Self-driving vehicles will rely on cameras, sensors and artificial intelligence (AI) to recognize and respond to road and traffic conditions, but sensing is the most effective for objects and movement in the neighborhood of the vehicle. Not everything important in a car's environment will be caught by the vehicle's camera. Another vehicle approaching at high speed on a collision (碰撞) track might not be visible until it's too late. This is why vehicle-to-vehicle communication is undergoing rapid development. Our research shows that cars will need to be able to chat and cooperate on the road, although the technical challenges are considerable.

    Applications for vehicle- to-vehicle communication range from vehicles driving together in a row, to safety messages about nearby emergency vehicles. Vehicles could alert each other to avoid collisions or share notices about passers-by and bicycles.

    From as far as several hundred meters away, vehicles could exchange messages with one another or receive information from roadside units (RSUs) about nearby incidents or dangerous road conditions through 4G network. A high level of AI seems required for such vehicles, not only to self-drive from A to B, but also to react intelligently to messages received. Vehicles will need to plan, reason, strategize and adapt in the light of information received in real time and to carry out cooperative behaviors. For example, a group of autonomous vehicles might avoid a route together because of potential risks, or a vehicle could decide to drop someone off earlier due to messages received, a foreseen crowding ahead.

    Further applications of vehicle- to-vehicle communication are still being researched, including how to perform cooperative behavior.

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