![]() A major topic of recent research is modifying backpressure control for communications networks into an adaptive traffic signal timing. ĭespite the advances in data availability, recent work on adaptive signal control nevertheless has relied heavily on queue length information. In comparison, physical sensors still relied upon for traffic data incur significant installation and maintenance costs. The ubiquity and accuracy of this type of crowdsourced data has made this high-quality real-time traffic data easily accessible at a substantially cheaper cost. ![]() These types of data, also called “crowdsourced data” have been used to understand mobility behavior and congestion patterns. Navigation companies like Google, Here, and TomTom extensively utilize these forms of data collected from the crowd to provide real-time traffic information back to their customers. The ubiquity of mobile devices has made possible each of these devices acting as a mobile sensor providing real-time information on travel time, speed, location, and traffic states. For this reason traffic signals have not developed or utilized delay data let alone crowsourced delay data in their optimization algorithms. ![]() Historically, the cost of acquiring volume and queue data at junctions was much more cost effective than acquiring delay data. A more recent and novel algorithms such as max-pressure used for adaptive signal systems at a network level also rely on queue length and volume counts that require physical sensors. These adaptive traffic signal systems and others that are widely used rely on physical sensors, such as loop detectors, radar sensors or near real-time traffic videos. Notable systems of this type include SCOOT SCATS OPAC and RHODES. Traditionally, the high cost and limited access to delay data meant that most adaptive traffic signal systems relied on volume and queue length data. Ever since the inception of traffic signals to manage conflicts at traffic junctions, increasing congestion has driven the pursuit towards optimal phase structure, cycle length and green times that would minimize delay and/or maximize throughput. Congestion has literally put our cities at the “crossroads.” Signals are a common strategy to manage traffic at junctions through prioritization of traffic movements while ensuring the efficient and safe flow of traffic.
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