Research On Intelligent Vehicle Decision-making Based On Pedestrian Intention Recognition

In today’s society,the atmosphere of energy shortage and environmental pollution,the wave of deep learning and artificial intelligence,and the great transformation of the automotive industry all promote the development of intelligent vehicles.Unmanned vehicle is an important part of intelligent vehicle,behavior decision-making is one of its three core technologies,This paper focuses on Intelligent Vehicle decision-making method based on pedestrian intention recognition.Firstly,human pose estimation is studied.The significance and methods of human pose estimation are briefly analyzed;the theoretical algorithm of human pose estimation is studied,Including: neural network structure、key point detection confidence map、part affinity field of key point connection、applying part affinity field to multi-person analysis;pose estimation for human detection in different scenes is realized.Secondly,a method for detecting pedestrian intentions is proposed.Feasibility of pedestrian intentions detection is studied based on human pose estimation;feasible behavioral intention classification method is adopted;a general detection process is proposed for specific exploration;and the current evaluation scheme is analyzed.Thirdly,the experimental platform of intelligent vehicle decision-making is built.Build a simulation experiment platform based on an electric vehicle;the overall framework of the platform consists of four parts: environment perception module,upper computer decision module,lower computer control module and vehicle execution module;upper computer based on Ubuntu is used for decision-making;lower computer is developed based on microcontroller STM32F103ZET6,which communicates through serial port;The design of vehicle speed control part and braking part depends on the DAC and TIM peripherals of the microcontroller.Finally,the simulation experiment of vehicle intelligent decision-making is completed.Make pedestrian intention dataset as data support for decision-making;the decision-making model based on neural network is established through training and testing of sample data;connect the above process ideas with vehicle control module to form an intelligent vehicle decision-making system.