Research On The Key Technology Of Urban Traffic Flow Cumulative Energy Consumption And Coordinated Control Methods

The energy consumption of urban road traffic system is directly affected by vehicle performance, and also closely related to the characteristics of the city road network, traffic flow condition, traffic control and management mode and other factors. In this paper, vehicle traffic flow cumulative energy consumption has been analyzed and researched, the internal mechanism of the cumulative energy consumption under urban road traffic environment has been researched, and the cumulative energy consumption analysis model based on the city road network traffic condition has been established, then the city traffic network control strategy based on optimal energy consumption oriented from the perspective of traffic management and individual traveler respectively. The main research contents of this paper are as follows:1. Through the analysis of factors affecting traffic energy consumption, the conversion method of vehicle equivalent fuel consumption has been used to study the cumulative energy consumption model of different driving conditions, such as at a constant speed, acceleration, deceleration and idle speed and so on, and the vehicle cumulative energy consumption model of urban ring intersection and no signal control intersection of the main road priority have been established respectively. On the basis of the vehicle’s deceleration delay, stop delay at the intersection, and combined with the law of energy consumption under different driving conditions, the cumulative energy consumption model of signalized intersection in the unsaturated state and over saturated state have been created. The relationship between cumulative energy and road traffic condition has been researched and the section cumulative energy consumption model based on the traffic saturation has been analyzed.2. Based on the analysis of the influence of roads and intersections traffic operation status on traffic energy consumption, according to the traffic status and vehicle fuel consumption rules, transportation energy area identification based on the traffic condition has been researched, and the seven parameters which can reflect the energy consumption status of section and intersection, have been respectively given to be as the indicators of traffic energy consumption area division, then the indicators has been quantified and studied on the threshold, the traffic state identification model of energy consumption area has been established, and the threshold level definition of high, middle and low energy consumption area have been also given.3. The network traffic cumulative energy consumption model has been established, and the balance network signal optimization model of optimal energy consumption in the low-energy zone has been established by using the bi-level programming model, combining with the traffic network energy consumption and traffic control parameter optimization, putting the network to minimize energy consumption as the optimization goal, then the feasibility of the model has been proved through the analysis of examples.4. The traffic consumption pattern under the high-energy condition has been researched by the introduction of the traffic flow macroscopic fundamental diagram, and the traffic flow balance equation at the high-energy zone boundary has been established, the estimation model of the macro network traffic energy has been also given; on this basis, the highest rate of vehicle complete operation and the lowest energy consumption at the same time have been put as the optimization goal, then the dual objective programming model of boundary control has been established, and the simulation analysis has been carried out combined with the example. The simulation results show that the optimization control method of the high-energy zone boundary, which the highest rate of vehicle complete operation and the lowest energy consumption, can effectively reduce the network fuel consumption, especially at the time with a large amount of traffic demand, the network evacuation capability can be improved and fuel consumption can be reduced at the same time, the macro network traffic density can be also effectively balanced.5. From the perspective of traveler, the function of the vehicles’ generalized travel cost which considers the energy consumption and congestion pricing have been established, the function of the bus generalized travel cost which considers the comfortable consumption have been established and the total system energy consumption which considers two kinds of traffic travel mode has been established. Based on the impact of energy consumption on route choice behavior, the bi-level programming model whose upper objective function is the minimum travel time under energy consumption constraints has been established. Combined with the example analysis, it is verified that the bus sharing rate can be improved under the two conditions of different energy-saving targets and road congestion pricing, the amount of each road vehicle travel can also be balanced, then traffic energy consumption will be reduced.