Optimized lane assignment on an automated highway

Highway automation entails the application of control, sensing and communcation technologies to road vehicles, with the objective of improving highway performance. It has been envisioned that automation would increase highway capacity by a factor of three. To attain this capacity, it will be important to minimize the amount of lane-changing and optimally assign vehicles to lanes. This paper develops and applies a linear programming based lane assignment model. The highway system is modeled as a multi-commodity network, where the commodities represent trip destinations (i.e. exit ramps on highways). An unusual feature of the model is that capacities are defined by bundle constraints, which are functions of the flow entering, leaving, continuing and passing through lanes in each highway segment. The objective is to maximize total flow, subject to a flxed origin destination pattern, expressed on a proportional basis. The model is tested for highways with up to 80 segments, 20 destinations and 5 lanes, and parametric analyses are provided with respect to the time-space requirement for lane-changes, number of lanes, number of segments and origin/destination pattern.