OPTIMIZED LANE ASSIGNMENT ON AN AUTOMATED HIGHWAY

Highway automation entails the application of control, sensing and com munication technologies to road vehicles, with the objective of improv ing highway performance. It has been envisioned that automation could increase highway capacity by a factor of three. To attain this capacit y, it will be important to minimize the amount of lane-changing and op timally assign vehicles to lanes. This paper develops and applies a li near programming based lane assignment model. The highway system is mo deled as a multi-commodity network, where the commodities represent tr ip destinations (i.e, exit ramps on highways). An unusual feature of t he model is that capacities are defined by bundle constraints, which a re functions of the Bow entering, leaving, continuing and passing thro ugh lanes in each highway segment. The objective is to maximize total flow, subject to a fixed origin/destination pattern, expressed on a pr oportional basis. The model is tested for highways with up to 80 segme nts, 20 destinations and 5 lanes, and parametric analyses are provided with respect to the time-space requirement for lane-changes, number o f lanes, number of segments and origin/destination pattern. Copyright (C) 1996 Elsevier Science Ltd