This paper presents a big data analytics method for the proactive mitigation of grounding
risk. The model encompasses the dynamics of ship motion trajectories while accounting for …

The simplified vehicle model often results in inaccuracy with respect to the conventional
model predictive control (MPC) as it causes steady error in tracking control, which has …

Despite the use of automation technology in the maritime industry, human errors are still the
typical navigational risk influencing factors in autonomous ships with the third degree of …

The trucking industry urgently requires comprehensive methods to evaluate driver safety,
given the high incidence of serious traffic accidents involving trucks. The concept of a “truck …

In previous research, the effects of commercial vehicle proportions (CVP) on overall crash
propensity have been found to be significant, but the results have been varied in terms of the …

Abstract Model-free reinforcement learning methods have potentials in ship collision
avoidance under unknown environments. To defect the low efficiency problem of the model …

During the past several years, the COVID-19 pandemic has had pronounced impacts on
traffic safety. Existing studies found that the crash frequency was reduced and the severity …

Unsafe driving behaviors are the leading causes of truck crashes. Therefore, an enhanced
understanding of truck drivers' unsafe driving behaviors is of considerable significance for …

Identifying critical safety management drivers with high driver-level risks is essential for
traffic safety improvement. Previous studies commonly evaluated driver-level risks based …

Fire detection technology based on video images can avoid many flaws in conventional
methods and detect fires. To achieve this, the support vector machine (SVM) method in …