Open AccessPrediction of Vehicle Braking Deceleration Based on BP Neural Network
Author(s) -
Shen Zhang,
Da Li,
Feng Du,
Tao Wang,
Yunpeng Liu
Publication year - 2022
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/2183/1/012025
Subject(s) - acceleration , artificial neural network , automotive engineering , computer science , braking distance , engine braking , control theory (sociology) , simulation , engineering , artificial intelligence , brake , control (management) , physics , classical mechanics
This paper first introduces the BP neural network, upgrades and optimizes the neural network according to the actual demand, and then establishes the prediction model of vehicle braking deceleration according to the relevant parameters affecting vehicle deceleration. According to the vehicle relative distance, vehicle relative speed, front vehicle acceleration, collision time and lateral distance, the vehicle deceleration is predicted and analyzed. After data verification, the vehicle braking deceleration prediction model is more accurate for vehicle deceleration prediction, and the established prediction model is effective.