A linear programming formulation for autonomous intersection control within a dynamic traffic assignment and connected vehicle environment. (June 2015)

• Record Type: Journal Article
• Authors: Zhu, Feng; Ukkusuri, Satish V.
• Is Part Of: Transportation research. Volume 55(2015)
• Page Start: 363
• Page End: 378
• Publication Date: 2015-06
• Subjects: Linear programming -- Autonomous intersection control -- Dynamic traffic assignment -- System optimum -- Connected vehicles; Transportation -- Periodicals; Transportation -- Technological innovations -- Periodicals; 388.011
• DOI: 10.1016/j.trc.2015.01.006
• Languages: English
• ISSNs: 0968-090X

Abstract

Highlights: Develops a linear programming formulation for autonomous intersection. It also accounts for system optimal route choice behavior. Intersection safety is guaranteed. There are no holding flows in the solution. Various tests have been conducted to verify the formulation's properties. Abstract: This paper develops a novel linear programming formulation for autonomous intersection control (LPAIC) accounting for traffic dynamics within a connected vehicle environment. Firstly, a lane based bi-level optimization model is introduced to propagate traffic flows in the network, accounting for dynamic departure time, dynamic route choice, and autonomous intersection control in the context of system optimum network model. Then the bi-level optimization model is transformed to the linear programming formulation by relaxing the nonlinear constraints with a set of linear inequalities. One special feature of the LPAIC formulation is that the entries of the constraint matrix has only {−1, 0, 1} values. Moreover, it is proved that the constraint matrix is totally unimodular, the optimal solution exists and contains only integer values. It is also shown that the traffic flows from different lanes pass through the conflict points of the intersection safely and there are no holding flows in the solution. Three numerical case studies are conducted to demonstrate the properties and effectiveness of the LPAIC formulation to solve autonomous intersection control.