Book Description

Recent reports from NHTSA state that approximately 37,000 fatalities occur each year as a result of traffic accidents. Around 6,000 of these fatalities are pedestrians and around 800 are bicyclists. Pedestrians and bicyclists are categorized as Vulnerable Road Users (VRU) in traffic. It should also be noted that the already high number of VRU fatalities is also increasing every year. In short, a serious safety risk for VRUs can be observed through these statistics where more pedestrian fatalities are present. This dissertation studies a pedestrian safety system for autonomous vehicles that non-autonomous vehicles can also partially utilize through warnings and speed profile recommendations provided to the driver. The safety system presented is designed to address both the safe stop condition and the emergency collision avoidance condition. Moreover, the approach was studied through several modules that covers aspects such as pedestrian path tracking and prediction, as well as real-world data processing for understanding human driver behavior and tuning the warning systems accordingly. On top of that, widely available mobile phones were utilized both in terms of their wireless communication and on-board sensor measurement capabilities which makes the safety system useful and available for a wider public at the current time while addressing dangerous no-line-of-sight or low visibility situations. For the cases where safe stopping is not possible or not preferable, a collision avoidance algorithm that executes modification of the pre-defined path based on the elastic band method for maneuvering around the pedestrian was proposed. Since autonomous vehicles are expected to have a pre-defined nominal path based on map information, modification of the pre-defined path is a more reasonable solution than creating a path from scratch because of the feasibility of the modified path and smooth departure from and connection to the pre-defined path. Pedestrians are treated as dynamic obstacles whose localization with respect to autonomous vehicles is improved for non-line-of-sight conditions and other problems in perception by using V2X communication. Moreover, with the proposed collision avoidance algorithm being calculated in very short time, modifying the path in each short time step with respect to new obstacle locations allows smooth tracking of the path even if the path is continuously modified while the vehicle is executing the maneuver. This results in a feasible approach for dynamic obstacles such as pedestrians. In order to have a more comfortable and safer collision avoidance behavior, speed profile modification was introduced to recalculate and modify the speed profile for the overall maneuver path while prioritizing the desired lateral acceleration. On top of the real-time implementation of the elastic band based modification to obtain a smooth avoidance path with moving pedestrians, with addition of the pedestrian location tracking, prediction and vehicle speed profile modification, a more complete and effective collision avoidance approach was achieved. Another topic studied in the dissertation, in the aspect of safe and robust path following control, was the proposed control structure where the disturbance observer was utilized in a path following loop for road curvature disturbance rejection. This structure is discussed in detail where the loop structure and derived equations were presented with frequency response and disturbance rejection analysis, as well as multiple simulation cases featuring different types of paths.