Steering short-term demand for car-sharing: a mode choice and policy impact analysis by trip distance

Transportation - Car-sharing could have substantial benefits. However, there is not enough evidence about if more people choosing car-sharing would reduce private car usage or public transport...     

A bi-objective cyclist route choice model

It is widely acknowledged that cyclists choose their route differently to drivers of private vehicles. The route choice decision of commuter drivers is often modelled with one objective, to reduce their generalised travel cost, which is a monetary value representing the combined travel time and vehicle operating cost. Commuter cyclists, on the other hand, usually have multiple incommensurable objectives when choosing their route: the travel time and the suitability of a route. By suitability we mean non-subjective factors that characterise the suitability of a route for cycling, including safety, traffic volumes, traffic speeds, presence of bicycle lanes, whether the terrain is flat or hilly, etc. While these incommensurable objectives are difficult to be combined into a single objective, it is also important to take into account that each individual cyclist may prioritise differently between travel time and suitability when they choose a route.This paper proposes a novel model to determine the route choice set of commuter cyclists by formulating a bi-objective routing problem. The two objectives considered are travel time and suitability of a route for cycling. Rather than determining a single route for a cyclist, we determine a choice set of optimal alternative routes (efficient routes) from which a cyclist may select one according to their personal preference depending on their perception of travel time versus other route choice criteria considered in the suitability index. This method is then implemented in a case study in Auckland, New Zealand.The study provides a starting point for the trip assignment of cyclists, and with further research, the bi-objective routing model developed can be applied to create a complete travel demand forecast model for cycle trips. We also suggest the application of the developed methodology as an algorithm in an interactive route finder to suggest efficient route choices at different levels of suitability to cyclists and potential cyclists.     

A tour-based model of travel mode choice

This paper presents a new tour-based mode choice model. The model is agent-based: both households and individuals are modelled within an object-oriented, microsimulation framework. The model is household-based in that inter-personal household constraints on vehicle usage are modelled, and the auto passenger mode is modelled as a joint decision between the driver and the passenger(s) to ride-share. Decisions are modelled using a random utility framework. Utility signals are used to communicate preferences among the agents and to make trade-offs among competing demands. Each person is assumed to choose the best combination of modes available to execute each tour, subject to auto availability constraints that are determined at the household level. The households allocations of resources (i.e., cars to drivers and drivers to ride-sharing passengers) are based on maximizing overall household utility, subject to current household resource levels. The model is activity-based: it is designed for integration within a household-based activity scheduling microsimulator. The model is both chain-based and trip-based. It is trip-based in that the ultimate output of the model is a chosen, feasible travel mode for each trip in the simulation. These trip modes are, however, determined through a chain-based analysis. A key organizing principle in the model is that if a car is to be used on a tour, it must be used for the entire chain, since the car must be returned home at the end of the tour. No such constraint, however, exists with respect to other modes such as walk and transit. The paper presents the full conceptual model and estimation results for an initial empirical prototype. Because of the complex nature of the model decision structure, choice probabilities are simulated from direct generation of random utilities rather than through an analytical probability expression.     

A model and algorithm for multicriteria route-mode choice

Using an idea proposed independently by Quandt and Schneider, the paper declares mode choice to be a special instance of route choice. It describes a (non-logit) model which includes in its route-choice mechanism the decision variables traditionally associated with mode choice. With the assumption that each traveller selects the route which minimizes his own personal linear choice function, it is clear that the routes with a nonzero chance of being picked are only those not dominated by any other path (e.g. are not both costlier and longer than any other path). The precise probability of a route being chosen is just the integral over the appropriate portion of the probability density of the coefficients of the choice function. The integration limits are implied by the amount of each disutility on each of the undominated routes. An algorithm is given which is quite efficient in finding these paths in a large and complex multimodal network.     

A non-compensatory choice model incorporating attribute cutoffs

This research proposes an extension to the traditional compensatory utility maximization framework which has guided most theoretical and statistical work in choice modeling applications, including those in transportation demand estimation work. Attribute cutoffs are incorporated into the decision problem formulation; it is then argued on extant empirical evidence that individuals may view these constraints as “soft”. This leads to the formulation of a penalized utility function that allows for constraint violation, but at a cost to the overall evaluation of the good. The proposed model is able to represent fully compensatory, conjunctive and disjunctive choice strategies, as well as combinations thereof. The properties of the proposed theoretical model are examined and discussed. From the theoretical framework, statistical models of choice behavior are easily derived; in their simplest forms, these models can be estimated using existing software. A Stated Preference choice experiment is analyzed using the proposed model, which is found to be highly consistent with observed choices and superior to a structural two-stage choice set formation model.     

A Stated preference freight mode choice model

Transport policy aims to assist the transport system to work more efficiently and effectively. An understanding of the reasons why people choose to move freight in a certain manner is critical to the development of appropriate policies. This article outlines a data collection approach and the development of a disaggregate mode choice model applicable to the analysis of freight shipper decision making. It focuses on the choice between rail and road in Java, Indonesia. The model indicates that safety, reliability and responsiveness are major attributes influencing rail/road freight mode choice. Transport policies aimed at improving these dimensions should increase the attractiveness of rail transport.     

Intercity rail services: A nested logit stated choice analysis of pricing options

There is a renewed interest in intercity and long-distance rail services in many countries, with both new high-speed rail services and improvements to conventional rail under review. The current study reports on an investigation using a stated choice experiment, of the demand for sleeper services between Sydney, Northern New South Wales (NSW) and Brisbane in Australia, a 12 to 14 hour trip, just after a decision by the NSW government to temporarily suspend sleeper services and introduce seating service only, pending an inquiry into the demand for such loss-making services under alternative price and service levels. A matrix of direct fare elasticities within the rail mode and between rail and competing modes are obtained for concession and non-concession travellers from a nested logit model. The empirical evidence extends our knowledge of the sensitivity of the long distance passenger market to a range of rails fares, distinguishing between classes of fares and levels of service.     

A simultaneous destination and mode choice model for shopping trips

This paper describes a disaggregate simultaneous destination and mode choice model for shopping trips. Following an introduction to the model structure and a review of the data, the results of five different model specifications are discussed. The models were estimated using data from two communities adjacent to Eindhoven, the Netherlands and utilise the multinomial logit model.     

A dichotomous choice survey for quantifying option and non-use values of bus services in Korea

The total economic value for a transportation service consists of use, option, and non-use value. The use benefit is based on a traveler’s willingness to pay for usual consumption of the service. The optional value, on the other hand, is related to the possible use of the service for trips not yet anticipated or currently accommodated by other travel modes. The non-use value, however, is derived from the intrinsic merit of the service, even though a trip-maker never actually or potentially depends on the mode. A closed-ended contingent valuation method is considered for the quantification of the option and non-use values. A survey of single- and double-bounded dichotomous choices is conducted with a case study of South Korean bus operations. A logistic regression model and a survival analysis for the single- and double-bounded approaches, respectively, are applied. The estimation result is examined according to the statistical property required and the behavioral validity expected. In particular, three issues from the output are discussed. First, the results help to show the preferable framework between single- and double-bounded surveys for addressing an individual’s option and non-use values. Second, the differences in the absolute values of option and non-use values are compared. Thirdly, the relationship between trip-makers’ willingness to pay and the level of service of their primary travel modes are investigated. In conclusion, the summary of research and the possibilities for future studies are given.     

Route choice and the value of commuting time: An economic model of dichotomous choice

This paper presents an economic model of generalized travel cost and provides an empirical study of the parameters of the cost function. The route-choice model that is estimated combines McFadden's theory of qualitative choice behavior with a function for the value of travel time in which total trip time and the income level are assumed to influence the marginal value of time. The empirical results indicate that, for a sample of commuters in the Chicago metropolitan area in 1972, the value of time is a positive function of total trip time, but is not a function of income.     

Characteristics of premium transit services that affect mode choice

This research seeks to improve the understanding of the full range of determinants for mode choice behavior and to offer practical solutions to practitioners on representing and distinguishing these characteristics in travel demand forecasting models. The principal findings were that the representation of awareness of transit services is significantly different than the underlying assumption of mode choice and forecasting models that there is perfect awareness and consideration of all modes. Furthermore, inclusion of non-traditional transit attributes and attitudes can improve mode choice models and reduce bias constants. Additional methods and analyses are necessary to bring these results into practice. The work is being conducted in two phases. This paper documents the results of Phase I, which included data collection for one case study city (Salt Lake City), research and analysis of non-traditional transit attributes in mode choice models, awareness of transit services, and recommendations for bringing these analyses into practice. Phase II will include data collection for two additional case study cities (Chicago and Charlotte) with minor modifications based on limitations identified in Phase I, additional analyses where Phase I results indicated a need, and a demonstration of the research in practice for at least one case study city.     

A flexible model structure approach for discrete choice models

Multi-dimensional discrete choice problems are usually estimated by assuming a single-choice hierarchical order for the entire study population or for pre-defined segments representing the behavior of an “average” person and by indicating either limited differences or a variety in choices among the study population. This study develops an integral methodological framework, termed the flexible model structure (FMS), which enhances the application of the discrete choice model by developing an optimization algorithm that segment given data and searches for the best model structure for each segment simultaneously. The approach is demonstrated here through three models that conceptualize the multi-dimensional discrete choice problem. The first two are Nested Logit models with a two-choice dimension of destination and mode; they represent the estimation of a fixed-structure model using pre-segmented data as is mostly common in multi-dimensional discrete choice model implementation. The third model, the FMS, includes a fuzzy segmentation method with weighted variables, as well as a combination of more than one model structure estimated simultaneously. The FMS model significantly improves estimation results, using fewer variables than do segmented NL models, thus supporting the hypothesis that different model structures may best describe the behavior of different groups of people in multi-dimensional choice models. The implementation of FMS involves presenting the travel behavior of an individual as a mix of travel behaviors represented by a number of segments. The choice model for each segment comprises a combination of different choice model structures. The FMS model thus breaks the consensus that an individual belongs to only one segment and that a segment can take only one structure.     

A utility-based bicycle speed choice model with time and energy factors

Transportation - This paper presents a utility-based behavioral model of bicycle speed choice. A mathematical framework is developed with travel time, energy expenditure, and control factors....     

Dynamic model of activity-type choice and scheduling

This paper presents a model for the choice of activity-type and timing, incorporating the dynamics of scheduling, estimated on a six-week travel diary. The main focus of the study is the inclusion of past history of activity involvement and its influence on current activity choice. The econometric formulation adopted, explicitly accounts both for correlation across alternatives and for state dependency. The results indicate that behavioral variables are superior to socio-economic variables and that consideration of the correlation pattern over alternatives clearly improves the fit of the model. This is a first but significant contribution to changing the current static demand models into dynamic activity based ones. The availability of other multi-week travel surveys and the progress made recently on advanced econometric techniques should encourage the transferability of this study to different regions or model scale.     

Future use of stage bus services

The reasons underlying the decline of stage bus services in the U.K. over the past 30 years seem to be well understood, and the probable future trends have been projected using a quantitative forecasting model. The model considers U.K. bus services at a very aggregate level, but it breaks the demand into specific user groups: work trips, children's travel, travel by the elderly, and all other travel, and separately for households with and without a private car. Forecasts depend very sensitively on the level of economic growth assumed, since this governs the two major factors which determine public transport use — car ownership and the cost of operating the services. If the economy could recover its historic growth rates, a further substantial decline in bus use seems inevitable under most realistic assumptions. However, with the present economic outlook, a lower growth rate seems likely to persist for some time, and in this case public transport use will become much more stable in the 1990's; a tendency which would be helped if there were large increases in fuel prices. Many of the Metropolitan Counties have adopted policies of strongly restraining future rises in fares, in some cases to the extent of freezing fares in monetary terms. The effects of such policies on both patronage and subsidies are considered here, and although much of the current political attention is focussed on controlling fares, the question of balance between fares and service levels is also discussed. Lastly, it must be admitted that these predictions are based on knowledge which is largely restricted to the short-term effects of transport policies. The nature of our uncertainty about longer-term effects, and the possible size of them, is considered in terms of sensitivity-testing of the prediction model.     

A mixed logit model for predicting exit choice during building evacuations

Knowledge on human behaviour in emergency is crucial to increase the safety of buildings and transportation systems. Decision making during evacuations implies different choices, of which one of the most important concerns is the escape route. The choice of a route may involve local decisions on alternative exits from an enclosed environment. This study investigates the effect of environmental (presence of smoke, emergency lighting and distance of exit) and social factors (interaction with evacuees close to the exits and with those near the decision-maker) on local exit choice. This goal is pursued using an online stated preference survey carried out making use of non-immersive virtual reality. A sample of 1503 participants is obtained and a mixed logit model is calibrated using these data. The model shows that the presence of smoke, emergency lighting, distance of exit, number of evacuees near the exits and the decision-maker and flow of evacuees through the exits significantly affect local exit choice. Moreover, the model indicates that decision making is affected by a high degree of behavioural uncertainty. Our findings support the improvement of evacuation models and the accuracy of their results, which can assist in designing and managing building and transportation systems. The main aim of this study is to enrich the understanding of how local exit choices are made and how behavioural uncertainty affects these choices.     

Development and validation of a direct mode choice model

A direct discrete mode choice model is introduced using relative attributes of competing modes as well as socioeconomic characteristics of travelers. The model is calibrated and validated for two available historic databases in the Dallas–Fort Worth region. The validation is conducted against the outputs of a current nested logit model used by the regional planning organization as well as the observed values based on transit ridership surveys for a newly inaugurated commuter rail service. The calibrated model is applied after the introduction of this new transit mode. The results show that the estimated mode shares by the proposed model have a statistically better consistency with the observed values than the estimates of the conventional nested logit model. Unlike the logit model, the structure of the direct model based on relative attributes also has the advantage of not needing recalibration each time a new travel mode is introduced. The model is found to be easier to calibrate and produces more accurate results than the nested logit model, commonly used by many metropolitan planning organizations.     

A latent class joint mode and departure time choice model for the Greater Toronto and Hamilton Area

This paper presents a closed-form Latent Class Model (LCM) of joint mode and departure time choices. The proposed LCM offers compound substitution patterns between the two choices. The class-specific choice models are of two opposing nesting structures, each of which provides expected maximum utility feedback to the corresponding class membership model. Such feedback allows switching class membership in response to the changes in choice contexts. The model is used for an empirical investigation of commuting mode and departure time choices in the Greater Toronto and Hamilton Area (GTHA) by using a large sample household travel survey dataset. The empirical model reveals that overall 38% of the commuters in the GTHA are more likely to switch modes than departure times and 62% of them are more likely to do the reverse. The empirical model also reveals that the average Subjective Value of Travel Time Savings (SVTTS) of the commuters in the GTHA can be as low as 3 dollars if a single choice pattern of departure time choices nested within mode choices is considered. It can also be as high as 67 dollars if the opposite nesting structure is assumed. However, the LCM estimates the average SVTTS to be around 27 dollars in the GTHA. An empirical scenario analysis by using the estimated model indicates that a 50% increase in morning peak period car travel time does not sway more than 4% of commuters from the morning peak period.

     

Effects of perceived safety,involvement and perceived service quality on loyalty intention among ride-sourcing passengers

Transportation - Ride-sourcing services are increasingly popular since they were first introduced in the last decade. Particularly in developing countries where public transport systems have...