How Can Autonomous Road Vehicles Coexist with Human-Driven Vehicles? An Evolutionary-Game-Theoretic Perspective

The advent of highly automated vehicles in the form of autonomous road vehicles (ARVs) is bound to bring about a paradigm shift in road user interaction, especially that between ARVs and human-driven vehicles (HDVs). Previous literature on the game-theoretic interaction between ARVs and HDVs tends to focus on working out the best possible strategy for a single interaction, i.e. the Nash equilibrium. This position paper sets out to demonstrate the importance and potential impact of applying evolutionary game theoretic principles to what is effectively a dynamic population driven by evolutionary forces – the population of road users. We demonstrate using theoretical scenarios that simply maintaining Nash equilibria does not guarantee evolutionary success. Instead, ARVs must enjoy a demonstrable advantage over other road users when few in numbers. Otherwise, their uptake will slow down and eventually reverse. We argue that the same selection factors which influence the success of living populations in the natural world also influence the success of the different vehicle types and driving styles in the road user population, including ARVs. We demonstrate this by assigning an expected fitness score to each vehicle in a one-to-one interaction, such as at a junction. This fitness score is dependent on driver, rider and economic costs incurred by the vehicle and/or its occupant(s) during interaction. In turn we show that ARV and transport system designers need to ensure that the fitness score of their systems create evolutionary stability.