Optimizing Lane Changing Safety: Development and Evaluation of Intelligent Decision-Making Algorithms

Abstract

Statistics Show That Driver Irresponsibility Is Mostly To Blame For Accidents, Particularly When A Driver Is About To Change Lanes Or Pass Another Car, Which Increases The Likelihood Of An Accident. Furthermore, Because Overtaking Involves Both Dynamic And Complex Functions As Well As The Challenging Task Of Implementing Control Strategies And Electronic Control Systems, Like Steering, Throttle, And Brake Control, It Is One Of The Most Challenging And Complex Functions For The Development Of Autonomous Driving Technologies. In This Thesis, A Safe Overtaking Technique For An Autonomous Vehicle Is Shown, Based On Model Predictive Control And Vehicle Dynamics. A Sensors Based Lane-Detection System Is Used To Estimate Tlc (Time To Lane Crossing) So That A Timely And Accurate Choice May Be Made Regarding Whether To Overtake Or Stay In The Lane. Overtaking Is One Of The Trickiest Maneuvers That Requires Both Lane Keeping And Lane Shifting. Next, Maintain The Smallest Possible Safe Distance While Selecting The Optimal Vehicle Controller, Such As Throttle, Brake, And Steering Angle. It Can Concurrently Guarantee The Maintenance Of Steering Velocity And Longitudinal Acceleration To Protect Drivers. In This Manner, The Study Involves The Integration Of Aem (Autonomous Emergency Maneuvering), Lkas (Lane Keeping Assistance System), And Acc (Adaptive Cruise Control) To Have More Accurate And Realistic Lane Changing, Lane Departure/Merging, And Overtaking Processes. The Vehicle Modes Is Imported From Carsim To Be Analyzed The Dynamics And Kinematics On Simulink. Later On, The System Is Validated By Carsim/Simulink Software Combined By Matlab. The Simulations Showed How Adaptable The Suggested Overtaking Judgment And Control Approach Was Under Different Driving Conditions. The Simulation Result Outcome The Desired The Vehicle Decision Action With Respect To The Scenarios Stated With Interaction With The Actor Vehicles And The Road Condition.