Springer Science and Business Media LLC

The need for realistic route choice models has become essential in light of the on going research in the IVHS (Intelligent Vehicle Highway Systems) area, where drivers are required to incorporate verbal, visual and prescriptive information into their own perceptions while making route choices. We present a modeling framework for route choice in the presence of information based on concepts from fuzzy set theory, approximate reasoning and fuzzy control. We use fuzzy sets to model perceptions of network attributes, and traffic information provided by an information system. Rules of the form: “if ... then ...” are used to model the decision process, and to describe attitudes towards taking a specific route given (possibly vague) perceptions on network attributes. The rules are used as anchoring schemes for decisions, while the adjustment of the rules to changing conditions is done by an approximate reasoning mechanism. The suggested approach provides a route choice model in which the final choice is a combination of various considerations each of which captures a certain aspect of the final decision in a non-linear fashion. We demonstrate the methodology through a small example and discuss calibration issues and implementation difficulties.

Studies have applied single-reference-point or safety margin hypotheses to examine how advanced traveler information affects travel behaviors. However, these theories may fail to fully capture the trade-offs among origin departure time, airport access time, and terminal processing time in terms of airport ground access behaviors. In this study, we developed a tri-reference-point hypothesis and assumed that the rate of change of utility may change at the air passenger’s preferred (PAT), earliest acceptable (EAT), and latest acceptable (LAT) airport arrival times. With an empirical data set collected from 304 passengers at Taipei Songshan Airport, the study examined the tri-reference-point hypothesis by analyzing airport ground access mode choice behaviors with a pooled framework that combined revealed and stated preferences. Moreover, the study developed four alternative specifications for schedule delay variables, assuming that air passengers used different reference points to determine relative gains and losses of the expected airport arrival time. The specifications included selecting both EAT and LAT as the zero-utility points (an indifference-band specification) and either one of PAT, EAT, and LAT as the single zero-utility point. Regardless of which specification was employed for schedule delay variables, the tri-reference-point hypothesis was generally supported. In particular, a significant difference of the rate of change of utility around PAT, EAT, and LAT was identified in the analysis results. When managing increasing road travel times and increasingly congested terminals, air passengers were more willing to retime their origin departure time to an earlier time than to switch their ground access mode. The implications of the analysis results for airport ground access management are discussed in the study.

Young people appear to be using public transit more than their predecessors, reversing twentieth century trends, but the importance of such findings depends on whether high transit use persists as these riders age. This paper examines whether transit mode share for commuting trips is increasing; socio-economic and geographic trends are also explored to attempt to determine whether these trends are likely to continue. The study uses repeated cross-sectional origin–destination surveys of Greater Montreal (1998, 2003 and 2008). Over 45,000 home-to-work and home-to-school trips are studied for each survey year. A general lifecycle pattern of decreasing transit share with age is apparent within cohorts until individuals reach their early 30s, followed by decades of stability. This pattern appears to hold in recent years, but with higher youth use rates, and it is argued that the higher use will continue as current younger cohorts mature. Suburbanization by those in their early 30s is evident and, along with household composition changes, appears to explain much of the final within-cohort mode share declines before equilibrium. Transit providers might see lasting ridership gains, as those currently in their early 30s and younger replace lower-use cohorts in the workforce, provided service provision keeps pace. Addressing the needs of young people, whose mode choices are comparatively unsettled, should be a priority for transit agencies to ensure higher transit usage in the future.

The automatic license plate recognition (LPR) system has the advantages of strong continuity, high data accuracy, and large detection samples. The detection data can be used as quasi and full sample sampling of road network vehicles. However, the system has the disadvantage of sparse geographical location, so the data is difficult to be used effectively. In order to obtain the full sample vehicle travel trajectory on an urban road network, this paper investigates the sparse trajectory recovery problem based on LPR data. A trajectory reconstruction algorithm based on the Markov decision process (MDP) in road network space is proposed. The algorithm is divided into two stages, including off-line training and on-line prediction. In the off-line training stage, the LPR data is transformed into the trajectory set represented by the link edge sequence in the road network space. The MDP model is used to describe the vehicle driving behavior, and the design rules of the link reward function in the model are discussed. An unsupervised Bayesian inverse reinforcement learning algorithm is proposed to train the historical vehicle trajectory data and learn the model parameters. In the online prediction stage, the transfer probability between links is calculated according to the trained model. The negative logarithm of the transfer probability modified by the spatio-temporal coefficient is used as the edge weight to construct a directed graph. The shortest path search is used to obtain the path with the highest probability to restore the missing path. The proposed method is implemented on a realistic urban traffic network in Ningbo, China. The comparison with the baseline algorithms indicates that the proposed method has higher accuracy, especially when the coverage rate of the LPR device is low. When the coverage rate is more than 60%, the comprehensive accuracy of the proposed algorithm is more than 85%, and reliable path estimation results can be obtained.

A range of factors, including improvements in battery and motor technology coupled with innovative industrial design, are contributing to the emergence of electric bicycles (E-bikes) with greater range and enhanced performance. This paper examines this emerging vehicle type within the context of sustainable transport. Mobility, safety and environmental impacts are considered. While governments could employ a range of policy instruments to respond to the opportunities and threats presented by these vehicles, the primary focus internationally is on vehicle standards. A review of regulations in different countries highlights little consistency in the parameters used to regulate E-bikes. Unresolved issues are identified to guide future research on this vehicle type.

The example of Singapore shows that rapid urban and economic growth does not have to bring traffic congestion and pollution. Singapore has chosen to restrain car traffic demand due to its limited land supply. Transport policy based on balanced development of road and transit infrastructure and restraint of traffic has been consistently implemented for the past 30 years. Combined with land use planning, it resulted in a modern transport system, which is free from major congestion and provides users with different travel alternatives. As the economic growth caused a substantial increase in demand for cars, several pricing policies were introduced with the aim of restraining car ownership and usage. Growth of the vehicle population is now controlled and potentially congested roads are subject to road pricing. These measures help to keep the roads free from major congestion, maintain car share of work trips below 25% and keep the transport energy usage low. Although Singapore conditions are in many aspects unique, its travel demand experience can provide useful lessons for other rapidly growing cities in Asia.