Vehicle Rollover Prediction for Banked Surfaces

Open Access
Lapapong, Sittikorn
Graduate Program:
Mechanical Engineering
Doctor of Philosophy
Document Type:
Date of Defense:
November 09, 2010
Committee Members:
  • Sean N Brennan, Dissertation Advisor
  • Sean N Brennan, Committee Chair
  • Henry Joseph Sommer Iii, Committee Member
  • Christopher Rahn, Committee Member
  • Eric Todd Donnell, Committee Member
  • Karen Ann Thole, Committee Member
  • Rollover Prediction
  • Vehicle Rollover
  • Vehicle Dynamics
  • Vehicle
  • Zero-Moment Point
Rollover accidents are one of the leading causes of death on the highway due to their very high fatality rate. A key challenge in preventing rollover via chassis control is that the prediction of the onset of rollover can be quite difficult, especially in the presence of terrain features typical of roadway environments. These road features include superelevation of the road (e.g. road bank), the median slope, and the shoulder down-slope. This work develops a vehicle rollover prediction algorithm that is based on a kinematic analysis of vehicle motion, a method that allows explicit inclusion of terrain effects. The solution approach utilizes the concept of zero-moment point (ZMP) that is typically applied to walking robot dynamics. This concept is introduced in terms of a lower-order model of vehicle roll dynamics to measure the vehicle rollover propensity, and the resulting ZMP prediction allows a direct measure of a vehicle rollover threat index. Both simulation and field experimental results show the effectiveness of the proposed algorithm during different road geometry scenarios and driver excitations.