Autonomous-Vehicle Intersection Control Method Based on an Interlocking Block

Abstract

Non-signalized intersections have only ever been suitable for low traffic flow; however, with the development of autonomous driving technology and new control methods, the operation efficiency of this kind of intersection may be improved. In view of the shortcomings of existing non-signalized intersection control methods in multilane situations and inspired by railway trains, an interlocking-block intersection control model is proposed. In this study, vehicles between parallel lanes are combined into a few combos, and the combo shape can be determined according to a pairing model and the interlocking angle range, and the gaps between the front and rear vehicles are simulated as blocks in a railway system, which are added into the intersection control model as virtual blocked cars (VBCs) for optimization. In setting the optimization objectives, the connotation and realization of fairness are discussed. Experimental results show that compared with signalized intersections, roundabouts, and non-signalized intersections without control, the interlocking-block intersection control model greatly reduces vehicle delay. Compared with an existing model, the calculation speed in a multilane situation has been greatly improved, while the vehicle delay is similar.