An alternative formulation of the simultaneous route and departure-time choice equilibrium problem

Traditional (static) network equilibrium models have always been formulated in a route-based fashion rather than a vehicle-based fashion. That is, the decision variables have been the number of vehicles using each route rather than the route choices of each vehicle. Given the success of this approach, it is not surprising that recent “dynamic” network equilibrium models have been formulated in a similar way. That is, the decision variables in these models are usually the route-specific departure rates over time. In this paper, we develop a vehicle-based equilibrium model of simultaneous route and departure-time choice and discuss the possible advantages of this approach. We then describe a heuristic for solving this model and demonstrate its effectiveness on several small examples.     

The effectiveness of differential pricing on route choice

The use of differential pricing as a means of traffic management has been advocated by specialists in the field of transport for quite some time. Because of technical and political reasons, a full-scale pricing scheme for the use of road space has yet to be introduced. Applying the principle to a highly automatic rail system, however, is technologically much more feasible. The Mass Transit Railway Corporation of Hong Kong has implemented a so-called revenue neutral peal pricing policy after the completion of a second cross-harbour route- the East Harbour Crossing — in May, 1990. Passengers travelling from Kowloon to the central business district (including Jordon and Tsim Sha Tsui on the Kowloon side and stations from Sheung Wan to Causeway Bay on the Island side) during the morning peak hour are confronted with the following choice: either (i) make use of the Nathan Road Corridor and pay 80 cents on top of normal face; or (ii) take the less congested but in general longer route via the East Harbour Crossing and get a 80 cents discount. The present paper attempts to analyse the effectiveness of this differential pricing policy in diverting passengers from the overcrowded section to the less heavily utilized route. A personal interview survey comprising a total of 1094 successful cases was conducted for this purpose. The logit regression model was employed to analyse the route choice. It is found that income, habit and journey time are the most important variables determining the route choice. The effect of cost or fare difference, although large in terms of magnitude, is only marginally significant in the statistical sense. It is suggested that efforts to change the passengers' habit and measures to shorten the train transfer time at the Quarry Bay Station for the East harbour Crossing users would be more effective in achieving this end. This is especially the case given the current political development in Hong King which renders further enlargement of the price difference a highly difficult proposition.     

Validating the results of a route choice simulator

This paper describes the validation of a route choice simulator known as VLADIMIR (Variable Legend Assessment Device for Interactive Measurement of Individual Route choice). VLADIMIR is an interactive computer-based tool designed to study drivers’ route choice behaviour. It has been extensively used to obtain data on route choice in the presence of information sources such as Variable Message Signs or In-Car Navigation devices. The simulator uses a sequence of digitized photographs to portray a real network with junctions, links, landmarks and road signs. Subject drivers are invited to make journeys between specified origins and destinations under a range of travel scenarios, during which the simulator automatically records their route choices. This paper describes validation experiments carried out during the period Summer 1994 to Autumn 1995 and reports on the results obtained. Each experiment involved a comparison of routes selected in real life with those driven under simulated conditions in VLADIMIR. The analysis included investigation of the subjects’ own assessment of the realism of the VLADIMIR routes they had chosen, a comparison of models based on the real life routes with models based on VLADIMIR routes, and a statistical comparison of the two sets of routes. After an extensive series of data collection exercises and analyses, we have concluded that a well designed simulator is able to replicate real life route choices with a very high degree of detail and accuracy. Not only was VLADIMIR able to precisely replicate the route choices of drivers who were familiar with the network but it also appears capable of representing the kind of errors made and route choice strategies adopted by less familiar drivers. Furthermore, evidence is presented to suggest that it can accurately replicate route choice responses to roadside VMS information.     

Economic resilience to transportation failure: a computable general equilibrium analysis

This study develops and applies a multimodal computable general equilibrium (CGE) framework to investigate the role of resilience in the economic consequences of transportation system failures. Vulnerability and economic resilience of different modes of transportation infrastructure, including air, road, rail, water and local transit, are assessed using a CGE model that incorporates various resilience tactics including modal substitution, trip conservation, excess capacity, relocation/rerouting, and service recapture. The linkages between accessibility, vulnerability, and resilience are analyzed. The model is applied to the transportation system failures in the aftermath of Hurricane Katrina to illustrate its capabilities. The analytical framework, however, has broader applications and can provide insights for resource allocations to enhance emergent responses to unexpected events and to improve resilient design of transportation infrastructure systems.     

Analysis of factors affecting the choice of route of pedestrians

Pedestrians as compared to vehicular traffic enjoy a high degree freedom of movement even in heavily congested areas. Consequently, there are more alternative links available to pedestrians between a given origin‐destination (O‐D) pair. This paper describes a study done by the University of Calgary to evaluate the factors affecting the choice of route on intra‐CBD trips or trips within the Central Business District (CBD).

An origin destination survey conducted in downtown Calgary, Alberta enabled the identification of the most significant factors influencing the choice. These factors were analyzed in relation to the physical characteristics of the location, personal characteristics of the trip maker and the type of the trip.

It appears that most people chose the shortest link and factors such as the level of congestion, safety or visual attractions were only secondary. This suggests that the length should be made a major consideration when planning and designing pedestrian links.     

Control of drivers' route choice: Pipe dream or panacea?

In most large cities traffic flow is controlled or manipulated in a number of ways. The methods used are mostly negative in the sense that they restrict the driver's choice of alternative routes rather than encourage him to use a particular one. This paper reviews some of the conventional measures and goes on to consider whether a more positive approach to route control might be justified, by inducing a more efficient or acceptable pattern of traffic movement in urban areas. The principal criteria for an efficient pattern are taken to be the total rate of expenditure of vehicle mileage and the frequency of route crossings, and an attempt is made to evaluate the potential benefits of route control in these terms. Social, technical and political considerations suggest that compulsory control will not be feasible for some time (at least, in the UK), but if the benefits to drivers as individuals can be shown to be worthwhile an advisory system might be practicable. Some possible systems are briefly outlined.The author is grateful to the City Engineer of Westminster City Council, Mr A.J. Cryer, for permission to publish this paper,which, however, does not necessarily represent the views . City Council. The author is greatly indebted to E. M. Holroyd for numerous suggestions and advice.     

Consumer preferences relative to the price and network capability of small urban vehicles

Preferences of consumers for small urban vehicle concepts differing only with respect to their hypothetical purchase prices and network capabilities (i.e., whether they are capable of operating on expressways, major arterials or local streets) are analyzed using statistical techniques based on psychological scaling theories. Results from these analyses indicate that a vast majority of consumers are not readily willing to give up the accessibility provided by conventional automobiles. More specifically, over the range of hypothetical prices considered here, network capability dominates as a determinant of preferences for vehicle concepts. Also, the ability to operate vehicles on expressways is of utmost importance to consumers.     

The dynamics of fare and frequency choice in urban transit

This paper investigates the choice of fare and service frequency by urban mass transit agencies. A more frequent service is costly to provide but is valued by riders due to shorter waiting times at stops, and faster operating speeds on less crowding vehicles. Empirical analyses in the 1980s found that service frequencies were too high in most of the cities studied. For a given budget constraint, social welfare could be improved by reducing service frequencies and using the money saved to lower fares. The cross-sectional nature of these analyses meant that researchers were unable to address the question of when the oversupply occurred. This paper seeks to answer that question by conducting a time-series analysis of the bus operations of the Chicago Transit Authority from 1953 to 2005. The paper finds that it has always been the case that too much service frequency was provided at too high a fare. The imbalance between fares and service frequency became larger in the 1970s when the introduction of operating subsidies coincided with an increase in the unit cost of service provision.     

Modeling the impact of pre-trip information on commuter departure time and route choice

The objective of this paper is to investigate the impact of pre-trip information on auto commuters’ choice behavior. The analysis is based on an extensive home-interview survey of commuters in the Taichung metropolitan area in Taiwan. A joint model for route and departure time decisions with and without pre-trip information is formulated. The model specifications are developed for both the systematic and random components. In particular, econometric issues associated with specifying the random error structure are addressed for parameter estimation purposes. Insights into the effects of attributes are obtained through the analysis of the model's performance and estimated parameter values. A probit model form is used for the joint model, allowing the introduction of state dependence and correlation in the model specification. The results underscore the important relationship between the different characteristics and the propensity of commuter choice behavior under two scenarios, with and without pre-trip information.     

Preliminary analysis on dynamic route choice behavior: Using probe‐vehicle data

Dynamic traffic assignment models have been attracting increasing attention with the progress of traffic management policies based on information technology. These dynamic estimation tools, however, just apply static route choice models either at only origin node or at every arrival node. This paper aims at providing some knowledge on drivers' dynamic route choice behavior using probe‐vehicle data. The results of analyses show that route choice behavior relates to the distance from driver's position to the destination and that dynamic route choice behavior is modeled better by considering decision process during the trip.     

An agent-based approach to modelling driver route choice behaviour under the influence of real-time information

This paper presents an agent-based approach to modelling individual driver behaviour under the influence of real-time traffic information. The driver behaviour models developed in this study are based on a behavioural survey of drivers which was conducted on a congested commuting corridor in Brisbane, Australia. Commuters’ responses to travel information were analysed and a number of discrete choice models were developed to determine the factors influencing drivers’ behaviour and their propensity to change route and adjust travel patterns. Based on the results obtained from the behavioural survey, the agent behaviour parameters which define driver characteristics, knowledge and preferences were identified and their values determined. A case study implementing a simple agent-based route choice decision model within a microscopic traffic simulation tool is also presented. Driver-vehicle units (DVUs) were modelled as autonomous software components that can each be assigned a set of goals to achieve and a database of knowledge comprising certain beliefs, intentions and preferences concerning the driving task. Each DVU provided route choice decision-making capabilities, based on perception of its environment, that were similar to the described intentions of the driver it represented. The case study clearly demonstrated the feasibility of the approach and the potential to develop more complex driver behavioural dynamics based on the belief–desire–intention agent architecture.     

Context-dependent influence of road attributes and pricing policies on route choice behavior of truck drivers: results of a conjoint choice experiment

In this paper, we report the results of a stated choice experiment, which was conducted to examine truck drivers?? route choice behavior. Of particular interest are the questions (i) what is the relative importance of road accessibility considerations via-a-vis traditional factors influencing route choice behavior, (ii) what are the influences of particular personal and situational variables on the evaluation of route attributes, (iii) how sensitive are truck drivers for possible pricing policies, and (iv) is there a difference in impact if environmental concerns are framed as a bonus or as a pricing instrument. The main findings indicate that road accessibility characteristics have a substantial impact on route preferences which is of the same order of magnitude as variation in travel times. This suggests that provision of adequate travel information in itself can be an effective instrument to prevent negative externalities of good transport associated with shortest routes. Furthermore, the results indicate that truck drivers/route planners when choosing a route are relatively sensitive to road pricing schemes and rather insensitive to environmental bonuses.     

Expanding the applicability of random regret minimization for route choice analysis

The discrete choice paradigm of random regret minimization (RRM) has been recently proposed in several choice contexts. In the route choice context, the paradigm has been used to model the choice among three routes and to formulate regret-based stochastic user equilibrium. However, in the same context the RRM literature has not confronted three major challenges: (i) accounting for similarities across alternative routes, (ii) analyzing choice set composition effects on choice probabilities, and (iii) comparing RRM-based models with advanced RUM-based models. This paper looks into RRM-based route choice models from these three perspectives by (i) proposing utility-based and regret-based correction terms to account for similarities across alternatives, (ii) analyzing the variation of choice set probabilities with the choice set composition, and (iii) comparing RRM-based route choice models with C-Logit, Path Size Logit and Paired Combinatorial Logit. The results illustrate the definition of the correction terms within the regret function, the effect of the choice set specificity of RRM-based route choice models, and the positive performance of these models when compared to advanced RUM-based models.     

The systemic,long-run relation among gasoline demand,gasoline price,income, and vehicle ownership in OECD countries: Evidence from panel cointegration and causality modeling

This paper looks at relationships between gasoline consumption per capita, income, gasoline price, and car ownership for a panel of OECD countries. Estimated long-run and short-run income elasticities are smaller than typically found and gasoline consumption is Granger-caused by gasoline price, but not by car ownership or income. Car ownership is Granger-caused by income and at the margin by gasoline consumption, but not by gasoline price.     

Specification,transferability and the effect of data outliers in modeling the choice of mode in urban travel

Three problems of great importance to urban travel demand modeling using multinominal logit models are examined in this paper. They are (1) the effect of data outliers on model coefficients; (2) the effect of model specification on coefficients and model explanatory power; and (3) the transferability of model coefficients within the region, between regions, and in time.Four data sets are used in the study. They are: Washington, D.C., Minneapolis-St. Paul, and two data sets from the San Francisco Bay Area, Pre-BART and Post-BART. The data are standard home-interview survey data appended with network supplied modal travel cost and time information.The findings of the research are occasionally contradictory; the majority of the evidence supports the following conclusions. The outliers do not have a statistically significant effect (at 0.05 level) on the coefficients; however, the outliers can have a substantial effect on the point estimates of some of the coefficients. Model specification has an impact on model coefficients and model explanatory power. In particular, the definition of out-of-vehicle travel time appears to be important and, if available, the use of separate walk and wait times is preferred over their sum, the out-of-vehicle time. Finally, the model coefficients do not appear transferable within region, between regions, or in time.Research was supported in part by the Alfred P. Sloan Foundation, through grant 74-12-8 to the Department of Economics, University of California, Berkeley and by the National Science Foundation, through grant APR 74-20392, Research Applied to National Needs Program, to the University of California, Berkeley.     

The impact of fare and gasoline price changes on monthly transit ridership: Empirical evidence from seven U.S. transit authorities

This paper presents eight empirical models of monthly ridership for seven U.S. Transit Authorities. Within the framework of these models, the impacts upon monthly ridership from changes in the real fare and gasoline prices are examined. Important findings are: (1) the elasticities of monthly transit ridership with respect to the real fare are negative and inelastic, ranging from 0.042 to 0.62; and (2) the elasticities of monthly transit ridership with respect to the real gasoline price are positive and inelastic, ranging from 0.08 to 0.80. Such results have important policy implications for decisions based on the relationships of price, revenue, and ridership; and for assessing the impacts of changing gasoline prices upon urban modal choice.     

The nonlinear equation system approach to solving dynamic user optimal simultaneous route and departure time choice problems

Dynamic user optimal simultaneous route and departure time choice (DUO-SRDTC) problems are usually formulated as variational inequality (VI) problems whose solution algorithms generally require continuous and monotone route travel cost functions to guarantee convergence. However, the monotonicity of the route travel cost functions cannot be ensured even if the route travel time functions are monotone. In contrast to traditional formulations, this paper formulates a DUO-SRDTC problem (that can have fixed or elastic demand) as a system of nonlinear equations. The system of nonlinear equations is a function of generalized origin-destination (OD) travel costs rather than route flows and includes a dynamic user optimal (DUO) route choice subproblem with perfectly elastic demand and a quadratic programming (QP) subproblem under certain assumptions. This study also proposes a solution method based on the backtracking inexact Broyden–Fletcher–Goldfarb–Shanno (BFGS) method, the extragradient algorithm, and the Frank-Wolfe algorithm. The BFGS method, the extragradient algorithm, and the Frank-Wolfe algorithm are used to solve the system of nonlinear equations, the DUO route choice subproblem, and the QP subproblem, respectively. The proposed formulation and solution method can avoid the requirement of monotonicity of the route travel cost functions to obtain a convergent solution and provide a new approach with which to solve DUO-SRDTC problems. Finally, numeric examples are used to demonstrate the performance of the proposed solution method.     

On the role of bridges as anchor points in route choice modeling

This work builds upon the thought that individuals allocate higher levels of importance to some particular features of the route, so called anchor points. Previous route choice models have either ignored the effects of anchor points (route-based models), or have given an exclusive attention to their effects and ignored the behavioral accuracy and practicality of these models (anchor-based models). In this work we argue that the consideration of both route-level attributes and anchor points would enhance the behavioral aspect of route choice models as well as their estimation and prediction abilities. Global Positioning System traces have been used to investigate the effect of bridges as anchor points for trips between Montreal and its Northern suburb, Laval. A classic Nested Logit and a nested Logit Kernel model have been estimated, in which interdependencies among routes crossing the same bridge are captured through the nested structure and the adopted factor analytic approach, respectively. A Metropolis–Hastings path-sampling algorithm is applied, for the first time, on a large road network with more than 40,000 nodes and 19,000 links to provide the consideration choice set. Estimates are then compared to three alternate models, representing route-based and anchor-based formulations; namely Path-Size Logit, Extended Path-Size Logit, and Independent Availability Logit models. Empirical results showed that the proposed nested structures with MH sampling provide better estimates and also perform better in the validation step with respect to comparative models. Findings underscore the importance of considering anchor points in conjunction with route level attributes in route choice decisions.     

The effect of work-related factors on the bicycle commute mode choice in the Netherlands

Increasing the number of people cycling to work brings a number of benefits: it can lead to reductions in air pollution and traffic jams, and increases people’s physical activity levels. We investigated the extent to which work-related factors influence (1) whether an individual decides to cycle to work, and (2) whether an individual cycles to work every day. It is anticipated that the office culture and colleagues’ and employers’ attitudes would significantly influence both decisions. These factors are expected to impact the provision of cycling facilities and financial compensation schemes in the workplace. We conducted an Internet survey in 4 Dutch municipalities, gathering data from over 4,000 respondents. The results suggest that the following factors increase the likelihood of being a commuter cyclist: having a positive attitude towards cycling; colleagues’ expectations that an individual will cycle to work; the presence of bicycle storage inside; having access to clothes changing facilities; and needing a bicycle during office hours. The presence of facilities for other transport modes, an increase in the commute distance, and the need to transport goods, in turn, reduces the chance that an individual will cycle. Cycling frequency is negatively affected, meanwhile, by an increase in commute distance, a free public transport pass or car parking provided by the employer. These results indicate that an individual’s working situation affects the commuting cycling behaviour. The findings also indicate that (partly) different variables influence an individual’s decision to cycle to work, and their decision to cycle every day.     

Modeling the evolutions of day‐to‐day route choice and year‐to‐year ATIS adoption with stochastic user equilibrium

Suppose that in an urban transportation network there is a specific advanced traveler information system (ATIS) which acts for reducing the drivers' travel time uncertainty through provision of pre‐trip route information. Because of the imperfect information provided, some travelers are not in compliance with the ATIS advice although equipped with the device. We thus divide all travelers into three groups, one group unequipped with ATIS, another group equipped and in compliance with ATIS advice and the third group equipped but without compliance with the advice. Each traveler makes route choice in a logit‐based manner and a stochastic user equilibrium with multiple user classes is reached for every day. In this paper, we propose a model to investigate the evolutions of daily path travel time, daily ATIS compliance rate and yearly ATIS adoption, in which the equilibrium for every day's route choice is kept. The stability of the evolution model is initially analyzed. Numerical results obtained from a test network are presented for demonstrating the model's ability in depicting the day‐to‐day and year‐to‐year evolutions.