Fig 1.
Intelligent autonomous vehicle system.
Fig 2.
Fundamentals of the PID control algorithm.
Fig 3.
Architecture of autonomous vehicles based on edge computing.
Fig 4.
Flow of the deviation detection algorithm.
Fig 5.
Procedures of the greedy algorithm.
Fig 6.
Membership functions of input and output variables (a) velocity deviation (b) acceleration deviation (c) brake pedal stroke change.
Table 1.
Fuzzy control rules.
Fig 7.
Basic flow of the path-tracing algorithm.
Fig 8.
Membership function of input and output variables (a) heading deviation (b) preview distance (c) steering wheel angle change.
Table 2.
Fuzzy control rules.
Fig 9.
Flow of the CAW algorithm.
Table 3.
Accuracy of two heuristic algorithms.
Table 4.
Running time of two heuristic algorithms.
Fig 10.
Experimental results of the vehicle control system (a) steering wheel angle curve (b) speed curve.
Fig 11.
Changing curves of the emergency braking speed.
Fig 12.
Model training results (a) Average prediction time (b) ROC curve.
Fig 13.
Simulation results of anti-collision of front vehicle at rest (a) comparison between actual distance and expected distance (b) comparison between actual acceleration and expected acceleration (c) comparison of two vehicle speeds.
Fig 14.
Anti-collision simulation results of the target vehicle driving at a constant speed (a) comparison between expected distance and actual distance (b) comparison between expected acceleration and actual acceleration (c) speed comparison between the two vehicles.
Fig 15.
Anti-collision simulation results of the target vehicle’s emergency deceleration (a) Comparison between actual distance and expected distance (b) Comparison between actual acceleration and expected acceleration (c) Comparison of two vehicle speeds.