Modeling of Low Illuminance Road Lighting Condition Using Road Temporal Profile

2016-01-1454

04/05/2016

Event
SAE 2016 World Congress and Exhibition
Authors Abstract
Content
Pedestrian Automatic Emergency Braking (PAEB) for helping avoiding/mitigating pedestrian crashes has been equipped on some passenger vehicles. Since approximately 70% pedestrian crashes occur in dark conditions, one of the important components in the PAEB evaluation is the development of standard testing at night. The test facility should include representative low-illuminance environment to enable the examination of the sensing and control functions of different PAEB systems. The goal of this research is to characterize and model light source distributions and variations in the low-illuminance environment and determine possible ways to reconstruct such an environment for PAEB evaluation. This paper describes a general method to collect light sources and illuminance information by processing large amount of potential collision locations at night from naturalistic driving video data. This study was conducted in four steps. (1) Gather night driving video collected from Transportation Active Safety Institute (TASI) 110 car naturalistic driving study, particularly emphasizing locations with potential pedestrian collision. (2) Generate temporal video profile as a compact index toward large volumes of video, (3) Identify light fixtures by removing dynamic vehicle head lighting in the profile and stamp them with their Global Positioning System (GPS) coordinates. (4) Find the average distribution and intensity of illuminants by grouping lighting component information around the potential collision locations. The resulting lighting model and setting can be used for lighting reconstruction at PAEB testing site.
Meta TagsDetails
DOI
https://doi.org/10.4271/2016-01-1454
Pages
14
Citation
Dong, L., Chien, S., Zheng, J., Chen, Y. et al., "Modeling of Low Illuminance Road Lighting Condition Using Road Temporal Profile," SAE Technical Paper 2016-01-1454, 2016, https://doi.org/10.4271/2016-01-1454.
Additional Details
Publisher
Published
Apr 5, 2016
Product Code
2016-01-1454
Content Type
Technical Paper
Language
English