The emergence of Intelligent Transportation Systems (ITS) has fostered the development of advanced traveler information systems (ATIS). These systems are designed to assist travelers in making pre-trip and enroute travel choice decisions. It is contended that while many traveler information systems are innovative and make use of cutting edge technologies, they lack real machine intelligence and therefore may be limited in their ability to service the traveling public over the long-run. The purpose of this paper is to present a vision of the next generation traveler information system, termed Intelligent Traveler Information Systems (ITIS) in which artificial intelligence techniques are drawn upon to create systems capable of providing travelers with more personalized planning assistance.

Toward the design of intelligent traveler information systems

Advanced Travel Information Systems (ATISs) are designed to assist travellers in making better travel choices by providing pre-trip and en-route information such as travel times on the relevant alternatives. Travellers’ choices are likely to be sensitive to the accuracy of the provided information in addition to travel time uncertainty. A route-choice experiment with 36 participants, involving 20 repetitions under three different levels of information accuracy was conducted to investigate the impact of information accuracy. In each experiment respondents had to choose one of three routes (risky, useless and reliable). Provided information included descriptive information about the average estimated travel times for each route, prescriptive information regarding the suggested route and experiential feedback information about the actual travel times on all routes. Aggregate analysis using non-parametric statistics and disaggregate analysis using a mixed logit choice model were applied. The results suggest decreasing accuracy shifts choices mainly from the riskier to the reliable route but also to the useless alternative. Prescriptive information has the largest behavioural impact followed by descriptive and experiential feedback information. Risk attitudes also seem to play a role. The implications for ATIS design and future research are further discussed.

The impact of travel information's accuracy on route-choice

A comprehensive travel demand modeling framework is proposed to identify and model the urban development decisions of firms and the mobility, activity, and travel decisions of individuals and households. The framework is also used to develop a system of models that can be used by decisionmakers and planners to evaluate the effects of developments in information technologies and changes in the transportation system. The implementation of an operational model system based on this framework is envisioned as an incremental process starting with the current best practice of disaggregate travel demand model systems. To this end, an activity-based model system is presented as the first stage in the development of an operational model system.

Travel demand model system for the information era. in: transport and information systems

This paper explores the use of cooperative, distributed multi-agent systems to improve dynamic routing and traffic management. On the supply-side, real-time control over the transportation network is accomplished through an agent-based distributed hierarchy of system operators. Allocation of network capacity and distribution of traffic advisories are performed by agents that act on behalf of information service providers. Driver needs and preferences are represented by agents embedded in intelligent in-vehicle route guidance systems. Negotiation between ISP and driver agents seek a more efficient route allocation across time and space. Results from simulation experiments suggest that negotiation can achieve more optimal network performance and increased driver satisfaction.

A multi-agent approach to cooperative traffic management and route guidance

The emergence of new information technologies and recent advances in existing technologies have provided new dimensions for travel demand decisions. In this paper we propose a comprehensive travel demand modeling framework to identify and model the urban development decisions of firms and developers and the mobility, activity and travel decisions of individuals and households, and to develop a system of models that can be used by decision makers and planners to evaluate the effects of changes in the transportation system and development of information technologies (e.g. various tele-commuting, tele-services and Intelligent Transportation Systems). The implementation of an operational model system based on this framework is envisioned as an incremental process starting with the current “best practice” of disaggregate travel demand model systems. To this end, we present an activity-based model system as the first stage in the development of an operational model system.

Travel demand model system for the information era

A conflict model and interactive simulator (fastcars) for predicting enroute assessment and adjustment behavior in response to real-time traffic condition information

It has been contended that in-laboratory experimentation with interactive microcomputer simulation can substitute for the lack of real-world applications and provide a useful approach to data collection and driver behavior analysis. With the rapid development but limited real-world deployment of Advanced Traveler Information Systems, interactive simulation has quickly grown in popularity among researchers studying dynamic driver behavior. This paper discusses the development and implementation of FASTCARS (Freeway and Arterial Street Traffic Conflict Arousal and Resolution Simulator), an interactive microcomputer-based animated simulator designed for in-laboratory experimentation to assist in the estimation and calibration of predictive models of driver behavior under the influence of real-time information.

Interactive simulation for modeling dynamic driver behavior in response to atis. working paper

The development and implementation is described of FASTCARS (Freeway and Arterial Street Traffic Conflict Arousal and Resolution Simulator), an interactive microcomputer-based animated simulator designed for in-laboratory experimentation and data collection to assist in the estimation and calibration of predictive models of driver behavior under the influence of real-time information. It is noted that limited real-world implementation of Advanced Traveler Information Systems (ATIS) technoloiges make it difficult to analyze the potential impact on driver behavior. The study holds that interactive animated route choice simulators can substitute for the lack of real-world applications and provide a useful approach to data collection and driver behavior analysis. The advantages of using FASTCARS over other data collection methods to study driver behavior are discussed.

M G McNally

Papers

A conflict model and interactive simulator (fastcars) for predicting enroute assessment and adjustment behavior in response to real-time traffic condition information

Interactive simulation for modeling dynamic driver behavior in response to atis. working paper

Microcomputers in transportation. using interactive simulation to model driver behavior under atis