A robust estimation of the effects of motorcycle autonomous emergency braking (MAEB) based on in-depth crashes in Australia
Creators: name: Savino, Giovanni
name: Mackenzie, Jamie
name: Allen, Trevor
name: Baldock, Matthew
name: Brown, Julie
name: Fitzharris, Michael
Publisher: name: Taylor & Francis
Year: 2016
Subjects: subject: Space Science
subject: Medicine
subject: 59999 Environmental Sciences not elsewhere classified
subject: FOS: Earth and related environmental sciences
subject: FOS: Earth and related environmental sciences
subject: Sociology
subject: FOS: Sociology
subject: FOS: Sociology
subject: 69999 Biological Sciences not elsewhere classified
subject: FOS: Biological sciences
subject: FOS: Biological sciences
subject: 80699 Information Systems not elsewhere classified
subject: FOS: Computer and information sciences
subject: FOS: Computer and information sciences
subject: 19999 Mathematical Sciences not elsewhere classified
subject: FOS: Mathematics
subject: FOS: Mathematics
subject: Computational Biology

description: <b>Objective</b>: Autonomous emergency braking (AEB) is a safety system that detects imminent forward collisions and reacts by slowing down the host vehicle without any action from the driver. AEB effectiveness in avoiding and mitigating real-world crashes has recently been demonstrated. Research suggests that a translation of AEB to powered 2-wheelers could also be beneficial. Previous studies have estimated the effects of a motorcycle AEB system (MAEB) via computer simulations. Though effects of MAEB were computed for motorcycle crashes derived from in-depth crash investigation, there may be some inaccuracies due to limitations of postcrash investigation (e.g., inaccuracies in preimpact velocity of the motorcycle). Furthermore, ideal MAEB technology was assumed, which may lead to overestimation of the benefits. This study sought to evaluate the sensitivity of the simulations to variations in reconstructed crash cases and the capacity of the MAEB system in order to provide a more robust estimation of MAEB effects. <b>Methods:</b> First, a comprehensive classification of accidents was used to identify scenarios in which MAEB was likely to apply, and representative crash cases from those available for this study were populated for each crash scenario. Second, 100 variant cases were generated by randomly varying a set of simulation parameters with given normal distributions around the baseline values. Variants reflected uncertainties in the original data. Third, the effects of MAEB were estimated in terms of the difference in the impact speed of the host motorcycle with and without the system via computer simulations of each variant case. Simulations were repeated assuming both an idealized and a realistic MAEB system. For each crash case, the results in the baseline case and in the variants were compared. A total of 36 crash cases representing 11 common crash scenarios were selected from 3 Australian in-depth data sets: 12 cases from New South Wales, 13 cases from Victoria, and 11 cases from South Australia. <b>Results:</b> The reduction in impact speed elicited by MAEB in the baseline cases ranged from 2.8 to 10.0 km/h. The baseline cases over- or underestimated the mean impact speed reduction of the variant cases by up to 20%. Constraints imposed by simulating more realistic capabilities for an MAEB system produced a decrease in the estimated impact speed reduction of up to 14% (mean 5%) compared to an idealized system. <b>Conclusions:</b> The small difference between the baseline and variant case results demonstrates that the potential effects of MAEB computed from the cases described in in-depth crash reports are typically a good approximation, despite limitations of postcrash investigation. Furthermore, given that MAEB intervenes very close to the point of impact, limitations of the currently available technologies were not found to have a dramatic influence on the effects of the system.