Vehicle Lane-Changing Safety Pre-Warning Model under the Environment of the Vehicle Networking

Lane-changing behavior is one of the most common driving behaviors while driving. Due to complexity its operation, vehicle collision accidents are prone occur when changing lanes. Under environment networking, drivers can obtain more accurate traffic information in time, which be great help terms improving lane-changing safety. This paper analyzes core factors that affect safety vehicles lanes, establishes weight model influencing using analytic hierarchy process (AHP), and obtains calculation method (LCBFs). Based on fuzzy reasoning theory, headway between adjacent target lane was examined, logic models were established for both situations (i.e., change left right lane). The tested via simulation experiments, test results showed have a better warning effect (LCBF = 1.5), with an accuracy than 90%. Thus, this provide theoretical support warnings lanes sustainable development transportation