Highlights of Lane-Free Automated Vehicle Traffic with Nudging
摘要
Connected Automated Vehicles (CAVs) have superb capabilities compared to human drivers, which calls for revisiting of established conventional road traffic principles. Recently, the TrafficFluid concept, a novel paradigm for vehicular traffic at high levels of vehicle automation, was proposed, relying on two combined principles: (a) Lane-free traffic, whereby vehicles are not bound to fixed traffic lanes and (b) Vehicle nudging, whereby vehicles influence other vehicles in front or aside of them. This chapter provides highlights of related research: three methodological approaches to lane-free vehicle movement strategies with nudging, namely, optimal control, nonlinear feedback control, multiagent reinforcement learning; a specialized microscopic simulation environment; macroscopic traffic flow models emerging from lane-free vehicle driving with nudging, using a theoretical and an empirical approach; a new, highly efficient traffic control measure for lane-free traffic; a challenging case study of a large-scale complex roundabout; and joint path optimization of multiple vehicles in a lane-free environment.