Study of automated shuttle interactions in city traffic using surrogate measures of safety

Driving automation is happening at a rapid pace, with different driver assistance systems already available in mass-market cars. However, this rapid development in driving automation leads to concerns and questions about their impact on safety. While previous studies have been restricted to incident reports and simulation tools, the safety of automated vehicles (AVs) has not been clearly demonstrated independently from their developers and proponents. Instead of crashes, which are extremely rare events, this study uses surrogate measures of safety (SMoS) to analyze the interactions between road users and low-speed automated shuttles that circulated in Montreal and Candiac, in Canada, during two pilot projects in mid and late 2019. Cameras were placed at seven intersections along the routes of the shuttles. More than 70 hours of footage were processed to extract the road user trajectories using computer vision techniques and compute various safety indicators: speed and acceleration at the road user level, time headway, time-to-collision (TTC), post-encroachment time (PET) and the speed difference at the interaction level. The Kolmogorov-Smirnov test was used to compare the distributions of these indicators for interactions involving automated shuttles or motorized vehicles following similar paths. Multivariate regression was used to identify the relationship between the safety indicators and various factors. The results indicate that these automated shuttles behave generally more safely: their speeds and accelerations are lower and their interactions are characterized by higher TTC and PET values, and lower speed differences. However, small headway times at one site with high-speed differences between the shuttles and other following vehicles raise concerns that warrant further research into the suitable context for these vehicles.