Prediction and early warning system of safe vehicle speed in curves based on multiple regression analysis

Abstract

The invention relates to a vehicle curve safety vehicle speed predication and pre-warning system based on multiple regression analysis. The vehicle curve safety vehicle speed predication and pre-warning system based on the multiple regression analysis comprises a test data collection module, a test data pre-processing module, a test data analysis module, a safety vehicle speed model database, a curve information module, a vehicle type judging module and a curve safety vehicle speed pre-warning module. According to the vehicle curve safety vehicle speed predication and pre-warning system basedon the multiple regression analysis, desired test data are collected, multiple linear regression analysis is carried out on processed test data to obtain a critical transverse adhesion factor model and a transverse load transfer rate model, and the critical transverse adhesion factor model and the transverse load transfer rate model are converted by using a formula to obtain a safety vehicle speedmodel. Collected curve pavement data and vehicle types are input into the safety vehicle speed model database. A curve safety predicated vehicle speed is obtained after calculation and displayed on an LED display screen at the entrance of a curve to warn a driver of a curve safety passing vehicle speed. According to the vehicle curve safety vehicle speed predication and pre-warning system based on the multiple regression analysis, the influences of multiple factors on the curve safety vehicle speed are comprehensively considered, and the curve safety vehicle speed can be accurately predicatedto provide a safety pre-warning vehicle speed for the driver so that the vehicle stably and safely runs through the curve.

Description

technical field [0001] The invention belongs to the technical field of traffic safety, and relates to a safety speed prediction and early warning system for vehicle curves based on multiple regression analysis Background technique [0002] Curve traffic accidents are one of many types of traffic accidents, which have the characteristics of frequent occurrence, high probability of occurrence and great harm. According to the annual statistical report on road traffic accidents in 2016, there were as many as 39,000 traffic accidents on curves throughout the year, and the number of deaths was as high as 14,800, accounting for 18.36% and 23.47% of the total number of road traffic accidents respectively. Most traffic accidents are caused by speeding. Therefore, it is necessary to develop a curve speed warning system, which can reduce the rollover and sideslip caused by vehicle overspeed, and reduce the occurrence of traffic accidents. [0003] In the existing technology, the Chin...

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Problems solved by technology

However, the disadvantage of this patent is that the safe vehicle speed is obtained through simple calculation of the formula, and the reliability and safety are low; and the total mass of the vehicle has a serious impact on the rollover of the truck, and this patent does not consider the impact of the total mass of the vehicle on the vehicle

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