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Keywords: traffic signal control, environmental load, vehicle carbon dioxide emissions, random search method, traffic control system In Japan, carbon dioxide (CO 2 ) emissions caused by vehicles have been increasing year by year and it is well known that CO 2 causes a serious global warming problem. For urban traffic control systems, there is a great demand for realization of signal control measures as soon as possible due to the urgency of the recent environmental situation. This paper proposes a new signal control method for reducing vehicle CO 2 emissions on an arterial road.To deal with signal control concerning environmental load in an online traffic control system, two problems must be overcome.First, it is extremely difficult to measure the emissions directly in an existing traffic control system. We thus need a proxy for the emissions for optimizing signal control parameters such as cycle length, split and offset. This paper describes a model for expressing the emissions in term of two factors, namely the traffic delay and the number of stops a driver makes. Each factor is calculated based on traffic flow model as shown in Fig. 1. The emission data for regression is generated by a traffic flow simulator combined with CO 2 emissions estimation model of gasoline and diesel powered vehicles. Through multi-regression analysis on the arterial road, Sangyo-doro in Kawasaki, we obtained the following equation, E = 8.43 × 10 where E denotes the total CO 2 emissions on the road, and d l and s l are the traffic delay and the number of stops on link l, respectively.Second, E cannot be explicitly expressed by control parameters and optimal solutions are to be found by a search method. We implement a random search method for the real traffic control system and determine the solutions every five minutes. In the method, the optimization problem is presented by a string model. To achieve rapid convergence, we develop a method for determining the number of mutation points.In order to verify the advantages of our approach, we conduct experiments on the aforementioned arterial road over four periods. Each period consists of successive four weekdays from 6:00 to 18:00. In the first period, signal control was operated by the existing method, and in the three other periods, new signal control was adopted. The experiment results confirm the proposed method to be effective since it is able to reduce not only CO 2 emissions by twenty five percent but also congestion and travel time by thirty two and seventeen percent, respectively, compared to the existing method.
Keywords: traffic signal control, environmental load, vehicle carbon dioxide emissions, random search method, traffic control system In Japan, carbon dioxide (CO 2 ) emissions caused by vehicles have been increasing year by year and it is well known that CO 2 causes a serious global warming problem. For urban traffic control systems, there is a great demand for realization of signal control measures as soon as possible due to the urgency of the recent environmental situation. This paper proposes a new signal control method for reducing vehicle CO 2 emissions on an arterial road.To deal with signal control concerning environmental load in an online traffic control system, two problems must be overcome.First, it is extremely difficult to measure the emissions directly in an existing traffic control system. We thus need a proxy for the emissions for optimizing signal control parameters such as cycle length, split and offset. This paper describes a model for expressing the emissions in term of two factors, namely the traffic delay and the number of stops a driver makes. Each factor is calculated based on traffic flow model as shown in Fig. 1. The emission data for regression is generated by a traffic flow simulator combined with CO 2 emissions estimation model of gasoline and diesel powered vehicles. Through multi-regression analysis on the arterial road, Sangyo-doro in Kawasaki, we obtained the following equation, E = 8.43 × 10 where E denotes the total CO 2 emissions on the road, and d l and s l are the traffic delay and the number of stops on link l, respectively.Second, E cannot be explicitly expressed by control parameters and optimal solutions are to be found by a search method. We implement a random search method for the real traffic control system and determine the solutions every five minutes. In the method, the optimization problem is presented by a string model. To achieve rapid convergence, we develop a method for determining the number of mutation points.In order to verify the advantages of our approach, we conduct experiments on the aforementioned arterial road over four periods. Each period consists of successive four weekdays from 6:00 to 18:00. In the first period, signal control was operated by the existing method, and in the three other periods, new signal control was adopted. The experiment results confirm the proposed method to be effective since it is able to reduce not only CO 2 emissions by twenty five percent but also congestion and travel time by thirty two and seventeen percent, respectively, compared to the existing method.
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