Bus intelligent network connection collision optimization system and method

Abstract

The invention discloses a bus intelligent network connection collision optimization system and method. The system comprises a vehicle-mounted terminal and an edge server; wherein the vehicle-mounted terminal comprises a data acquisition module, a first data transmission module, a vehicle-mounted data processing module and an interaction module; and the edge server comprises an object detection module, a decision optimization module and a second data transmission module. According to the invention, since the auxiliary driving technology is applied to a bus, and an edge server is arranged in a station on a bus line, data collected by a sensor in a bus driving scene can be processed in real time; cooperative processing is carried out according to the data, and an optimal driving decision is provided for a driver under the condition that the bus may collide; therefore, the minimization of the collision loss of the bus is realized, and the time delay of data analysis and processing is greatly reduced through network connection calculation, so that decision information has high real-time performance.

Description

technical field [0001] The invention belongs to the field of vehicle intelligent network security technology, and in particular relates to a bus intelligent network collision optimization system and method. Background technique [0002] In recent years, with the development of my country's economy, people's living standards have been continuously improved, and the number of domestic car ownership has continued to increase. This has also led to an increase in the complexity of the road traffic system and frequent bus driving accidents. For the large-scale urban public transportation such as buses, how to ensure the safety of driving as much as possible has become a social problem that cannot be ignored. [0003] At present, the academic community has proposed many driving assistance solutions for intelligent networked vehicles. Technologies such as multi-sensor data fusion, visual perception, and cooperative driving are widely used in the field of automatic driving of vehicle...

AI Technical Summary

Problems solved by technology

[0004] However, the amount of sensor data generated by autonomous driving or assisted driving is massive, and the computing resources and storage resources required by the deep neural network used in target detection and scene understanding are also huge.

At present, only the 5G mobile communication system deployed on the vehicle is difficult to meet the above-mentioned calculation amount, and the centralized cloud server deployed at the remote end communicates with the vehicle and provides computing services. Will bring huge pressure to the cloud computing center

[0005] At the same time, although the current academic research on vehicle collision avoidance has been very in-depth and the related technologies are relatively mature, most of the current research only considers how to avoid collisions.

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