Vehicular Crowdsourcing for Congestion Support in Smart Cities

Abstract

Under present-day practices, the vehicles on our roadways and city streets are mere spectators that witness traffic-related events without being able to participate in the mitigation of their effect. This paper lays the theoretical foundations of a framework for harnessing the on-board computational resources in vehicles stuck in urban congestion in order to assist transportation agencies with preventing or dissipating congestion through large-scale signal re-timing. Our framework is called VACCS: Vehicular Crowdsourcing for Congestion Support in Smart Cities. What makes this framework unique is that we suggest that in such situations the vehicles have the potential to cooperate with various transportation authorities to solve problems that otherwise would either take an inordinate amount of time to solve or cannot be solved for lack for adequate municipal resources. VACCS offers direct benefits to both the driving public and the Smart City. By developing timing plans that respond to current traffic conditions, overall traffic flow will improve, carbon emissions will be reduced, and economic impacts of congestion on citizens and businesses will be lessened. It is expected that drivers will be willing to donate under-utilized on-board computing resources in their vehicles to develop improved signal timing plans in return for the direct benefits of time savings and reduced fuel consumption costs. VACCS allows the Smart City to dynamically respond to traffic conditions while simultaneously reducing investments in the computational resources that would be required for traditional adaptive traffic signal control systems.