Spatial system perspective of understanding ‘‘fuel-sensitive routes’’ using regional-scale case studies

Abstract

Eco-routing is widely researched as a promising way to reduce traffic-related environmental externalities. Past studies indicate that fuel-sensitive eco-routing trades the fastest routes with shorter, slower urban roads to take advantage of the “optimal fuel economy”. However, past studies focusing on individual routes often fail to depict the spatial redistribution of traffic being closer to the residential areas when eco-routing is adopted at a large scale. This research conducts city-scale fuel-sensitive routing simulations for two large metropolitan areas: the San Francisco Bay Area case and the Tokyo Area case. Combining agent-based simulations with data-driven fuel model, it is revealed that fuel-sensitive routing exerts heavier traffic on the local streets and increases residents’ direct exposure to traffic. Furthermore, by comparing different sub-areas, the varied degrees of traffic redistribution are found to be mainly dependent on the availability of major roads as alternative routes, and existing traffic congestion levels in an area.