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Recent research into the phenomenon of tire hydroplaning has concentrated on the effects of possible path clearing of the rear tires by the front tires. When this occurs, the rear tire behavior and hydroplaning properties will be different from what would occur had the tire been running in an undisturbed flow field. In the present work, we modify rear tire properties to simulate the path clearing effect and utilize the SIMON/HVE suite of simulation programs with a standardized double lane change maneuver to examine path clearing potential during transient vehicle behavior.

This research compares the responses of a vehicle modeled in the 3D vehicle simulation program SIMON in the HVE simulation operating system against instrumented responses of a 3-axle tractor, 2-axle semi-trailer combination. The instrumented tests were previously described in SAE 2001-01-0139 and SAE 2003-01-1324 as part of a continuous research effort in the area of vehicle dynamics undertaken at the Vehicle Research and Test Center (VRTC). The vehicle inertial and mechanical parameters were measured at the University of Michigan Transportation Research Institute (UMTRI). The tire data was provided by Smithers Scientific Services, Inc. and UMTRI. The series of tests discussed herein compares the modeled and instrumented vehicle responses during quasi-steady state, steady state and transient handling maneuvers, producing lateral accelerations ranging nominally from 0.05 to 0.5 G's.

Traditional vehicle simulations use two methods of modeling driver inputs, such as steering and braking. These methods are broadly categorized as “Open Loop” and “Closed Loop”. Open loop methods are most common and use tables of driver inputs vs time. Closed loop methods employ a mathematical model of the driving task and some method of defining an attempted path for the vehicle to follow. Closed loop methods have a significant advantage over open loop methods in that they do not require a trial-and-error approach normally required by open loop methods to achieve the desired vehicle path. As a result, closed loop methods may result in significant time savings and associated user productivity. Historically, however, closed loop methods have had two drawbacks: First, they require user inputs that are non-intuitive and difficult to determine. Second, closed loop methods often have stability problems.

Deteriorated roadway surfaces (potholes) encountered under everyday driving conditions may produce external vehicle disturbance inputs that are both destabilizing and highly transient. We examine vehicle behavior in response to such inputs through simulation. Idealized pothole geometry configurations are used to represent deteriorated roadway surfaces, and as environments in the HVE simulation suite of programs. Differences in vehicle response and behavior are cataloged, and the potential for destabilized vehicle behavior is examined, particularly under conditions in which only one side of the vehicle contracts the pothole. Vehicle types used in the simulation ensemble represent three classes of vehicles: a sedan, a sports car and an SUV. Results show that many combinations of vehicle speed, vehicle type and pothole configuration have essentially no destabilizing effects on the vehicle trajectory.

Roadway tractive capabilities are an important factor in accident reconstruction. In the absence of full-scale experiments, tire/road coefficient of friction values are sometimes quoted from reference textbooks. For the various types of road construction, the values are given only in the form of a wide range. One common roadway type is oil-and-chip construction. We examine stopping distances for newly-rocked oil-and-chip roads vs. similarly constructed roads that have been traffic-polished. The examination was conducted through full-scale braking experiments with instrumented vehicles. Results show that the differences between newly-rocked oil-and-chip roads when compared to roads that are traffic-polished are on the same order as vehicle, tire and ABS algorithm differences, and that full-scale testing is required for accurate μ-values.