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Advanced Traffic Signal Control Algorithms, PB2014-108745.
| 题名： | Advanced Traffic Signal Control Algorithms, PB2014-108745. |
| 作者： | Winckler, A. |
| 关键词： | Annealing; Automatic Traffic Control; Characteristics; Combinations; Comprehensive Experiments; Cycle Length Optimization; Genetic Algorithms; Iterative Approaches; Mathematical Model; Problem Algorit |
| 摘要： | This research is aimed at reducing fuel consumption in situations where the car is facing multiple traffic signals in a row on its route. Recent studies show that it is possible to reduce the fuel consumption by 12% by adjusting the driving strategy using Signal Phase and Timing (SPaT) information. However, these results are based on simulations. These results are further corroborated by the results reported in(Asadi, 2011) (Mahler, 2012). The main goal of this project is to build a prototype system that shows that it is possible to reduce the fuel efficiency in the above mentioned situations. Therefore an in-vehicle system computes a speed recommendation - based on current SPaT information - and provides it to the driver on a graphical interface. Based on this recommendation the driver should be able to adjust his/her driving speed resulting in improved fuel consumption. In the first field test, the position data of the vehicle is sent to a second system called Adaptive Priority for Individual Vehicle (APIV). APIV is an operational strategy that adapts signal timing to facilitate the movement of individual vehicles through signalized intersections. While the main focus of the speed recommendation system is on reducing fuel consumption, the prime focus of APIV is on reducing the number of stops at red traffic and reduce fuel consumption. In addition APIV helps in reducing the number of stops at red traffic and associated intersection delays which leads to reduced travel time. Comprehensive field tests using a BMW vehicle showed that significant fuel savings are possible using the APIV. |
| 报告类型： | 科技报告 |
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