Safety control method for intelligent driving on low-attached roads based on v2i

Abstract

The invention discloses a V2I-based intelligent driving safety control method on low-attached roads, which includes the following steps: roadside equipment collects images of the road surface; the roadside equipment processes the collected road images; The device encodes the processing result data to generate a message; the roadside device broadcasts the message to the surrounding predetermined range; the vehicle entering the predetermined range receives the message through the on-board LTE-V2X device, and releases the vehicle's information to the roadside device Position information, if the vehicle is within the predetermined range of several roadside devices at the same time, the vehicle receives the messages broadcast by each roadside device and fuses the received messages; the vehicle's intelligent driving control device The text is analyzed, and the security policy is adjusted according to the analysis results. The security policy is related to the low-attached road surface; the above steps are executed cyclically.

Description

technical field [0001] The present invention relates to the field of intelligent transportation, more specifically, to the safety control technology in the intelligent driving technology. Background technique [0002] Automobile intelligence is the direction and trend of the future development of automobiles. Autonomous driving or intelligent assisted driving is rapidly developing and popularizing. In addition to identifying road condition information (the status of other traffic participants), intelligent driving technology also needs to identify the state of the road surface. For intelligent driving, the identification of road conditions is no longer simply applied to automotive safety systems such as ABS and EPS, but will also be applied to every link of the perception planning system, decision-making system, and execution system of autonomous vehicles. [0003] The identification of road surface state includes parameters such as road surface type, road surface state, s...

AI Technical Summary

Problems solved by technology

However, at the current stage, smart driving cars are limited by the functional limitations of the perception system and the limited computing and processing capabilities, so it is difficult to identify the type of road ahead and the road adhesion coefficient

Coupled with the limited field of view of the car itself, when the driving speed is fast, it is unrealistic to rely solely on the vehicle's own detection to perceive the state of the road ahead. Therefore, the existing intelligent driving solutions cannot obtain the road on the vehicle's planned path in advance. Road Surface Condition and Road Adhesion Coefficient

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