Design and Evaluation of a Mathematical Optimization Model for Traffic Signal Plan Transition Based on Social Cost Function
保存先:
| 出版年: | Journal of Advanced Transportation vol. 2017 (2017) |
|---|---|
| 第一著者: | |
| その他の著者: | , , |
| 出版事項: |
John Wiley & Sons, Inc.
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| 主題: | |
| オンライン･アクセス: | Citation/Abstract Full Text Full Text - PDF |
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| 024 | 7 | |a 10.1155/2017/1943846 |2 doi | |
| 035 | |a 2407644579 | ||
| 045 | 2 | |b d20170101 |b d20171231 | |
| 084 | |a 164028 |2 nlm | ||
| 100 | 1 | |a Peñabaena-Niebles, Rita |u Department of Industrial Engineering, Universidad del Norte, Atlantico, Colombia | |
| 245 | 1 | |a Design and Evaluation of a Mathematical Optimization Model for Traffic Signal Plan Transition Based on Social Cost Function | |
| 260 | |b John Wiley & Sons, Inc. |c 2017 | ||
| 513 | |a Journal Article | ||
| 520 | 3 | |a Signal plan transition is the process of changing from one timing plan to another. It begins when the first intersection starts adjusting signal timing plans and ends when the last intersection completes adjusting signal timing plans. The transition between signal timing plans is required because traffic patterns change during the day. Therefore, it is necessary to modify signal timing parameters offset, phase split, and cycle length for different expectations of traffic volume. This paper presents an alternative and new mathematical model to enhance the performance of traffic signals coordination at intersections during the transition phase. This model is oriented to describe the transition regarding coordination parameters in all intersections of an arterial road for minimizing the social cost during the transition phase expressed in function of costs due to delays, fuel consumption, and air emissions. An ant colony algorithm was designed, coded, and simulated to find the optimal transition parameters using available data. The model was evaluated based on its ability to minimize social costs during the transition period. Results showed that the proposed method performs better than traditional ones. | |
| 651 | 4 | |a United States--US | |
| 653 | |a Mathematical models | ||
| 653 | |a Cost function | ||
| 653 | |a Emissions | ||
| 653 | |a Optimization techniques | ||
| 653 | |a Phase transitions | ||
| 653 | |a Parameter modification | ||
| 653 | |a Traffic flow | ||
| 653 | |a Traffic models | ||
| 653 | |a Coordination | ||
| 653 | |a Ant colony optimization | ||
| 653 | |a Traffic congestion | ||
| 653 | |a Computer simulation | ||
| 653 | |a Efficiency | ||
| 653 | |a Vehicles | ||
| 653 | |a Signal processing | ||
| 653 | |a Traffic volume | ||
| 653 | |a Traffic signals | ||
| 653 | |a Traffic control | ||
| 653 | |a Design | ||
| 653 | |a Algorithms | ||
| 653 | |a Methods | ||
| 653 | |a Traffic planning | ||
| 653 | |a Design optimization | ||
| 653 | |a Externality | ||
| 653 | |a Optimization models | ||
| 653 | |a Traffic intersections | ||
| 653 | |a Energy consumption | ||
| 653 | |a Transportation planning | ||
| 653 | |a Economic | ||
| 700 | 1 | |a Cantillo, Victor |u Department of Civil and Environmental Engineering, Universidad del Norte, Atlantico, Colombia | |
| 700 | 1 | |a Moura, José Luis |u Department of Transport, Universidad de Cantabria, Cantabria, Spain | |
| 700 | 1 | |a Ibeas, Angel |u Department of Transport, Universidad de Cantabria, Cantabria, Spain | |
| 773 | 0 | |t Journal of Advanced Transportation |g vol. 2017 (2017) | |
| 786 | 0 | |d ProQuest |t ABI/INFORM Global | |
| 856 | 4 | 1 | |3 Citation/Abstract |u https://www.proquest.com/docview/2407644579/abstract/embedded/6A8EOT78XXH2IG52?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text |u https://www.proquest.com/docview/2407644579/fulltext/embedded/6A8EOT78XXH2IG52?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text - PDF |u https://www.proquest.com/docview/2407644579/fulltextPDF/embedded/6A8EOT78XXH2IG52?source=fedsrch |