Dr. Pitu Mirchandani, STC Distinguished Speaker, Professor of Computing, Informatics, and Decision Systems Engineering and Director of the ATLAS Laboratory at Arizona State University
Currently, adaptive traffic signal control systems often require a major investment of resources for both initial installation and subsequent maintenance. The next generation traffic signal system will be easy to install, easy to maintain, operator friendly, and reliable, through what may be referred to as a self-adaptive traffic signal system that observes (through camera-based and other sensors) the traffic in the network, predicts the traffic demands and conditions for a short-term horizon, and sets phase durations to optimize an objective specified by the jurisdiction; where the optimization objective may include measures related to delays, safety, emissions, etc. as long as the corresponding performance measures may be monitored in real-time. With a self-adaptive signal control system in place, the next logical step is to expand the system further to include IntelliDrive technologies (IDT). Through the use of IDT, information on a vehicle’s current location, destination, speed, acceleration, etc. can be available throughout its journey, greatly expanding the ability of signal control systems to efficiently allocate available green times to handle varying traffic demands on the network. The talk will discuss some initial attempts to develop the Next Generation RHODES adaptive traffic control system, supported though a FHWA grant, where advanced algorithms will utilize the available rich data flow in new ways to extract RHODES’ timing parameters automatically, rather than requiring periodic traffic studies to collect information about turn proportions, travel times, etc.