attitude Scale (RPCPAAS) was created to measure positive and negative attitudes towards a new and plausible form of air travel. This information was then used, in combination with a latent class logit model built on data generated from a stated choice experiment to gain insight into the choice behaviour between conventionally piloted aircraft (CPA) with a pilot on-board and remotely piloted aircraft (RPA) with a pilot on the ground. The results revealed that individuals, on-average, if presented a choice between a CPA and a RPA of equivalent attributes, would elect for the CPA option. However, there is variability in the passengers’ sensitivity to various flight attributes, and these sensitivities were influenced by individuals’ attitude towards the new technology (i.e., RPA). From an operational perspective, and assuming that one day passengers of commercial airlines are offered the choice between CPA and RPA, the strategies employed by airlines to encourage the use of the new technology need to be different, based on individuals’ attitude towards RPA.     

Anticipating PEV buyers’ acceptance of utility controlled charging

Utility controlled-charging (UCC) of plug-in electric vehicles (PEVs) could potentially align vehicle charging with the availability of intermittent, renewable electricity sources. We investigated the case of a nightly charging program where the electric utility can control home PEV charging. To explore consumer acceptance of this form of UCC, we implemented a web-based survey of new vehicle buyers in Canada (n = 1470). The survey assessed interest in PEVs, explained UCC, and elicited openness to UCC through attitudinal questions and a stated choice experiment. We find potential for UCC support among one-half to two-thirds of respondents interested in purchasing a PEV, depending on the scenario. However, some respondents express concerns with privacy and loss of control. To quantify preferences for UCC, we estimated a latent class choice model where respondents chose between different PEV charging programs. The model identified four distinct respondent segments (or classes) that vary in their acceptance of UCC, as well as their valuation of renewable electricity, saving money on their electrical bill, and undergoing charging inconvenience. The overall sample was more sensitive to cost incentives than to renewable incentives, where cost-based UCC programs garnered 63–78% enrollment while renewable-based programs garnered only 49–59% enrollment. Overall, we observe the potential for widespread acceptance of UCC programs among Canadian PEV buyers, but program design and deployment will need to carefully acknowledge the various motivations and concerns of different vehicle buyer segments.     

Willingness-to-pay for alternative fuel vehicle characteristics: A stated choice study for Germany

In the light of European energy efficiency and clean air regulations, as well as an ambitious electric mobility goal of the German government, we examine consumer preferences for alternative fuel vehicles (AFVs) based on a Germany-wide discrete choice experiment among 711 potential car buyers. We estimate consumers’ willingness-to-pay and compensating variation (CV) for improvements in vehicle attributes, also taking taste differences in the population into account by applying a latent class model with 6 distinct consumer segments. Our results indicate that about 1/3 of the consumers are oriented towards at least one AFV option, with almost half of them being AFV-affine, showing a high probability of choosing AFVs despite their current shortcomings. Our results suggest that German car buyers’ willingness-to-pay for improvements of the various vehicle attributes varies considerably across consumer groups and that the vehicle features have to meet some minimum requirements for considering AFVs. The CV values show that decision-makers in the administration and industry should focus on the most promising consumer group of ‘AFV aficionados’ and their needs. It also shows that some vehicle attribute improvements could increase the demand for AFVs cost-effectively, and that consumers would accept surcharges for some vehicle attributes at a level which could enable their private provision and economic operation (e.g. fast-charging infrastructure). Improvement of other attributes will need governmental subsidies to compensate for insufficient consumer valuation (e.g. battery capacity).     

Preferences for shared autonomous vehicles

Shared autonomous vehicles (SAVs) could provide inexpensive mobility on-demand services. In addition, the autonomous vehicle technology could facilitate the implementation of dynamic ride-sharing (DRS). The widespread adoption of SAVs could provide benefits to society, but also entail risks. For the design of effective policies aiming to realize the advantages of SAVs, a better understanding of how SAVs may be adopted is necessary. This article intends to advance future research about the travel behavior impacts of SAVs, by identifying the characteristics of users who are likely to adopt SAV services and by eliciting willingness to pay measures for service attributes. For this purpose, a stated choice survey was conducted and analyzed, using a mixed logit model. The results show that service attributes including travel cost, travel time and waiting time may be critical determinants of the use of SAVs and the acceptance of DRS. Differences in willingness to pay for service attributes indicate that SAVs with DRS and SAVs without DRS are perceived as two distinct mobility options. The results imply that the adoption of SAVs may differ across cohorts, whereby young individuals and individuals with multimodal travel patterns may be more likely to adopt SAVs. The methodological limitations of the study are also acknowledged. Despite a potential hypothetical bias, the results capture the directionality and relative importance of the attributes of interest.