Artificial Intelligence in Transportation: Information for Application

Abstract

Foreword he Transportation Research Board's Artificial Intelligence and Advanced Computing Committee (ABJ70) has as part of its mission to serve as a technical forum on the application of artificial intelligence (AI) to transportation problems, and to disseminate information about AI applications that is deemed credible and potentially useful to the transportation community. To this end, this Transportation Research Circular, created by members of ABJ70, provides six articles describing five general AI areas, namely, knowledgebased systems, neural networks, fuzzy sets, genetic algorithms, and agent-based models. It is designed to serve as an informational resource for transportation practitioners and managers with respect to AI tools within these general areas. Each article, for its related AI paradigm, details the types of problems to which the paradigm is best suited, its strengths and weaknesses, example applications, and guidelines for its application. The articles are meant, as one of the authors states, as a sort of Cliff Notes for AI Applications in Transportation. In describing the state of the art vis a vis these areas of AI, it is hoped that better decisions will be made about what tools to choose, under what conditions and for what specific applications for a wide range of transportation problems.