Alternative Approach to Estimation of Critical Cornering Speed

Abstract

An alternative approach to the estimation of the critical cornering speed of large combination vehicles is presented. Existing techniques are based on analytical models subject to a series of simplifying assumptions, and do not explicitly consider grades and other three‐dimensional roadway features of the real problem. One result of this study indicates that these simplified models may overestimate critical cornering speed by as much as 50%. The proposed technique combines detailed simulation of the dynamics of the motion of large combination vehicles through a three‐dimensional roadway, with a Monte Carlo sampling of possible vehicle configurations and component mechanical properties to produce databases for statistical analysis. This approach is applied to the study of critical cornering speed at freeway‐to‐freeway connectors. Databases for several samples of vehicles are generated, and a series of regression models that predict critical cornering speed is created. Results indicate that these regression models may be used to predict critical cornering speed to a high degree of accuracy. Finally, critical cornering speeds estimated using these models compare reasonably with actual speed data collected at five freeway connectors.