Premium
Case‐Based Reasoning for Real‐Time Traffic Flow Management
Author(s) -
Sadek Adel W.,
Demetsky Michael J.,
Smith Brian L.
Publication year - 1999
Publication title -
computer‐aided civil and infrastructure engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.773
H-Index - 82
eISSN - 1467-8667
pISSN - 1093-9687
DOI - 10.1111/0885-9507.00153
Subject(s) - computer science , case based reasoning , heuristic , routing (electronic design automation) , set (abstract data type) , traffic flow (computer networking) , traffic congestion , intelligent transportation system , artificial intelligence , operations research , transport engineering , engineering , computer network , programming language
Real‐time traffic management is a promising approach for alleviating congestion. This approach uses real‐time and predicted traffic information to develop routing strategies that optimize the performance of highway networks. This article explores the potential for using case‐based reasoning (CBR), an emerging artificial intelligence (AI) paradigm, to overcome the limitations of existing traffic‐management decision support systems. To illustrate the feasibility of the approach, the article develops and evaluates a prototype CBR routing system for a real‐world network in Hampton Roads, Virginia. Cases for building the system's case base are generated using a heuristic dynamic traffic assignment (DTA) model specifically designed for the region. Using a set of 25 new independent cases, the performance of the prototype system is evaluated by comparing its solutions with those of the DTA model. The evaluation results demonstrate the feasibility of the CBR approach. The prototype system was capable of running in real time and produced high‐quality solutions using case bases of reasonable size.