Energy and emissions impacts of a freeway-based dynamic eco-driving system

摘要

Surface transportation consumes a vast quantity or fuel and accounts tor about a third or the US CO_2 emissions. In addition to the use of more fuel-efficient vehicles and carbon-neutral alternative fuels, fuel consumption and CO_2 emissions can be lowered through a variety of strategies that reduce congestion, smooth traffic flow, and reduce excessive vehicle speeds. Eco-driving is one such strategy. It typically consists of changing a person's driving behavior by providing general static advice to the driver (e.g. do not accelerate too quickly, reduce speeds, etc.). In this study, we investigate the concept of dynamic eco-driving, where advice is given in real-time to drivers changing traffic conditions in the vehicle's vicinity. This dynamic strategy takes advantage of real-time traffic sensing and telematics, allowing for a traffic management system to monitor traffic speed, density, and flow, and then communicates advice in real-time back to the vehicles. By providing dynamic advice to drivers, approximately 10-20% in fuel savings and lower CO_2 emissions are possible without a significant increase in travel time. Based on simulations, it was found that in general, higher percentage reductions in fuel consumption and CO_2 emission occur during severe compared to less congested scenarios. Real-world experiments have also been carried out, showing similar reductions but to a slightly smaller degree.