Collision prediction method based on vehicle distance probability distribution for internet of vehicles

The invention discloses a vehicle collision prediction method based on vehicle distance probability distribution under a highway model. The method includes the steps of a vehicle periodically (under 10Hz) broadcasts current motion statuses Beacons (speed, acceleration and GPS); the density of vehicles in the surrounding environment is dynamically calculated to build a vehicle distance distribution probability model; a minimum safety distance required to avoid collision when two adjacent vehicles emergently brake is dynamically calculated according the motion status of one vehicle and the motion status of the adjacent vehicle ahead; the collision probability (the probability for the vehicle distance being smaller than the minimum safety distance) of the two adjacent vehicles is calculated according to vehicle distance probability distribution; a multi-vehicle collision Markov chain and a state transition matrix are established, and expectation for the number of vehicle collisions on the whole section at certain time is estimated. The method is high in innovation level and extensibility; the defects of poor GPS data precision and instability in the current vehicle-location-based collision prediction algorithm are well made up; the method plays an excellent role especially in GPS satellite signal blind areas and has promising application prospect.