Fast-charging station choice behavior among battery electric vehicle users

This study explores how battery electric vehicle users choose where to fast-charge their vehicles from a set of charging stations, as well as the distance by which they are generally willing to detour for fast-charging. The focus is on fast-charging events during trips that include just one fast-charge between origin and destination in Kanagawa Prefecture, Japan. Mixed logit models with and without a threshold effect for detour distance are applied to panel data extracted from a two-year field trial on battery electric vehicle usage in Japan. Findings from the mixed logit model with threshold show that private users are generally willing to detour up to about 1750 m on working days and 750 m on non-working days, while the distance is 500 m for commercial users on both working and non-working days. Users in general prefer to charge at stations requiring a shorter detour and use chargers located at gas stations, and are significantly affected by the remaining charge. Commercial users prefer to charge at stations encountered earlier along their paths, while only private users traveling on working days show such preference and they turn to prefer the stations encountered later when choosing a station in peak hours. Only private users traveling on working days show a strong preference for free charging. Commercial users tend to pay for charging at a station within 500 m detour distance. The fast charging station choice behavior is heterogeneous among users. These findings provide a basis for early planning of a public fast charging infrastructure.     

Measuring the influence of bus service quality on the perception of users

Encouraging the use of public transport is a key policy goal in many countries. Therefore, public transport should offer the level of quality that accommodates the demands of current users, and importantly, the desires of potential users. This study investigates the influence of the perceived quality of bus service on the perception of both current and potential users. The study draws upon data from 512 questionnaires distributed across Belfast City in the UK. The study utilises a binary logistic regression model to quantify the relationships between the perceived quality of 29 bus indicators (independent) and the perceptions of users towards the overall bus service (dependent). Eleven significant indicators are reported to have significant influence on the perception of users. These indicators are utilised to propose scenarios for optimising the quality of bus service with the perceptions of current and potential users.     

Viability of new road infrastructure with heterogeneous users

This paper explores the importance of heterogeneity in value of time and route choice when assessing the viability of new road infrastructure to alleviate congestion problems. The model incorporates strategic interaction between road operators in a cost-benefit framework and several competitive regimes are considered. It is then employed to establish the financial and socio-economic viability of a congestion pricing demonstration entering Madrid city centre, where road users have to choose between a free but highly congested road and a priced free-flowing road (semi-private regime). A logit estimation is undertaken with information from a questionnaire among road users in the Eastern Madrid area to obtain users’ value of time and of congestion.The tolls obtained generate a traffic reallocation towards the new roadway such that revenues suffice to render the infrastructure socio-economically viable. The private and the low toll regimes generate similar welfare gains that are close to the first best. Yet the former supposes large losses to users. The low toll and the semi-private regimes do not raise such distributional concerns. However, the low toll regime requires a sufficiently high traffic growth rate to make it financially viable; this does not happen for the other competitive regimes.     

A robust approach for road users classification using the motion cues

Video monitoring of traffic is a common practice in major cities. The data generated by video monitoring has practical uses such as traffic analysis for city planning. However, the usefulness of video monitoring of traffic is limited unless there is also a reliable way to automatically classify road users. This paper presents an automated method of road users’ classification into vehicles, cyclists, and pedestrians by using their motion cues. In this method, the movement of road users was captured on sequences of video frames. The videos were analysed using a feature-based tracking system, which has returned the tracks of road users. The separate pieces of information gained from these tracks are hereafter called Classifiers. There are nineteen classifiers included in this method. The classifiers’ values were assessed and integrated into a fuzzy membership framework, which in turn required prior configurations to be available. This led to the final classification of road users. The performance of this method demonstrated promising results. An important contribution of this paper is the creation of a robust approach that can integrate different classifiers using fuzzy membership framework. The developed method also uses parametric classifiers, which do not depend on the specific geometry or traffic operation of the intersection. This is a key advantage because it enables transferability and improves the practicality and usefulness of the method.     

Effect of environmental awareness on electric bicycle users’ mode choices

Travellers’ environmental awareness can affect their mode choices. The primary objective of this study is to identify the effect of electric bicycle (e-bike) users’ environmental awareness on their mode choice when the use of e-bikes is prohibited in urban areas in China. The data were collected via a questionnaire survey administered at ten locations in Nanjing, China. Using mixed multinomial logit (MMNL) models, we examined the relationship between the e-bike users’ mode choice and their environmental awareness, combined with socioeconomic and demographic characteristics and trip attributes. The results show that the level of environmental awareness, gender, age, education, income, the ownership of car and conventional bike, and trip distance affect e-bike users’ choices significantly. Those with a high level of environmental awareness are more likely to choose zero-emission transport modes. A stratified analysis reveals that the effect of environmental awareness is associated with their original transport mode choice prior to their use of the e-bike. With a high level of environmental awareness, original car users tend to opt for moderate- or zero-emission modes; original bus and metro users incline to choose a zero-emission mode or their original mode; and few original cyclists and walkers favour moderate- or high-emission modes. The results of the current study provide transport authorities with insights to establish sustainable urban transportation management policies and strategies to increase the share of zero- and low-emission transport modes.     

On the degradation of performance for traffic networks with oblivious users

We consider the problem of characterizing user equilibria and optimal solutions for routing in a given network. We extend the known models by considering users oblivious to congestion in the following sense: While in the typical user equilibrium setting the users follow a strategy that minimizes their individual cost by taking into account the (dynamic) congestion due to the current routing pattern, an oblivious user ignores congestion altogether; instead, he or she decides his routing on the basis of cheapest routes on a network without any flow whatsoever. These cheapest routes can be, for example, the shortest paths in the network without any flow. This model tries to capture the fact that a certain percentage of travelers base their route simply on the distances they observe on a map, without thinking (or knowing, or caring) about the delays experienced on this route due to their fellow travelers. In this work we study the effect of such users using as the measure of network performance its price of anarchy, i.e., the ratio of the total latency experienced by the users (oblivious or not) at equilibrium over the social optimum.     

Modeling isoexposure to transit users for market potential analysis

Transit operators face a difficult fiscal environment and an imperative to contribute to urban sustainability. Under these circumstances, operators must find innovative ways to make public transportation attractive to broader segments of the public, while simultaneously trying to raise revenue to reduce reliance on public subsidies. Development of commercial partnerships is seen as a promising way to achieve these goals. Previous research has examined the potential of using geodemographics to assist transit agencies in the task of identifying potential partners for developing mutually beneficial commercial agreements. In this paper we describe an approach to model isoexposure to transit users as a tool to assess market potential. The approach is based on the analysis of walking behavior of transit users, and specifically distance walked at the end of their transit trip. Spatial modeling is used to geographically project estimates of walking distance for a desired demographic profile at a specific transit facility. After expanding the estimates using sample weights, overlays of these estimates can be used to generate variations in exposure to transit travelers at different locations in space. The approach is demonstrated using the case of Metro users in Montreal, Canada. The case study demonstrates the use of isoexposure profiles as a novel approach to generate marketing intelligence. This should be of interest to transit agencies and businesses interested in developing partnerships.     

Valuation of users’ benefits in transport systems

Transport projects involve costs and benefits. Benefits to users appear in the form of more and/or better trips. Once the neoclassical idea of demand is accepted, the variation of utility levels underlie the measurement of benefits. In the evaluation process, benefits have to be compared with costs, and this can be done converting utility into monetary units. This paper deals with the treatment of this problem, starting with the general relation among utility, demand and the various forms of consumers’ surplus, to move further into the particular forms that these relations take in the transport field. The rule‐of‐a‐half is followed from the intuitive initial justification to a strict (and general) analytical derivation. More rigorous forms of users’ surplus variation are then presented for fairly general cases, including both aggregate and disaggregate transport demand models, emphasizing the manner in which welfare measures are derived in each case. Discussion is centred around the comparative advantages and limitations of available approaches, searching for improvements in demand formulation and benefits measurement.     

Evaluating bicycle-transit users’ perceptions of intermodal inconvenience

Bicycles and transit systems are considered to be the pinnacle of green transportation. The combined use of the two could provide a competitive alternative for an integrated, green, and seamless service, yet relatively few studies have investigated the multimodal integration problems of the entire service chain from the perspective of users. Users’ perceived inconvenience during travel can be regarded as a latent construct that describes an unobservable and immeasurable characteristic. Nevertheless, the traditional Likert method in an ordinal scale causes a misleading statistical inference. The Rasch model eliminates such bias generated by an ordinal scale through a logistic linear transformation, and it compares person parameters with item parameters, which are then subjected to a logarithmic transformation along a logit scale to clearly identify which service items’ inconvenience cannot be easily overcome by certain users. This empirical study demonstrates that perceived inconveniences differ based on the users’ sex, riding frequency, trip purpose, and environmental awareness. The differential item functioning analysis that was adopted in this study can identify the critical factors leading to the differences in perceived inconvenience. Our empirical results suggest that a male cyclist who is a commuter with a high monthly riding frequency and who is environmentally conscious has a better ability than their counterpart to overcome perceived inconveniences during travel using a bicycle-transit service. To effectively mitigate users’ perceived inconvenience, the Rasch analytical results suggest that the improvement of the intra-transit system factors in the short term and the improvement of external environmental factors in the long term will be successful. The information herein proves useful for transportation planners and policy makers when considering the special travel needs of certain groups to create a user-friendly bicycle-transit travel environment that promotes its usage.     

Determinants affecting ferry users’ waiting time at ferry terminals

Transportation - The paper develops a model to examine how different factors influence ferry users’ waiting time at the terminals. The estimations are based on interviews of 10,952 Norwegian...     

Inferring patterns in the multi-week activity sequences of public transport users

The public transport networks of dense cities such as London serve passengers with widely different travel patterns. In line with the diverse lives of urban dwellers, activities and journeys are combined within days and across days in diverse sequences. From personalized customer information, to improved travel demand models, understanding this type of heterogeneity among transit users is relevant to a number of applications core to public transport agencies’ function. In this study, passenger heterogeneity is investigated based on a longitudinal representation of each user’s multi-week activity sequence derived from smart card data. We propose a methodology leveraging this representation to identify clusters of users with similar activity sequence structure. The methodology is applied to a large sample (n = 33,026) from London’s public transport network, in which each passenger is represented by a continuous 4-week activity sequence. The application reveals 11 clusters, each characterized by a distinct sequence structure. Socio-demographic information available for a small sample of users (n = 1973) is combined to smart card transactions to analyze associations between the identified patterns and demographic attributes including passenger age, occupation, household composition and income, and vehicle ownership. The analysis reveals that significant connections exist between the demographic attributes of users and activity patterns identified exclusively from fare transactions.     

Modelling users’ behaviour in inter-urban carsharing program: A stated preference approach

In this paper, the effects of a inter-urban carsharing program on users’ mode choice behaviour were investigated and modelled through specification, calibration and validation of different modelling approaches founded on the behavioural paradigm of the random utility theory. To this end, switching models conditional on the usually chosen transport mode, unconditional switching models and holding models were investigated and compared. The aim was threefold: (i) to analyse the feasibility of a inter-urban carsharing program; (ii) to investigate the main determinants of the choice behaviour; (iii) to compare different approaches (switching vs. holding; conditional vs. unconditional); (iv) to investigate different modelling solutions within the random utility framework (homoscedastic, heteroscedastic and cross-correlated closed-form solutions). The set of models was calibrated on a stated preferences survey carried out on users commuting within the metropolitan area of Salerno, in particular with regard to the home-to-work trips from/to Salerno (the capital city of the Salerno province) to/from the three main municipalities belonging to the metropolitan area of Salerno. All of the involved municipalities significantly interact each other, the average trip length is about 30 km a day and all are served by public transport. The proposed carsharing program was a one-way service, working alongside public transport, with the possibility of sharing the same car among different users, with free parking slots and free access to the existent restricted traffic areas. Results indicated that the inter-urban carsharing service may be a substitute of the car transport mode, but also it could be a complementary alternative to the transit system in those time periods in which the service is not guaranteed or efficient. Estimation results highlighted that the conditional switching approach is the most effective one, whereas travel monetary cost, access time to carsharing parking slots, gender, age, trip frequency, car availability and the type of trip (home-based) were the most significant attributes. Elasticity results showed that access time to the parking slots predominantly influences choice probability for bus and carpool users; change in carsharing travel costs mainly affects carpool users; change in travel costs of the usually chosen transport mode mainly affects car and carpool users.     

Time-dependent area-based pricing for multimodal systems with heterogeneous users in an agent-based environment

In this paper, we investigate an area-based pricing scheme for congested multimodal urban networks with the consideration of user heterogeneity. We propose a time-dependent pricing scheme where the tolls are iteratively adjusted through a Proportional–Integral type feedback controller, based on the level of vehicular traffic congestion and traveler’s behavioral adaptation to the cost of pricing. The level of congestion is described at the network level by a Macroscopic Fundamental Diagram, which has been recently applied to develop network-level traffic management strategies. Within this dynamic congestion pricing scheme, we differentiate two groups of users with respect to their value-of-time (which related to income levels). We then integrate incentives, such as improving public transport services or return part of the toll to some users, to motivate mode shift and increase the efficiency of pricing and to attain equitable savings for all users. A case study of a medium size network is carried out using an agent-based simulator. The developed pricing scheme demonstrates high efficiency in congestion reduction. Comparing to pricing schemes that utilize similar control mechanisms in literature which do not treat the adaptivity of users, the proposed pricing scheme shows higher flexibility in toll adjustment and a smooth behavioral stabilization in long-term operation. Significant differences in behavioral responses are found between the two user groups, highlighting the importance of equity treatment in the design of congestion pricing schemes. By integrating incentive programs for public transport using the collected toll revenue, more efficient pricing strategies can be developed where savings in travel time outweigh the cost of pricing, achieving substantial welfare gain.     

Mobile taxi booking application service’s continuance usage intention by users

The long-term development of a mobile booking taxi application service depends on the continued use of its passengers. The aim of this study is to investigate the determinants of the mobile taxi booking application service’s continuance intention, using the technology continuance theory by including the perceived risk and subjective norms. The data were collected by surveying 387 users of the mobile taxi application service. The data were analysed by applying the partial least squares technique. The analysis showed that the technology continuance theory has extensive power to explain the continuance intention to use the mobile booking taxi application. Subjective norms also have a significant effect on the attitude of mobile booking taxi application users which represents an important contribution to technology continuance theory extension. The theoretical and practical significances of the study have been discussed.     

Home charge timing choice behaviors of plug-in hybrid electric vehicle users under a dynamic electricity pricing scheme

This paper examines choice behaviors pertaining to the time at which users of plug-in hybrid electric vehicle with 24 km electric range charge their vehicles after arriving at home under a dynamic electricity pricing scheme. The following mutually exclusive alternatives are presented: no charging, charging immediately after arriving at home, charging at the cheapest time, and charging at other times. Four versions of a mixed logit model with unobserved heterogeneity are applied to panel data on vehicle usage from 9 households with 2226 observations in Toyota City. Estimation results suggest that users’ willingness to charge become stronger with increasing driving distance when the driving distance is less than the electric range of 24 km, while tend not to charge when the driving distance is longer than the electric range. Users who return home at the cheapest time or during the day are willing to charge immediately after arriving at home. Electricity prices significantly affect choices to charge at the cheapest time for all users, and stay-at-home mother users and users returning home in the evening tend to charge at the cheapest time. Users returning home in the evening also tend to charge at other times, and being accustomed to charge at a certain time increases the probability of charging at other times. In addition, considerable variations are found across individuals with respect to their preferences for charge timing alternatives as well as for electricity prices.     

Modelling shared space users via rule-based social force model

The promotion of space sharing in order to raise the quality of community living and safety of street surroundings is increasingly accepted feature of modern urban design. In this context, the development of a shared space simulation tool is essential in helping determine whether particular shared space schemes are suitable alternatives to traditional street layouts. A simulation tool that enables urban designers to visualise pedestrians and cars trajectories, extract flow and density relation in a new shared space design, achieve solutions for optimal design features before implementation, and help getting the design closer to the system optimal. This paper presents a three-layered microscopic mathematical model which is capable of representing the behaviour of pedestrians and vehicles in shared space layouts and it is implemented in a traffic simulation tool. The top layer calculates route maps based on static obstacles in the environment. It plans the shortest path towards agents’ respective destinations by generating one or more intermediate targets. In the second layer, the Social Force Model (SFM) is modified and extended for mixed traffic to produce feasible trajectories. Since car movements are not as flexible as pedestrian movements, velocity angle constraints are included for cars. The conflicts described in the third layer are resolved by rule-based constraints for shared space users. An optimisation algorithm is applied to determine the interaction parameters of the force-based model for shared space users using empirical data. This new three-layer microscopic model can be used to simulate shared space environments and assess, for example, new street designs.     

Charge timing choice behavior of battery electric vehicle users

This paper aims to examine choice behavior in respect of the time at which battery electric vehicle users charge their vehicles. The focus is on normal charging after the last trip of the day, and the alternatives presented are no charging, charging immediately after arrival, nighttime charging, and charging at other times. A mixed logit model with unobserved heterogeneity is applied to panel data extracted from a two-year field trial on battery electric vehicle usage in Japan. Estimation results, obtained using separate models for commercial and private vehicles, suggest that state of charge, interval in days before the next travel day, and vehicle-kilometers to be traveled on the next travel day are the main predictors for whether a user charges the vehicle or not, that the experience of fast charging negatively affects normal charging, and that users tend to charge during the nighttime in the latter half of the trial. On the other hand, the probability of normal charging after the last trip of a working day is increased for commercial vehicles, while is decreased for private vehicles. Commercial vehicles tend not to be charged when they arrival during the nighttime, while private vehicles tend to be charged immediately. Further, the correlations of nighttime charging with charging immediately and charging at other times reveal that it may be possible to encourage charging during off-peak hours to lessen the load on the electricity grid. This finding is supported by the high variance for the alternative of nighttime charging.     

Segmentation of paratransit users based on service quality and travel behaviour in Bandung,Indonesia

Using a data-set collected among paratransit users in Bandung, Indonesia, this paper explores the impacts of paratransit users' negative experiences and dissatisfactions with their paratransit usage pattern. Segmentation and ordered probit analyses are used to examine the impacts of users' opinions on service quality on their trip-making behaviour. The results indicate that users are divided into six segments – namely, the unlucky, the young user, the experienced, the adapter, the infrequent user and the captive. The results further indicate that paratransit users, especially women, perceive negative experiences related to on-time performance (departure and arrival time) and security issues related to vehicles. Despite these dissatisfactions and negative experiences, they are still likely to use paratransit as part of their daily life. Two paratransit market segments (the adapter and the captive) are also likely to result in more trips using paratransit. The study offers several strategies and recommendations that can improve the current paratransit system so that it can better serve local needs.     

Using AHP to measure the perception gap between current and potential users of bus services

Abstract

This study develops a multicriteria evaluation of user perception towards bus transit services and measures the gap in the perceptions held by current and potential users. A review of the transport quality literature indicates that both preference and satisfaction measures have been implemented to provide a comprehensive perception-based evaluation of bus quality. Although attempts have been made to evaluate user perception through a separate analysis of each (preference and/or satisfaction), the application of multicriteria quality measures are limited. A multicriteria quality measure not only offers more than just information on the daily experience of users but also knowledge of the internal process of quality evaluation (drivers/barriers). The multicriteria measure utilises the data of 512 questionnaires, whereby user perceptions were expressed through judgments of importance and satisfaction based on a set of 29 quality indicators classified into six attributes. Firstly, the study develops analytical hierarchy process (AHP) models to measure user preference. Secondly, a weighted perception index (WPI) of both preference and satisfaction is developed through a multicriteria model. Finally, multivariate analysis of variance (MANOVA) is conducted to identify the level of variation in the perception of both current and potential users towards bus service quality. The results show that although both current and potential users place a higher importance towards the same indicators, they do not share the same pattern of preferences (values and/or order). In addition, the study found that the interaction between preferences and satisfaction generated new patterns of subjective evaluation, and that these patterns vary significantly by user category.     

Heterogeneous hazard model of PEV users charging intervals: Analysis of four year charging transactions data

Public charging infrastructure represents a key success factor in the promotion of plug-in electric vehicles (PEV). Given that a large initial investment is required for the widespread adoption of PEV, many studies have addressed the location choice problem for charging infrastructure using a priori simple assumptions. Ideally, however, identifying optimal locations of charging stations necessitates an understanding of charging behavior. Limited market penetration of PEV makes it difficult to grasp any regularities in charging behavior. Using a Dutch data set about four-years of charging transactions, this study presents a detailed analysis of inter-charging times. Recognizing that PEV users may exhibit different charging behavior, this study estimates a latent class hazard duration model, which accommodates duration dependence, unobserved heterogeneity and the effects of time-varying covariates. PEV users are endogenously classified into regular and random users by treating charging regularity as a latent variable. The paper provides valuable insights into the dynamics of charging behavior at public charging stations, and which strategies can be successfully used to improve the performance of public charging infrastructure.