Research On Active Braking Strategy Of Pedestrians Collision Avoidance In Urban Conditions

The development of smart cars is increasing rapidly,and the accompanying smart driving functions are becoming more and more abundant.The development of active and passive safety functions for drivers has always attracted much attention,and safety issues related to Vulnerable Road Users have gradually been paid attention to.In busy traffic,active safety functions equipped with cars can largely avoid traffic accidents,actually,Both drivers and vulnerable road users in the traffic environment need to be protected.The subject of this paper is to discuss the method of real-time assessment of collision risk index and decision of active braking timing under typical urban conditions.The main contents of this paper include: the estimation algorithm of the motion status of the host vehicle and pedestrian,the evaluation algorithm of the collision risk of the host vehicle,the active braking decision algorithm,and the response characteristics of the braking system.The Kalman filter algorithm based on the kinematics model is used to estimate the motion state of the host vehicle and pedestrians.The kinematic model of the host vehicle refers to the Constant Turn Rate and Acceleration motion model,and the pedestrian kinematic model refers to the Constant Velocity motion model.The transformation,based on the current coordinate system of the vehicle,derives the relational mapping matrix of the system state vector,and then constructs the correlation coefficient matrix in the Kalman filtering algorithm.Based on the results of estimating the pedestrian and host vehicle's motion,a collision risk assessment algorithm based on kinematics and geometry is designed to calculate the collision risk characteristic parameter—Time To Collision(TTC).Based on this characteristic parameter,a fuzzy logic decision algorithm is designed.Calculating the desired braking deceleration according to TTC at the present time.In order to match the control interface of the braking system in the simulation system,a first-order inertial pure hysteresis braking system response model was built based on the actual vehicle braking experimental data,and the braking deceleration and brake master cylinder pressure were established by data fitting The approximate relationship between them,thus linking decision expectations with brake execution.Drawing on the relevant test specifications for pedestrian collision avoidance in ENCAP,this article builds relevant test scenarios based on PreScan scenario modeling software,and develops related algorithm modules in conjunction with Matlab / Simulink to build a scenario-algorithm joint simulation platform,and finally completes Simulation test.In this paper,five typical test conditions(CPFA,CPNA,CPNC,CPLA,and CPTA)are designed.The active braking decision algorithm uses fuzzy logic decision.From the results of the simulation test,the pedestrian vehicle movement state estimation algorithm works well,the collision risk assessment algorithm can also feedback the current emergency state in time,and the active braking decision algorithm can continuously request a reasonable deceleration in the complete simulation test conditions.Next,the active braking decision algorithm for pedestrian collision avoidance designed in this paper can completely avoid collision.