A linear programming formulation for autonomous intersection control within a dynamic traffic assignment and connected vehicle environment
•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. This paper devel...
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| Vydáno v: | Transportation research. Part C, Emerging technologies Ročník 55; s. 363 - 378 |
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| Hlavní autoři: | , |
| Médium: | Journal Article |
| Jazyk: | angličtina |
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Elsevier India Pvt Ltd
01.06.2015
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| Témata: | |
| ISSN: | 0968-090X, 1879-2359 |
| On-line přístup: | Získat plný text |
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| Abstract | •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.
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. |
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| AbstractList | 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. •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. 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. |
| Author | Zhu, Feng Ukkusuri, Satish V. |
| Author_xml | – sequence: 1 givenname: Feng surname: Zhu fullname: Zhu, Feng email: zhu214@purdue.edu – sequence: 2 givenname: Satish V. surname: Ukkusuri fullname: Ukkusuri, Satish V. email: sukkusur@purdue.edu |
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| SubjectTerms | Autonomous Autonomous intersection control Connected vehicles Dynamic traffic assignment Dynamical systems Intersections Linear programming Mathematical models Nonlinear dynamics Optimization System optimum Traffic flow |
| Title | A linear programming formulation for autonomous intersection control within a dynamic traffic assignment and connected vehicle environment |
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