Effects of Future Connected Autonomous Vehicles on Freeway Congestion Using Fuzzy Cognitive Mapping

Continuing population growth and urbanization are projected to add 2.5 billion people to the world's urban population by 2050 [1]. It is evident that this will increase traffic congestion especially in the urban areas, which will bring economic, safety, environmental and quality of life challenges. There are various organizations looking for possible solutions to reduce the impact of future congestion by long term planning [2], most of these studies don't take into account emergence of disruptive technologies. The concept of vehicles with autonomous driving and online connectivity capabilities, namely, connected autonomous vehicles (CAVs) is an emerging technology [3] which may contribute to the solution of this problem through adoption. This paper aims to shed light on effect of different levels of CAV adoption on congestion through scenario planning with fuzzy cognitive mapping. Different future scenarios on CAV adoption based on research and development being done on CAV technology [3] are run through a fuzzy cognitive model of congestion developed through detailed literature review. Results indicate CAV adoption provides an opportunity for reducing congestion. Therefore suggesting, investing in CAV enabling upgrades of existing roads, and giving incentives for CAV adoption, is a viable option for city planners' and local governments' project portfolios to reduce congestion.