Innovative strategies for urban car-sharing systems and a simulator to assess their performance

In this paper, three innovative car-sharing systems for urban areas are proposed, based on fleets of individual intelligent vehicles with three service characteristics: instant access, open-ended reservations and one-way trips. These features provide high flexibility but create an uneven distribution of vehicles among stations. Therefore, relocation of vehicles must be performed. Three different system procedures are proposed: in the first system, relocations are performed by users; in the other two, vehicles relocate automatically, thanks to their automation. In the first two systems, vehicles are accessible only at stations, whereas in the third they are also accessible along roads. In order to provide transport managers with a tool to test systems in different realities, an object-oriented simulator is developed. The simulation provides outputs of system performance, in terms of user waiting times and system efficiency. The proposed systems are simulated for the city of Genoa, in Italy, and a comparative analysis is presented.     

Analysis of factors that may be essential in the decision to fly on fully autonomous passenger airliners

This research investigates factors that influence opinion in the decision to fly on fully autonomous passenger airliners primarily from the perspective of aviation and technology professionals. Bayesian statistical inference and a two‐level fractional factorial survey are used to sample passengers' views on fully autonomous airliners. Eight trust, safety, and cost factors are incorporated into a vignette set in the future. Factors include automation levels, safety records, liability guarantees, airline integrity, and service disruptions. Dependent variables exist in five post‐vignette questions and essentially ask “Would you” or “Would you not” be willing to fly on a fully autonomous airliner? Sixteen versions of the vignette, each with unique trust, safety, and cost levels, present varying (unknown) degrees of influence to the survey respondents. For every demographic, the research shows a 99% statistically significant difference between the “prior” and “posterior” sampled population proportions willing to fly. The most significant positive influence involves integrity characteristics of the airline, while the most negative influence relates to life insurance liability guarantees. Research from 2003 suggested that this mode of travel would be acceptable to only 10.5% of respondents. When the 2003 research is used as a Bayesian prior probability, the resulting posterior probability for the demographics sampled can be modeled as a beta distribution, indicating 95% probability that the sampled proportion of the population willing to fly is between 33.2% and 36.4%. After adjusting for age and profession demographics to match the US population, the 95% probability bounds on the proportion willing to fly are 31.35% and 34.15%. Copyright © 2015 John Wiley & Sons, Ltd.     

A new approach for improving the performance of freight train timetabling of a single-track railway system

A new approach for improving the performance of freight train timetabling for single-track railways is proposed. Using the idea of a fixed-block signaling system, we develop a matrix representation to express the occupation of inter- and intra-station tracks by trains illustrating the train blocking time diagram in its entirety. Train departure times, dwell times, and unnecessary stopping are adjusted to reduce average train travel time and single train travel time. Conflicts between successive stations and within stations are identified and solved. A fuzzy logic system is further used to adjust the range of train departure times and checks are made to determine whether dwell times and time intervals can be adjusted for passenger and freight trains at congested stations to minimize train waiting times. By combining manual scheduling expertise with the fuzzy inference method, timetable efficiency is significantly improved and becomes more flexible.     

Bush-based sensitivity analysis for approximating subnetwork diversion

Subnetwork analysis is often used in traffic assignment problems to reduce the size of the network being analyzed, with a corresponding decrease in computation time. This is particularly important in network design, second-best pricing, or other bilevel problems in which many equilibrium runs must be solved as a subproblem to a master optimization program. A fixed trip table based on an equilibrium path flow solution is often used, but this ignores important attraction and diversion effects as drivers (globally) change routes in response to (local) subnetwork changes. This paper presents an approach for replacing a regional network with a smaller one, containing all of the subnetwork, and zones. Artificial arcs are created to represent “all paths” between each origin and subnetwork boundary node, under the assumption that the set of equilibrium routes does not change. The primary contribution of the paper is a procedure for estimating a cost function on these artificial arcs, using derivatives of the equilibrium travel times between the end nodes to create a Taylor series. A bush-based representation allows rapid calculation of these derivatives. Two methods for calculating these derivatives are presented, one based on network transformations and resembling techniques used in the analysis of resistive circuits, and another based on iterated solution of a nested set of linear equations. These methods are applied to two networks, one small and artificial, and the other a regional network representing the Austin, Texas metropolitan area. These demonstrations show substantial improvement in accuracy as compared to using a fixed table, and demonstrate the efficiency of the proposed approach.     

A stochastic model of traffic flow: Theoretical foundations

In a variety of applications of traffic flow, including traffic simulation, real-time estimation and prediction, one requires a probabilistic model of traffic flow. The usual approach to constructing such models involves the addition of random noise terms to deterministic equations, which could lead to negative traffic densities and mean dynamics that are inconsistent with the original deterministic dynamics. This paper offers a new stochastic model of traffic flow that addresses these issues. The source of randomness in the proposed model is the uncertainty inherent in driver gap choice, which is represented by random state dependent vehicle time headways. A wide range of time headway distributions is allowed. From the random time headways, counting processes are defined, which represent cumulative flows across cell boundaries in a discrete space and continuous time conservation framework. We show that our construction implicitly ensures non-negativity of traffic densities and that the fluid limit of the stochastic model is consistent with cell transmission model (CTM) based deterministic dynamics.     

Estimation of origin-destination matrices from link counts and sporadic routing data

Estimation of origin-destination (OD) matrices from link count data is a challenging problem because of the highly indeterminate relationship between the observations and the latent route flows. Conversely, estimation is straightforward if we observe the path taken by each vehicle. We consider an intermediate problem of increasing practical importance, in which link count data is supplemented by routing information for a fraction of vehicles on the network. We develop a statistical model for these combined data sources and derive some tractable normal approximations thereof. We examine likelihood-based inference for these normal models under the assumption that the probability of vehicle tracking is known. We show that the likelihood theory can be non-standard because of boundary effects, and provide conditions under which such irregular behaviour will be observed in practice. For regular cases we outline connections with existing generalised least squares methods. We then consider estimation of OD matrices under estimated and/or misspecified models for the probability of vehicle tracking. Theoretical developments are complemented by simulation experiments and an illustrative example using a section of road network from the English city of Leicester.     

Understanding members' carsharing (activity) persistency by using econometric model

Carsharing is an innovative travel alternative that has recently experienced considerable growth and become part of sustainable transportation initiatives. Although carsharing is becoming increasingly a popular alternative transportation mode in North America, it is still an under‐researched area. Current research is aimed at better understanding of the behavior of carsharing users. For every member, a two‐stage approach microsimulates the probability of being active in any month using a binary probit model and given that a particular member is active during a month, the probability of that member using the service multiple times using a random utility‐based model. The model is estimated using empirical data from one of the largest carsharing companies in North America. The model estimates reveal that the activity persistency of members is positively linked to previous behaviors for up to 4 months, and that the influence of previous months weakens over time. It also shows that some attributes of the traveler (gender, age, and language spoken at home) impact his or her behaviors. Copyright © 2010 John Wiley & Sons, Ltd.     

Ridership drivers of bus rapid transit systems

We have collected information on 46 bus rapid transit (BRT) systems throughout the world to investigate the potential patronage drivers. From a large number of candidate explanatory variables (quantitative and qualitative), 11 sources of systematic variation are identified which have a statistically significant impact on daily passenger-trip numbers. These sources are fare, headway, the length of the BRT network, the number of corridors, average distance between stations; whether there is: an integrated network of routes and corridors, modal integration at BRT stations, pre-board fare collection and fare verification, quality control oversight from an independent agency, at-level boarding and alighting, as well as the location of BRT. The findings of this paper offer important insights into features of BRT systems that are positive contributors to growing patronage and hence should be taken into account in designing and planning BRT systems.     

Review and meta-analysis of U.K. time elasticities of travel demand

In contrast with reviews of values of time and price elasticities, the literature contains little by way of detailed reviews of travel time based choice and demand elasticities. This paper reports the most extensive meta-analysis of time-based demand elasticities yet undertaken, supplemented with a review of literature not previously in the public domain. The meta-analysis is based upon 427 direct elasticities covering travel time, generalised journey time (GJT) and service headway and drawn from 69 UK studies. The elasticities are found to vary, as expected, across attributes, and quite strong effects have been detected according to distance. We provide interesting insights into the relationship between long and short run elasticities and elasticities obtained from static models and choice models based on actual and hypothetical preferences. Significantly, the results seem to indicate that the duration for the long run demand impact to work through depends upon the periodicity of the model estimated. There is little variation apparent by journey purpose, source of the evidence, nor over time or by region/flow type, whilst travel time elasticities for high speed rail are not materially different from conventional contexts. The findings support some official elasticity recommendations and conventions but challenge others, and can be used to provide time-based elasticities where none exist or to assess new empirical evidence.     

Interactive stated choice surveys: a study of air travel behaviour

Stated preference (SP) experiments are becoming an increasingly popular survey methodology for investigating travel behaviour. Nevertheless, some evidence suggests that SP experiments do not mirror decisions in real markets. With an increasing number of real world decisions made using the internet, an opportunity exists to improve the realism of the SP counterparts of such choices by aligning the choice environment with such online portals. In this paper, we illustrate the benefits of such an approach in the context of air travel surveys. Our survey is modelled on the interface and functionality of an online travel agent (OTA). As with a real OTA, many ticket options are presented. Sort tools allow the options to be reordered, search tools allow options to be removed from consideration, and a further tool allows attributes to be hidden and shown. Extensive use of these tools is made by the 462 respondents. A traditional SP component was also completed by the respondents. Our exploratory analysis as well as random utility model estimation results confirm not only that respondents seem to engage more actively with the interactive survey, but also that the resulting data allows for better performance in model estimation compared to a more conventional SP experiment. These results have implications for the study of other complex travel choices where interactive surveys may similarly be preferable to standard approaches.