On-Demand Greenwave for Emergency Vehicles in a Time-Varying Road Network With Uncertainties

Abstract

The response time of emergency vehicles (EV) is critical to saving lives. In this paper, we address the two challenges to the reduction of EV response time: 1) path-searching for a reliable estimated time of arrival (ETA) in ever-changing traffic conditions and 2) elastic signal preemption to reduce the negative impact on the whole traffic flow introduced by prioritizing the EVs. While traditional path-searching methods aim to minimize only the mean value of ETA, our approach minimizes a combination of its mean and variance, as we found that the variance of speed has a significant impact on path searching. The simulation shows that our approach generates paths with reliable ETA, i.e., lower variance with the same level of accuracy. Furthermore, we formulate the elastic signal preemption (ESP) as a set of quadratic programming (QP) problems to find non-intrusive signal schedules to the fast track EVs through junctions without stopping. When the ESP module was applied in the real world, results showed about 30% reduction of response time with little impact on the overall traffic conditions.