Calibration Measurements and Computational Models of Sensors Used in Autonomous Vehicles

Unsuccessful overtaking maneuvers on two-lane rural roads are one of the major causes road accidents in 21st century. The complexity this maneuver merits adoption a thorough method for developing proposed assistance system to prevent and consequently reduce high number fatalities associated economic costs. This study aims introduce an intelligent Driver Overtaking Assistance System (DOAS) assist drivers performing safely. also will assess impact all influential variables related driver, vehicle, traffic, road, surrounding environment. In momentary driving situations, DOAS uses communicated information via Hello beacon messages (HBM) set input sensors measure possibility preceding vehicle(s) proactively by considering whether distance gap oncoming vehicle is sufficient overtaking. Besides, vehicle-based safety based collection contextual from vicinity acquire relevant regarding ambient environment vehicles involved To do this, Bayesian Network (BN) model maneuvers. work presented shows accuracy promising results aiding safe overtaking, with significant improvements roads.