Citation

Savino G, Rizzi M, Brown J, Piantini S, Meredith L, Albanese B, Pierini M, Fitzharris M. Traffic Injury Prev. 2014; 15(Suppl 1): S165-S172.

Affiliation

University of Florence , Florence , Italy.

Copyright

(Copyright © 2014, Informa - Taylor and Francis Group)

DOI

10.1080/15389588.2014.926009

PMID

25307383

Abstract

OBJECTIVE: In 2006, Motorcycle Autonomous Emergency Braking (MAEB) was developed by a European Consortium (Powered Two Wheeler Integrated Safety, PISa) as a crash severity countermeasure for riders. This system can detect an obstacle through sensors in the front of the motorcycle and brakes automatically to achieve a 0.3 g deceleration if the collision is inevitable and the rider does not react. However, if the rider does brake, full braking force is applied automatically. Previous research into the potential benefits of MAEB has shown encouraging results. However, this was based on MAEB triggering algorithms designed for motorcycle crashes involving impacts with fixed objects and rear-end crashes. To estimate the full potential benefit of MAEB, there is a need to understand the full spectrum of motorcycle crashes and further develop triggering algorithms that apply to a wider spectrum of crash scenarios.

METHODS: In-depth crash data from 3 different countries were used: 80 hospital admittance cases collected during 2012-2013 within a 3-h driving range of Sydney, Australia, 40 crashes with Injury Severity Score (ISS) > 15 collected in the metropolitan area of Florence, Italy, during 2009-2012, and 92 fatal crashes that occurred in Sweden during 2008-2009. In the first step, the potential applicability of MAEB among the crashes was assessed using a decision tree method. To achieve this, a new triggering algorithm for MAEB was developed to address crossing scenarios as well as crashes involving stationary objects. In the second step, the potential benefit of MAEB across the applicable crashes was examined by using numerical computer simulations. Each crash was reconstructed twice-once with and once without MAEB deployed.

RESULTS: The principal finding is that using the new triggering algorithm, MAEB is seen to apply to a broad range of multivehicle motorcycle crashes. Crash mitigation was achieved through reductions in impact speed of up to approximately 10 percent, depending on the crash scenario and the initial vehicle pre-impact speeds.

CONCLUSIONS: This research is the first attempt to evaluate MAEB with simulations on a broad range of crash scenarios using in-depth data. The results give further insights into the feasibility of MAEB in different speed ranges. It is clear then that MAEB is a promising technology that warrants further attention by researchers, manufacturers, and regulators.

Language: en