Route Control and Behavior Decision of Intelligent Driverless Truck Based on Artificial Intelligence Technology
Feng Wang, Zhaofeng Zhang
Abstract
With the increase in global car ownership, the demand for traffic safety is very strong. Research shows that drivers account for more than 90% of global traffic accidents. Driverless cars can reduce traffic accidents caused for these reasons and greatly improve traffic safety. At the same time, driverless real‐time path planning can select the best driving route for vehicles, reduce traffic congestion, and improve the efficiency of transportation. To sum up, driverless vehicles are considered an important solution to ensure traffic safety, improve traffic efficiency, reduce energy consumption and pollution, and change travel mode. An intelligent driverless vehicle is a key component of the intelligent transportation system, which organically combines various functions such as. Among them, path tracking and motion control play a very important role in intelligent driverless technology. At the same time, accurately tracking the desired feasible path and stable motion control are the basis of intelligent unmanned driving. Based on this, this paper uses artificial intelligence technology to study the path control and behavior decision‐making of intelligent driverless trucks, and an improved tracking control method is proposed. Through this improved method, the intelligent unmanned vehicle can track the desired feasible path under different curvatures more accurately and stably. Finally, through the road test experiment of the intelligent unmanned vehicle experimental platform in the actual environment, the effectiveness of the scheme design and related algorithms of intelligent unmanned vehicle motion control in this paper is verified.