On the required complexity of vehicle dynamic models for use in simulation-based highway design.

INTRODUCTION

This paper presents the results of a comprehensive project whose goal is to identify roadway design practices that maximize the margin of safety between the friction supply and friction demand. This study is motivated by the concern for increased accident rates on curves with steep downgrades, geometries that contain features that interact in all three dimensions - planar curves, grade, and superelevation. This complexity makes the prediction of vehicle skidding quite difficult, particularly for simple simulation models that have historically been used for road geometry design guidance.

METHOD

To obtain estimates of friction margin, this study considers a range of vehicle models, including: a point-mass model used by the American Association of State Highway Transportation Officials (AASHTO) design policy, a steady-state "bicycle model" formulation that considers only per-axle forces, a transient formulation of the bicycle model commonly used in vehicle stability control systems, and finally, a full multi-body simulation (CarSim and TruckSim) regularly used in the automotive industry for high-fidelity vehicle behavior prediction. The presence of skidding--the friction demand exceeding supply--was calculated for each model considering a wide range of vehicles and road situations.

RESULTS

The results indicate that the most complicated vehicle models are generally unnecessary for predicting skidding events. However, there are specific maneuvers, namely braking events within lane changes and curves, which consistently predict the worst-case friction margins across all models. This suggests that any vehicle model used for roadway safety analysis should include the effects of combined cornering and braking.

PRACTICAL IMPLICATIONS

The point-mass model typically used by highway design professionals may not be appropriate to predict vehicle behavior on high-speed curves during braking in low-friction situations. However, engineers can use the results of this study to help select the appropriate vehicle dynamic model complexity to use in the highway design process.