Literature DB >> 20728647

Pedestrian injury mitigation by autonomous braking.

Erik Rosén1, Jan-Erik Källhammer, Dick Eriksson, Matthias Nentwich, Rikard Fredriksson, Kip Smith.   

Abstract

The objective of this study was to calculate the potential effectiveness of a pedestrian injury mitigation system that autonomously brakes the car prior to impact. The effectiveness was measured by the reduction of fatally and severely injured pedestrians. The database from the German In-Depth Accident Study (GIDAS) was queried for pedestrians hit by the front of cars from 1999 to 2007. Case by case information on vehicle and pedestrian velocities and trajectories were analysed to estimate the field of view needed for a vehicle-based sensor to detect the pedestrians one second prior to the crash. The pre-impact braking system was assumed to activate the brakes one second prior to crash and to provide a braking deceleration up to the limit of the road surface conditions, but never to exceed 0.6 g. New impact speeds were then calculated for pedestrians that would have been detected by the sensor. These calculations assumed that all pedestrians who were within a given field of view but not obstructed by surrounding objects would be detected. The changes in fatality and severe injury risks were quantified using risk curves derived by logistic regression of the accident data. Summing the risks for all pedestrians, relationships between mitigation effectiveness, sensor field of view, braking initiation time, and deceleration were established. The study documents that the effectiveness at reducing fatally (severely) injured pedestrians in frontal collisions with cars reached 40% (27%) at a field of view of 40 degrees. Increasing the field of view further led to only marginal improvements in effectiveness. 2010 Elsevier Ltd. All rights reserved.

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Year:  2010        PMID: 20728647     DOI: 10.1016/j.aap.2010.05.018

Source DB:  PubMed          Journal:  Accid Anal Prev        ISSN: 0001-4575


  2 in total

1.  Automatic Emergency Braking (AEB) System Impact on Fatality and Injury Reduction in China.

Authors:  Hong Tan; Fuquan Zhao; Han Hao; Zongwei Liu; Amer Ahmad Amer; Hassan Babiker
Journal:  Int J Environ Res Public Health       Date:  2020-02-02       Impact factor: 3.390

2.  Analysis of historical road accident data supporting autonomous vehicle control strategies.

Authors:  Sándor Szénási
Journal:  PeerJ Comput Sci       Date:  2021-02-23
  2 in total

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