Research On Layout Optimization Method Of Traffic Detecto Location Based On Road Segment Importance

Traffic detection point is one of the main technical means for traffic information collection.The location and quantity of the traffic detection in the road network are the key to affect the quality of traffic information collection.It is of great significance for reasonable traffic detection point layout to construct the traffic basic database and improve the traffic management level.Due to the different aspects of the existing research on traffic detection location,the application scenarios of the layout methods are not universal.Moreover,unreasonable layout scheme leads to a large waste of funds,and the benefits of the detection points are also reduced drastically.Therefore,how to optimize the layout of traffic detection location in the regional road network and improve the accuracy and integrity of traffic information collection is of great significance for improving the construction and management of the road network.Aiming to solve the problems including insufficient optimization of incomplete data acquisition,single application scenario,and low efficiency of detection location in existing traffic detection point layout methods,this paper proposes an optimal layout method for traffic detection location based on the importance of road sections.The function and grade of each road segment in the road network is used as a quantitative indicator for traffic detection location.Based on the layout of traffic detection location is optimized as much as possible to maximize the benefits of traffic detection location and reducing the cost of traffic detection location layout.The main research contents of this paper are as follows:Considering the influencing factors of various aspects of road traffic network,this paper proposes a method for calculating the importance of road sections in terms of comprehensive social economic and functional characteristics.Firstly,the economic and social indicators of the location of the road segment are selected and analyzed.The principal component analysis method is used to screen and obtain the weight coefficient of each index.Then the economic and social importance of each road can be obtained by using the gravity model to distribute the node importance.With regard to the functional characteristics,this paper selects the length of the road segment,the number of lanes,the design speed and the traffic capacity as the evaluation index.Employing the multi-attribute decision-making method,the weight coefficient of functional characteristics can be computed.Finally,according to the mean variance method,the comprehensive importance of the road section is obtained.Based on the analysis of the influencing factors and layout basis of the traffic detection location,the method of layout for traffic detection location based on the importance of the road sections are put forward.After that the multi-objective optimization model of traffic detection location is established.The minimization of the number of location and maximization of total road importance are selected as objective functions,and the OD coverage principle is the constraint condition.Thus the detection point layout system can simultaneously acquire the traffic flow data of the whole road network and also used to the data of the OD matrix update and check requirements.Analyzing the failure rate and stability of traffic detection equipment,this paper introduce the influencing factor—the reliability of the detection equipment,and established a traffic detection point layout optimization model based on the reliability of the detection point.By setting the redundant decetion points in the road network,the data can be corrected and supplemented to ensure the reliability of the traffic detection location.The adaptive genetic algorithm(AGA),mostly to solve the multi-objective optimization problem are applied to the traffic detection point layout optimization problem.Taking the road network of Xiaoshan District in Hangzhou as the research case,the feasibility and effectiveness of this method can be verified by analyzing and discussing the test results.