Rollover Prevention

To prevent rollover accident and reduce the loss on highway traffic, the Center for Automotive Research and Intelligent Transportation of The Ohio State University conducted research programs to study rollover prediction and prevention.

In this project, on-road and untripped heavy duty vehicle rollover propensity is studied under characterization maneuvers. By system identification using data from TruckSim, both the complex nonlinear model and its simple version are given for a typical heavy-duty truck and ION, the off-road navigator from OSU team in Darpa Grand Challenge. Based on dynamic rollover prediction metric TTR (time-to-rollover), a hybrid control system is proposed and simulated in different driving scenarios. The maximal safe driving speed under certain steering input and the maximal safe steering angle at certain longitudinal speed are studied. The simulation results show that the proposed control strategy can effectively improve roll stability

Selected Bibliography

Yongjie Zhu, Ümit Özgüner “Investigation of ION and a heavy truck on rollover propensity and prevention,” Proceedings of the American Control Conference, New York City, Jul. 2007, pp. 1630-1635.

Hai Yu, Levent Guvenc and Ümit Özgüner, “Heavy Duty Vehicle Rollover Detection and Active Roll Control,” The 16th IFAC world congress, Prague, Jul. 2005.

Hai Yu, Ümit Özgüner, “Heavy truck trajectory matching and simulation with VDANL,” Proceedings of the 2003 American Control Conference, Denver, Colorado, Jun. 2003, pp. 4693-4698.

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