IndexTraffic SimulationMacroscopic Traffic SimulationMicroscopic Traffic SimulationFuel-Efficient MethodsTraffic SimulationSome factors such as traffic conditions have a great influence on the driving strategy vehicle control. In this thesis, we will try to come up with an eco-driving strategy that aims at a better way to reduce fuel consumption. The feature of this strategy is to create a preview decision using traffic simulation. This is due to two aspects. The first is reality: the designed curve is very different from reality, so we need to simulate traffic and get a better description of fuel consumption. And another is economical: simulating real road conditions instead of real racing, will reduce many costs. In other words, the complexity of traffic flow and the difficulty of experiencing world traffic in real life make computer simulation a critical tool in traffic analysis. Meanwhile, traffic simulation models are used to monitor data for traffic planning. Through analysis, traffic scenarios can have more variations and can actually dominate the simulation time. In general, there are three types of traffic simulation models: microscopic, mesoscopic and macroscopic. The microscopic and macroscopic traffic simulations are explained below. This thesis uses the microscopic traffic flow model and describes it in detail. Say no to plagiarism. Get a tailor-made essay on "Why Violent Video Games Shouldn't Be Banned"? Get an Original EssayMacroscopic Traffic SimulationA macroscopic traffic flow model is a mathematical traffic model that establishes the relationship between traffic flow characteristics such as density, flow, average speed of a traffic flow, etc. They usually face a wide range of problems, regardless of individual driving behavior. These models are typically implemented by integrating several microscopic traffic flow models and converting single entity-level features into comparable system-level features. "Rigorous Derivation of Nonlinear Scalar Conservation Laws from Follow-the-Leader Models via the Many-Particle Limit". Archive of mechanics and rational analysis. The purpose of macroscopic models is to describe the most important property, i.e. the dynamics of the traffic flow. According to various experiments, several macroscopic traffic flow models are simple enough for real-time simulation of large traffic networks, while being sufficiently robust to effectively describe the main variables of the total traffic flow and their dynamics. Overall, this model can determine the average travel time, average fuel consumption and emissions associated with traffic flow. The macroscopic traffic model is not very computationally demanding. Furthermore, the computing demand does not increase with increasing traffic density, i.e. it does not depend on the number of vehicles in the network. Meanwhile, this model is less sensitive to small disturbances in the input. In general, the macroscopic traffic model is applied to short-term forecasts in network-wide coordinated traffic management and is suitable for the development of dynamic traffic management and control systems designed to optimize transportation systems and can be available to estimate and forecast average traffic flow operations. Microscopic traffic simulation Contrary to modelsMacroscopic, microscopic traffic flow models simulate individual vehicle units, so the models focus on dynamic variables representing microscopic properties such as the position and speed of individual vehicles. The microscopic simulation describes the system entities and their interactions with high levels of detail. A microscopic model strives to analyze traffic flow by modeling the influence between individual units such as driver-driver and driver-road respectively. Microscopic traffic simulation has proven to be a useful tool for carrying out these analyses. This is due not only to its ability to capture the entire time-related traffic flow dynamics, but also to its ability to manage behavioral models that take into account drivers' reactions to different traffic phenomena. VISSIM software is part of PTV Vision and provides microscopic simulation methods to evaluate and solve various transportation problems. The main functions of VISSIM include vehicle tracking, lane changing and pedestrian movement as defined by the model. Vehicle following models are a form of stimulus-response model, where the response is the reaction of the driver (follower) to the movement of the vehicle immediately preceding him (the leader) in the traffic flow. As the traffic flow to be visualized and expressed becomes quite complex, the influences of planning concepts based on purely aggregate values ​​are difficult to analyze and understand. In this case, the only option that can draw reliable conclusions about traffic quality is to express road traffic for certain traffic plan measures through a visual representation. With the help of Vissim and other microscopic simulation software, it is possible to determine how drivers and pedestrians interact with each other in the entire transport network based on their stereotypical athletic behavior. Furthermore, the visualization of each traffic light, speed bump and conflict zones provides an overview of the traffic flow. Vissim is also able to refine the level of detail of the map as close to reality as possible so that connected models are displayed with the most realistic definition. Multiple ratings are available for online and offline analysis during the simulation. Another special feature is the display of animation in 2D or 3D, which provides the opportunity to immediately understand simulated traffic conditions and bridges the gaps between technical expertise and non-technical audiences. Microscopic traffic simulation has proven to be a useful tool for carrying out these analyses. This is due not only to its ability to capture the entire time-related traffic flow dynamics, but also to the ability to manage behavioral models that take into account drivers' reactions to different traffic phenomena. Fuel-Efficient Methods Automobiles need energy in the fuel to overcome various losses (air resistance, tire resistance, etc.) encountered during the driving process, as well as power vehicle systems such as the ignition or auxiliary system. Various strategies can currently be adopted to reduce the energy conversion loss between the chemical energy of the fuel and the kinetic energy of the vehicle. And driver behavior can also have a significant impact on fuel economy; maneuvers such as rapid acceleration and sudden braking will cost a lot of energy. Fuel efficiency depends on many vehicle parameters, including engine parameters, fuel performance, weight, aerodynamic drag and rolling resistance. In recent decades they have been.