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Joint optimization of vehicle trajectories for a highway weaving area in lane-free traffic

Dafereras Georgios

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Summary

Traffic congestion on highways and arterials is an increasingly serious problem for most major cities around the world, leading to substantial delays, increased fuel consumption, excessive environmental pollution, and compromised traffic safety. While traffic management measures utilizing conventional actuators are valuable and, in some cases, capable of delaying or even preventing congestion, they are not always adequate for addressing heavily congested traffic conditions. Gradually emerging and future ground-breaking vehicle automation and communication systems should be exploited to develop innovative solutions that can be applied within a smart road infrastructure.The recently introduced TrafficFluid concept presents a novel paradigm for vehicular traffic, particularly applicable at high levels of vehicle automation and communication systems. The TrafficFluid concept suggests: (1) lane-free traffic, whereby vehicles are not bound to fixed traffic lanes, as in conventional traffic; and (2) vehicle nudging, whereby vehicles may exert a "nudging" effect on vehicles in front of them. Vehicles in a lane-free environment do not necessarily align to form lanes but are self-organizing into dynamically changing 2-D clusters, depending on the vehicle sizes, their desired speeds, the employed vehicle movement strategies, and the prevailing density, so as to maximize the infrastructure utilization.This thesis introduces a joint trajectory optimization algorithm for a number of connected and automated vehicles within a lane-free highway weaving area, i.e. a common highway design element near ramps. A weaving area may experience congestion problems even when traffic flow is less than capacity due to design and complexity of the vehicle interactions, resulting into low traffic flow and potential safety issues. A double-integrator model is utilized for the longitudinal and lateral movements of each vehicle. The objective function comprises several sub-objectives reflecting corresponding, partially competing, driving aspects and concerns, including passenger comfort, low fuel consumption, vehicle advancement at desired speed, collision avoidance, suppressing of infeasible maneuvers. Fixed and state-dependent control input bounds account for various technical limitations as well as road boundary adherence. The solution to the formulated joint Optimal Control Problem (OCP) is computed using a highly efficient Feasible Direction Algorithm, which exploits the structure of the state equations to map the OCP into a reduced Nonlinear Programming Problem. To demonstrate the efficiency of the proposed approach, challenging scenarios will be examined on a lane-free highway, including an on-ramp and off-ramp, located close to each other and forming a weaving area.

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