ADVANCED ADAPTIVE SIGNAL CONTROL

摘要

Historically, Road Weather Information Systems (RWIS), their many associated atmosphericsensors, road pavement condition sensors, and the data they provide have been an integralpart of the Road Weather Maintenance and Decision Support Systems that many of theworld’s nations and nearly all of the U.S. States use in their winter maintenance efforts. Thisdata has proven to be an effective tool for maintaining a safe surface transportation systemwhile improving mobility and mitigating the environmental impacts of the chemicals used inthese efforts - all while significantly reducing operational costs. The returns on investment inthis technology have been proven and illustrated in many value added propositionsthroughout the world.During the Transportation Research Board (TRB) conference held in Washington D.C. onJanuary 23-27 2010, there were over 15 studies from universities throughout the U.S. thatprovided significant conclusions on the impact of weather on traffic. Many of these studies,however, were based on simple atmospheric conditions like precipitation and visibility; theyused broad guidelines to define “bad weather” or “good weather.” However, one studyconducted by the University of Wisconsin concluded that, “[t]he pavement surfacetemperature, not often investigated by existing studies, has significant impacts on urbanfreeway traffic flow.”(1) Every study that included correlation of weather events and the effecton traffic concluded that weather had substantial impact on either traffic safety or efficiency.The next step is to capitalize on this research and develop applications and even fine tuneexisting systems in ways that could potentially reduce the effect weather has on traffic.This paper brings technical light and an innovative approach to a specific application that canutilize the existing infrastructure of RWIS data and Adaptive Traffic Signal Control (ATSC)to create more efficient signal phasing and safer intersection conditions during inclementweather. It defines in general adaptive signal control applications and current atmosphericand pavement condition data assets. The paper then presents ideas on how to combine thosetwo to create system applications that adapt to current traffic conditions and the associatedchanges in driver behavior, with the goal of creating safer, more efficient weather basedadaptive signal phasing systems. For example, if a sensor senses that the friction coefficientof the pavement at an intersection is significantly reduced so that the stopping distance of avehicle is increased by 50%, the signal controller can take that data and modify the signaltiming to increase yellow lights or increase the delay between red and green light phasing.This will allow vehicles more time to clear the intersection, reducing collisions caused byvehicles unable to stop in their normal time because of reduced friction. This is just oneexample of the many applications that could be developed by integrating these two existingITS systems.The paper concludes that by utilizing existing ITS infrastructure to develop new advancedapplications without significant increase in costs, we can increase the return on investmentand effectiveness of Intelligent Transportation Systems. It also demonstrates that bydeveloping systems that have multiple applications we can increase the resolution of dataderived from these systems, thus increasing the overall effectiveness of IntelligentTransportation Systems throughout the world.