Case‐Based Reasoning for Real‐Time Traffic Flow Management

摘要: Real-time traffic management is a promising approach for alleviating congestion. This uses real-time and predicted information to develop routing strategies that optimize the performance of highway networks. article explores potential using case-based reasoning (CBR), an emerging artificial intelligence (AI) paradigm, overcome limitations existing traffic-management decision support systems. To illustrate feasibility approach, develops evaluates prototype CBR system real-world network in Hampton Roads, Virginia. Cases building system's case base are generated heuristic dynamic assignment (DTA) model specifically designed region. Using set 25 new independent cases, evaluated by comparing its solutions with those DTA model. The evaluation results demonstrate approach. was capable running real time produced high-quality bases reasonable size.