This paper presents a framework and methodology for integrating real-time Traffic Estimation and Prediction Systems (TrEPS) into weather-responsive traffic signal operations in Utah, USA. This study is motivated by the need for adjusting signal timing plans in response to changing traffic conditions during inclement weather in order to mitigate the impact of weather and maintain the network service level. This study provides a real-world application demonstrating that such a need can be effectively assisted by a TrEPS-based decision support system. Three components are introduced to form the overall decision support system: real-time TrEPS, Scenario Manager, and Scenario Library. Real-time TrEPS offers the capability to estimate and predict network states under various control scenarios; Scenario Manager provides an environment to identify and evaluate alternative signal control strategies based on TrEPS-predicted network states; and Scenario Library serves as a knowledge base defining available weather-responsive signal timing plans for Scenario Manager to access in real-time. The detailed implementation procedure and expected benefits of the proposed system are illustrated and discussed using a case study based on a historical snow event.
|Title of host publication||Proceedings of the 17th International IEEE Conference on Intelligent Transportation Systems|
|State||Published - 2014|
|Event||Proceedings of the 17th International IEEE Conference on Intelligent Transportation Systems - Qingdao, China|
Duration: Oct 1 2014 → …
|Conference||Proceedings of the 17th International IEEE Conference on Intelligent Transportation Systems|
|Period||10/1/14 → …|