Smarter Transit System via Connected Vehicles and Low Cost Internet of Things

In this presentation, we present transit signal priority harnessed by connected vehicle technology that overcomes limitations of the state of the art transit signal priority algorithms. These limitations include (i) bus
missing extended green, (ii) disruption on arterial progression, and (iii) incapable of handling multiple buses. Our proposed transit signal priority approach introduced green allocation concept to allow bus can take advantage
of transit signal priority at any time in cycle, and formulated the progression and multiple bus optimization problem using binary mixed integer linear programing. Compared to traditional transit signal priority, our approach significantly improved bus travel times and person delays at the intersections.

In addition, we present a low cost Internet of Things (IoT) technology to monitor transit system. We developed an IoT device based on a Raspberry Pi and WiFi reader to track passengers (actually WiFi devices) at the bus stations. This low cost IoT device can estimate (i) passengers' waiting times at bus stations and (ii) passengers' origin-destination stations. The IoT devices were pilot tested at the James Madison University campus and the University of Virginia on grounds. We found that our devices are capable of estimating waiting times as well as origin-destination estimations. This is a great alternative to smart card and automated passenger counting system used by metropolitan cities for origin-destination estimations, especially for small and medium sized cities.