Research On Economic Motion Planning Of Intelligent Vehicle Based On Road Slope

With the rapid development of automotive intelligence and network technology,intelligent vehicles can receive more comprehensive perception information,which has injected fresh vitality into the research of energy conservation and emission reduction of vehicles.In this paper,with the help of high-precision positioning technology,combined with vehicle dynamics and road slope information,the global economic reference speed is planned based on the high-efficiency zone of the power components of intelligent vehicles.Combined with the economic reference speed,the motion planner can complete the development of economic motion planning algorithm,so as to improve the fuel economy of intelligent vehicles.In order to improve the efficiency of calculation,the motion planning is decoupled to path planning and speed planning.The main content of this paper is divided into four parts:the planning of economic reference speed,the construction of speed planner,the construction of path planner,and the co-simulation verification of economic motion planning.In the research of economic reference speed planning,the vehicle longitudinal dynamics model and engine fuel consumption calculation model are established first.Then,the dynamic programming algorithm for solving economic reference speed is constructed from four aspects: stage division and discretization,selection of state variables and control variables,definition of state transition equation and construction of cost function.In order to solve the problem that the dynamic programming algorithm takes too long time,the time-consuming optimization of the dynamic programming algorithm is carried out from three aspects: dimensionality reduction,road network reconstruction and optimization of sampling strategy,and vehicle dynamics constraints for state transitions.The optimization effect has been verified.Finally,the simulation of the typical road segment and the real road segment are carried out respectively to verify the fuel-saving effect of the algorithm.And the fuel-saving mechanism of the economic reference speed is analyzed.In the research of speed planning,in order to clearly describe the problem of speed planning,the path planning result is used as the coordinate axis to transform the Cartesian coordinate system into the natural coordinate system.Moreover,the trajectory prediction of dynamic obstacles is carried out with the constant v model under the natural coordinate system,and the mapping relationship between S-L graph and S-T graph is found to generate the S-T projection graph.Considering that the solution space of the S-T projection graph is often non-convex,this paper designs a vehicle longitudinal behavior decision-making algorithm based on dynamic programming combined with the economic reference speed.The non-convex solution space is transformed into convex solution space by making the mark of overtaking or giving way for each obstacle.Finally,in the safety domain,applying the quadratic programming method,the speed planning is carried out under the guidance of the economic reference speed.In the research of path planning,the transformation from the Cartesian coordinate system to the Frenet coordinate system is completed with the centerline of the lane as the coordinate axis.By analyzing the minimum safety distance required by vehicles when overtaking or changing lanes,the safety distance model for driving is established.Then,using the constant v model in the Frenet coordinate system,the algorithm predicts the trajectory of the obstacle and generates the collision risk area to complete the configuration of the S-L graph.Considering that the solution space of S-L graph is often non-convex,this paper designs a lateral behavior decision-making algorithm based on dynamic programming.The non-convex solution space can be transformed into a convex solution space by determining the left or right detour mark for each collision risk area.Finally,aiming at safety and comfort,the objective function and constraints are constructed,and the path planning is carried out based on the quadratic programming method.In the co-simulation verification of economic motion planning,the scheme of "MATLAB/Simulink + SCANe R" is adopted to build the co-simulation platform and formulate the economic driving strategy.The effectiveness of the motion planner is verified by the simulation of lane changing condition and overtaking condition.In addition,this paper designs the highway scene under good traffic condition,and simulates and demonstrates the fuel economy of economic motion planning.The simulation results show that the economic motion planning algorithm proposed in this paper is effective,and the fuel economy can be improved under the condition of good road traffic.