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This report describes results from a series of experiments using the virtual bumper collision avoidance algorithm implemented on a Navistar tractor cab. The virtual bumper combines longitudinal and lateral collision avoidance capabilities to control a vehicle in normal and emergency situations. A programmable boundary, the virtual bumper, defines a personal space around the host vehicle. Researchers used a radar and a laser range sensor to sense the location of vehicles in front of the truck. Target vehicles that enter the truck's personal space impose a virtual "force" on the host, which in turn modifies the vehicle's trajectory to avoid collisions with objects in the field of view. Researchers tested the virtual bumper longitudinal controller under different driving situations and at different speeds. The experiments included several scenarios: Adaptive Cruise Control, the truck performing a critical stop for a stationary target vehicle, and situations that simulate stop-and-go traffic. Results from the virtual bumper longitudinal experiments were favorable. The algorithm demonstrated robustness to sensor noise and the ability to maintain a safe headway for both normal and emergency driving scenarios. Researchers currently are improving the sensing technology and incorporating a road database, which contains roadside features to greatly reduce, if not eliminate, false target detection.

The SAFETRUCK program focuses on preventing accidents on rural highways, especially those associated with run-off-the-road incidents and driver fatigue, by giving the vehicle the ability to steer to the side of the road and come to a safe stop if the driver falls asleep or is otherwise incapacitated. Researchers have equipped a Navistar 9400 series class 8 truck tractor with the sensors and control computers necessary to perform this task. Designing the controller that will steer the truck requires a mathematical model of the lateral response of the truck to steering inputs. In this project, researchers developed a lateral dynamic model by incorporating second order dynamics into the steering axle tires. Simulation of the resulting models indicated dynamic behavior that was close to the experimental data for speeds between 15 and 30 miles per hour. This is the first time that a lateral dynamic model of a truck has been experimentally verified. Both models, however, resulted in experimentally determined values for steering axle cornering stiffness that were considerably smaller than published values for the Goodyear G 159 tires on the truck.

This report summarizes the work performed during the 18-month period ending in December 1997. Researchers investigated the use of differential global positioning systems (GPS), inertial measurement, and other sensing technologies as the basis of a system that would prevent crashes. Such a system attempts to control the vehicle if it leaves the lane because the driver is incapacitated. The report includes in its appendices related work on driver fatigue and a bibliography on the effect of drugs and alcohol on driving behavior. The long-term goal of this research involves development of a "driver-centered" vehicle control system capable of providing lane-keeping feedback to the driver, and, if necessary, of imposing aggressive intervention strategies to take over control of the vehicle, steer it to a safe position on the shoulder, and stop it. This research also targets the development of "driver assistive" technologies--such as Heads Up Display and torque feedback supplied by the steering wheel--which provide information to the driver without necessarily requiring computer control of the vehicle. The highlight achievement during this funding period has been the successful demonstration of a GPS-based automated lane-keeping mode of a tractor-trailer on the Minnesota Road Research Project (Mn/ROAD) test track. The report concludes with a strategy for pursuing future deployment.