An investigation of truck drivers' behaviour before and during real-world advanced emergency braking system interventions

Advanced emergency braking systems (AEBS) aim to address rear-end collisions, which are the most common crash type involving heavy good vehicles. Although previous studies have investigated the safety benefits introduced by AEBS, there is a lack of research exploring drivers' behaviour before and after AEBS interventions. In this paper, we analyzed 6-s long event-triggered naturalistic driving data, collected from heavy goods vehicles every time an AEBS braking intervention occurred, either as preliminary mitigation braking (pMB) or full mitigation braking (MB). The analyses focused on rear-end critical situations in which the drivers did not brake before a collision warning (CW) or a mitigation braking was triggered by the system. The rear-end critical situations encompassed scenarios where the lead vehicle was the same for the whole duration of the event. The results show that full mitigation braking are rare events, occurring in approximately 5 % of the complete dataset. Besides, drivers of heavy goods vehicles are in 75 % of the cases already braking before the intervention of CW. Analyzing in detail a restricted number of interventions from CW and MB, it was found that drivers are keeping headway shorter than 1 s in 44.4 % and 53.6 % of the cases respectively. The annotations performed on the restricted dataset indicate that the drivers were “out of the loop” in 57.3 % of CW interventions and 65 % of MB interventions. However, this finding should be taken with caution, due to the lack of video recordings: in fact, the lack of a fast drivers' response could also be an indication of overtrust in the system or a sign of the drivers assessing the situation as not enough critical to require a braking. Further naturalistic driving studies with increased data frequency and availability of video data are recommended to investigate deeper on this matter. • We analyzed events including AEBS interventions, from naturalistic driving data collected in a fleet of heavy good vehicles. • Drivers are in most of the cases braking before the intervention of CW, and full emergency braking interventions are rare. • Based on this study, simulation scenarios can be built using kinematics information before CW and MB interventions.