Rollover speed prediction on curves for heavy vehicles using mobile smartphone

Inappropriate speed selection on a curved road is a main cause of rollover accidents for heavy vehicles due to their relative higher centers of gravity, comparing with those of passenger cars. Traditional driving safety improvement methods on curves include static/dynamic roadside speed limit signs that lack individual vehicle's characteristics, and the high-cost anti-rollover stability control systems that cannot take road geometric parameters like superelevation of a vehicle's upcoming curve into consideration. In this paper,a new rollover speed prediction model based on the derivation of three-degree-of-freedom vehicle dynamics and lateral load transfer ratio (LTR) index is presented. Through numerical experiments, the results show that this model could guarantee the vehicle roll stability with the calculated speed for entering a curve whose road radius is even 50 m, in which the vehicle's LTR never exceeds 0.72 and lateral acceleration is always less than 0.63 g. Moreover, the proposed model built in a mobile smartphone app can calculate curve radius at first, then provide an early alarming to the driver with an appropriate speed if rollover accident is imminent on the curve. The field tests on freeway off-ramps show that this smartphone-based rollover speed warning system can calculate the curve radii, and alert the driver with appropriate curve speeds that are partially equivalent to professional skilled drivers' speed choices.