Emergency lane change optimization control of intelligent inspection vehicles on highways in 5G network environment

To address the issues of low minimum safe distance maintenance rate, low control success rate, and long control response time associated with traditional control methods, an optimized emergency lane change control approach for intelligent inspection vehicles on highways within a 5G network environment is proposed. The fifth-degree polynomial programming is utilized to design the emergency lane change trajectory of the intelligent inspection vehicles. In the 5G network environment, the information regarding the emergency lane change trajectory of the inspection vehicles is transmitted. This information is then input into a BP neural network PID controller, aiming to optimize the emergency lane change control of the intelligent inspection vehicles on highways. Experimental results indicate that the proposed method can achieves a maximum minimum safe distance retention rate of 98.91%, a control success rate ranging from 95.2% to 98.1%, and a minimum control response time of 0.43s.