Built environment, driving errors and violations, and crashes in naturalistic driving environment

被引:17
作者
Ahmad, Numan [1 ]
Wali, Behram [2 ]
Khattak, Asad J. [1 ]
Dumbaugh, Eric [3 ]
机构
[1] Univ Tennessee, Dept Civil & Environm Engn, Knoxville, TN 37996 USA
[2] Urban Design 4 Hlth, 24 Jackie Circle East, Rochester, NY 14612 USA
[3] Florida Atlantic Univ, Sch Urban & Reg Planning, Boca Raton, FL 33431 USA
关键词
Driver errors and violations; Built environment; Taxonomy; Path analysis; Ordered probit; Multinomial logit; SHRP2; Naturalistic driving study; RAIL GRADE CROSSINGS; DRIVER INJURY SEVERITY; RISK-FACTORS; MODELS; BEHAVIOR;
D O I
10.1016/j.aap.2021.106158
中图分类号
TB18 [人体工程学];
学科分类号
1201 ;
摘要
Driving errors and violations are highly relevant to the safe systems approach as human errors tend to be a predominant cause of crash occurrence. In this study, we harness highly detailed pre-crash Naturalistic Driving Study (NDS) data 1) to understand errors and violations in crash, near-crash, and baseline (no event) driving situations, and 2) to explore pathways that lead to crashes in diverse built environments by applying rigorous modeling techniques. The "locality" factor in the NDS data provides information on various types of roadway and environmental surroundings that could influence traffic flow when a precipitating event is observed. Coded by the data reductionists, this variable is used to quantify the associations of diverse environments with crash outcomes both directly and indirectly through mediating driving errors and violations. While the most prevalent errors in crashes were recognition errors such as failing to recognize a situation (39 %) and decision errors such as not braking to avoid a hazard (34 %), performance errors such as poor lateral or longitudinal control or weak judgement (8 %) were most strongly correlated with crash occurrence. Path analysis uncovered direct and indirect relationships between key built-environment factors, errors and violations, and crash propensity. Possibly due to their complexity for drivers, urban environments are associated with higher chances of crashes (by 6.44 %). They can also induce more recognition errors which correlate with an even higher chances of crashes (by 2.16 % with the "total effect" amounting to 8.60 %). Similar statistically significant mediating contributions of recognition errors and decision errors near school zones, business or industrial areas, and moderate residential areas were also observed. From practical applications standpoint, multiple vehicle technologies (e.g., collision warning systems, cruise control, and lane tracking system) and built-environment (roadway) changes have the potential to reduce driving errors and violations which are discussed in the paper.
引用
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页数:17
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