Validating the results of a route choice simulator

Bonsall, Peter; Firmin, P E; Anderson, Monica; Palmer, Ian; Balmforth, Peter

doi:10.1016/s0968-090x(98)00003-5

Cited by 77 publications

(35 citation statements)

References 4 publications

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“…Route choice studies (e.g. Bonsall et al 1997) have revealed that drivers making unfamiliar journeys generally seek to make maximum use of routes with which they are already familiar. Other work has suggested that female drivers are less willing than males to depart from familiar or signposted routes (Bonsall, 1992;Khattak et al, 1993;Emmerink et al, 1996) and that drivers' reluctance to depart from familiar routes is greatest when they are under time pressure (Bonsall et al, 2000).…”

Section: Advance Planning In Order To Reduce Uncertaintymentioning

confidence: 99%

Traveller Behavior: Decision-Making in an Unpredictable World

Bonsall

2004

Journal of Intelligent Transportation Systems

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This paper discusses the nature and consequences of uncertainty in transport systems. Drawing on work from a number of fields, it addresses travellers' abilities to predict variable phenomena, their perception of uncertainty, their attitude to risk and the various strategies they might adopt in response to uncertainty. It is argued that despite the increased interest in the representation of uncertainty in transport systems, most models treat uncertainty as a purely statistical issue and ignore the psychological aspects of response to uncertainty. The principle theories and models currently used to predict travellers' response to uncertainty are presented and number of alternative modelling approaches are outlined. It is argued that the current generation of predictive models do not provide an adequate basis for forecasting response to changes in the degree of uncertainty or for predicting the likely effect of providing additional information. A number of alternative modelling approaches are identified to deal with travellers' acquisition of information, the definition of their choice set and their choice between the available options. The use of heuristic approaches is recommended as an alternative to more conventional probabilistic methods. 1.

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Section: Advance Planning In Order To Reduce Uncertaintymentioning

confidence: 99%

Traveller Behavior: Decision-Making in an Unpredictable World

Bonsall

2004

Journal of Intelligent Transportation Systems

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“…Some other studies used SP data from travel simulator experiments (e.g., [17][18][19][20][21][22][23][24][25]). Others used revealed preference (RP) data to model drivers' response behavior (e.g., [26][27][28][29]).…”

Section: Introductionmentioning

confidence: 99%

Leave the expressway or not? Impact of dynamic information

Gan

2014

J. Mod. Transport.

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This study investigates drivers' diversion decision behavior under expressway variable message signs that provide travel time of both an expressway route and a local street route. Both a conventional cross-sectional logit model and a mixed logit model are developed to model drivers' response to travel time information. It is based on the data collected from a stated preference survey in Shanghai, China. The mixed logit model captures the heterogeneity in the value of ''travel time'' and ''number of traffic lights'' and accounts for correlations among repeated choices of the same respondent. Results show that travel time saving and driving experience serve as positive factors, while the number of traffic lights on the arterial road, expressway use frequency, being a middle-aged driver, and being a driver of an employer-provided car serve as negative factors in diversion. The mixed logit model obviously outperforms the cross-sectional model in dealing with repeated choices and capturing heterogeneity regarding the goodness-of-fit criterion. The significance of standard deviations of random coefficients for travel time and number of traffic lights evidences the existence of heterogeneity in the driver population. The findings of this study have implications for future efforts in driver behavior modeling and advanced traveler information system assessment.

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“…IGOR (Interactive Guidance on Routes) by Bonsall and Parry [9], is the first simulator introduced, which simulates en-route travel through a network and the provision of real-time information. Following IGOR_s path is VLADIMIR by Bonsall et al [10], which has as primary purpose to explore the influence of route-guidance and information on drivers_ route choice. The next simulator, developed at MIT by Koutsopoulos et al [34], is used to collect data and calibrate a route-choice model incorporating concepts of fuzzy logic and fuzzy set theory.…”

Section: Travel Simulatorsmentioning

confidence: 99%

GABRIEL: Gis Activity-Based tRavel sImuLator. Activity Scheduling in the Presence of Real-Time Information

Kwan

Casas

2006

Geoinformatica

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A series of travel simulators have been developed in the past two decades under the Intelligent Transportation Systems (ITS) umbrella. They have addressed issues such as reactions to advisory radio and variable message signs, use of navigation systems, route diversion, and mode choice. The objective of this paper is to present the design and implementation of a different kind of travel simulator. GABRIEL (Gis Activity-Based tRavel sImuLator) has as a foundation the activitybased approach and makes use of geographic information systems (GIS) as a development environment. The simulation scenario consists of a commute trip where two activities take place. En-route to the first destination, congestion occurs and subjects are requested to take action based on a set of alternatives. The simulator provides re-routing, destination substitution, dynamic geographic information and real-time information to aid users in their decision-making process. As a result it helps subjects in developing their ability to adapt given a particular scenario and allow researchers in understanding trip making, activity rescheduling, and the decision-making process from a comprehensive perspective.

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Validating the results of a route choice simulator

Cited by 77 publications

References 4 publications

Traveller Behavior: Decision-Making in an Unpredictable World

Traveller Behavior: Decision-Making in an Unpredictable World

Leave the expressway or not? Impact of dynamic information

GABRIEL: Gis Activity-Based tRavel sImuLator. Activity Scheduling in the Presence of Real-Time Information

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