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Intelligent Transport Systems and Traffic Management
Published in Rajshree Srivastava, Sandeep Kautish, Rajeev Tiwari, Green Information and Communication Systems for a Sustainable Future, 2020
Pranav Arora, Deepak Kumar Sharma
One such system is Scalable Urban Traffic Control (SURTRAC) that was developed by researchers from Carnegie Mellon University (CMU). The system dynamically optimizes the traffic signals, hence improving the flow of traffic, leading to shorter waiting times, reduced traffic congestion, and ultimately less pollution.The SURTRAC (Scalable Urban Traffic Control) system merges the ideas from traffic control theory with the current advancement in the domain of multiple agent planning systems and also has quite a few vital traits that distinguish it from the others. To further enhance the ascendability and dependence/reliance of the system SURTRAC firstly functions in a complete unconsolidated controlled way; every junction of the traffic is independently allocated a green period, based flow of incoming vehicles. Secondly, SURTRAC also strives to improve urban road transportation networks with a lot of input traffic flows where the coordination of individual levels is done by processing with the estimated outflows to the various downstream neighbors, which gives these traffic intersections a more informed basis for locally balancing competing for the inflow of traffic while simultaneously also promoting the setting up even of even larger green travel corridors. Thirdly SURTRAC also operates in an instantaneous manner thus each traffic junctions recalculates its initial allotment procedure and thus re-communicates expected outflows as with a frequency close to 1 per second in rolling horizon fashion, enabling both effective operations in heavily congested signal networks and also being aware to sudden changes in traffic conditions and adapting accordingly [6].
Operational performance evaluation of adaptive traffic control systems: A Bayesian modeling approach using real-world GPS and private sector PROBE data
Published in Journal of Intelligent Transportation Systems, 2020
Zulqarnain H. Khattak, Mark J. Magalotti, Michael D. Fontaine
A study regarding SURTRAC (SCALABLE URBAN TRAFFIC CONTROL) was conducted by its developers, and mainly focused on explaining the architecture of SURTRAC and its functionality along with providing some brief descriptions of its implementation to a nine-intersection grid network. That study concluded that major reductions in travel times and emissions were achieved, but no statistical evaluation was performed (Smith, Barlow, Xie, & Rubinstein, 2013). As a result, there is no objective performance information available on the performance of this system. The research documented in this paper evaluates the performance of SURTRAC on a network in Pittsburgh, Pennsylvania to help fill this gap. The system was assessed using a combination of real-world GPS floating car runs and private sector probe travel time data from INRIX.