Evaluation of Adaptive Control Strategies for NJ Highways

In this project, a prototype knowledge-based expert system (KBES) integrated with a Geographic Information System (GIS) is developed. Geomedia Pro is used as the GIS interface for data entry. A software bridge is also implemented to ensure swift data exchange between Synchro, which is a commercial signal optimization software package used by the New Jersey Department of Transportation (NJDOT), and the developed prototype. This integration will allow the users to transfer intersection data between Synchro and the prototype KBES tool in an efficient way. The rule base of the prototype KBES was developed using the information that exists in the literature, including surveys conducted by other researchers and the simulation studies conducted by the Rutgers research team. The performance of three distinct adaptive control strategies were assessed by using a macroscopic and a microscopic simulation tool namely, PARAMICS. Prototypes for reactive (SCOOT-like), case-based/reactive (SCATS-like) and proactive/predictive (OPAC-like algorithms), each using a different control logic, were developed. These prototypes were tested for various well-calibrated New Jersey intersections. The outcome of these simulation studies was then used to develop general rules in terms of the effectiveness of using adaptive control strategies under various network and traffic conditions. The developed rule base was implemented in Visual Basic and integrated with the developed prototype. The prototype also has the capability of performing interactive macroscopic simulation of OPAC-like, SCOOT-like, and SCATS-like control strategies given the intersection and traffic characteristics. This feature was added to the KBES system to enable the user to further analyze each individual intersection. Finally, a benefit-cost analysis function is implemented and integrated to further support the decision making process. In short, the developed tool provides the NJDOT traffic engineers and decision makers with a user-friendly suite of tools to guide them in identifying the most suitable intersections for adaptive control and in accurately assessing the potential benefits over existing control.

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