Vehicle sensor concurrent monitoring method facing road conditions

Abstract

The invention provides a vehicle sensor concurrent monitoring method facing road conditions / the method is finished through coordination of a vehicle node which carries a sensor and a road side base station. The vehicle node sends data collected by the sensor and observation data obtained by fusion of local data to a local road side base station, the road side base station receives and stores the observation data and decides whether concurrent monitoring is required to be started, the vehicle sensor data based concurrent event monitoring process can be started if conditions are met, vehicle sensor data of position correlation, time correlation and driving behavior correlation are mined, after the data correlation is obtained, a voting weighting method is used for processing, the road side base station judges whether a road condition event occur in a local sub-cell according to processing results, and if the event can be determined, the road side base station issues the event.

Description

technical field [0001] The present invention relates to the field of cooperative information processing and event monitoring of vehicle-mounted self-organizing sensor networks, and more specifically, relates to a vehicle that travels on urban roads and carries various types of sensor nodes to collect data related to road conditions and events, and communicate with roadside The base station cooperates to carry out collaborative data processing related to location, time, and vehicle driving behavior, so as to accurately and effectively monitor whether there are abnormal road conditions in the road area, such as road potholes, wet slippery, and stranded. Background technique [0002] With the popularization of automobiles, the development of sensor technology and wireless communication, various types of intelligent sensor node devices can be installed on road vehicles to perceive physical quantities related to driving conditions. Mobile network connection to form a self-organiz...

AI Technical Summary

Problems solved by technology

[0005] The implementation method of collaborative monitoring technology is related to specific applications, and the monitoring method of wireless sensor network cannot be well adapted to the application environment of vehicle network

In the vehicle sensor network environment, due to the high mobility of vehicles and the complexity of urban road traffic conditions, the topology of the mobility network changes rapidly; in addition, road traffic and vehicle driving are affected by the natural environment, road terrain characteristics and human factors. etc., there are problems such as noise and sparse data in the information collected by vehicle nodes, which is prone to false alarms, resulting in low monitoring accuracy

Some researchers have proposed artificial intelligence-based methods for event monitoring in mobile ad hoc networks and wireless sensor networks, through local node collaboration, using machine learning, support vector machines, Bayesian neural networks, or using hidden Markov models etc., to extract and classify event features, judge the probability of event generation, and realize event monitoring; when these event monitoring methods are used in the vehicle network application environment, it is necessary to train the data set in the specific environment of road vehicles in advance, due to road traffic and vehicle Driving is greatly affected by the natural environment, road terrain characteristics, and human factors, and the training of real-time data sets is difficult, which directly affects the performance of the event monitoring system; these methods have high computational complexity and cannot be well adapted to wireless vehicle networks. Distributed network environment with self-organization and mobility

It is difficult to accurately and effectively monitor events if inappropriate on-board sensor data is used for coordination, or wrong prior information is given on its performance, error statistics, etc.

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