Night-time driving visibility associated with LED streetlight dimming

Wood, Joanne M.; Isoardi, Gillian; Black, Alex A.; Cowling, Ian

doi:10.1016/j.aap.2018.08.023

Cited by 20 publications

(16 citation statements)

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“…Meta‐analyses of crash data and streetlighting levels, demonstrate that lower levels of traditional streetlighting do not necessarily increase crash risk, and highlight the potential for dimming and adaptive strategies, where streetlighting levels are modified according to road user needs. The only study that has explored the impact of LED streetlight dimming on driving performance was conducted on a closed road for a group of young drivers . Dimming of LED streetlighting to 25% and 50% of the brightest level (average road surface luminance of 1.14 cd m −2 ), resulted in a small but significant slowing of driving reaction times and decreased response distances to low contrast moving targets and pedestrians, while dimming to 75% did not affect any of the outcome measures .…”

Section: Driving Under Nighttime Conditionsmentioning

confidence: 99%

“…The only study that has explored the impact of LED streetlight dimming on driving performance was conducted on a closed road for a group of young drivers . Dimming of LED streetlighting to 25% and 50% of the brightest level (average road surface luminance of 1.14 cd m −2 ), resulted in a small but significant slowing of driving reaction times and decreased response distances to low contrast moving targets and pedestrians, while dimming to 75% did not affect any of the outcome measures . An important question is whether these changes in driving reaction times and recognition distances under the lower streetlight levels negatively impact on nighttime road safety; this issue needs to be explored in future studies including drivers of different ages and with a range of levels of visual performance that are representative of the driving population.…”

Section: Driving Under Nighttime Conditionsmentioning

confidence: 99%

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Nighttime driving: visual, lighting and visibility challenges

Wood

2019

Ophthalmic Physiologic Optic

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Purpose Nighttime driving is dangerous and is one of the most challenging driving situations for most drivers. Fatality rates are higher at night than in the day when adjusted for distances travelled, particularly for crashes involving pedestrians and cyclists. Although there are multiple contributory factors, the low light levels at night are believed to be the major cause of collisions with pedestrians and cyclists at night, most likely due to their reduced visibility. Understanding the visibility problems involved in nighttime driving is thus critical, given the increased risk to road safety. Recent Findings This review discusses research that highlights key differences in the nighttime road environment compared to the day and how this affects visual function and driving performance, together with an overview of studies investigating how driver age and visual status affect nighttime driving performance. Research that has focused on the visibility of vulnerable road users at nighttime (pedestrians and cyclists) is also included. Summary Collectively, the research evidence suggests that visual function is reduced under the mesopic lighting conditions of night driving and that these effects are exacerbated by increasing age and visual impairment. Light and glare from road lighting and headlights have significant impacts on vision and night driving and these effects are likely to change with evolving technologies, such as LED streetlighting and headlights. Research also highlights the importance of the visibility of vulnerable road users at night and the role of retroreflective clothing in the ‘biomotion’ configuration for improving their conspicuity and hence safety.

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Section: Driving Under Nighttime Conditionsmentioning

confidence: 99%

Section: Driving Under Nighttime Conditionsmentioning

confidence: 99%

Nighttime driving: visual, lighting and visibility challenges

Wood

2019

Ophthalmic Physiologic Optic

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“…A study based on the Fatality Analysis Reporting System (FARS) data reported that fatal crashes in rain were three times as likely to involve ≥10 vehicles as fatal crashes on clear days [17]. Nighttime driving is also dangerous with adjusted fatality rates being up to three times higher than daytime driving [18]. This situation is even worse for fatal crashes involving pedestrians, where pedestrian fatalities at night occur at higher rates compared to pedestrian fatalities during the day [19], and its rate is up to seven times higher than that in daytime [20].…”

Section: Introductionmentioning

confidence: 99%

Association between Crash Attributes and Drivers’ Crash Involvement: A Study Based on Police-Reported Crash Data

Lai

2020

IJERPH

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Understanding the association between crash attributes and drivers’ crash involvement in different types of crashes can help figure out the causation of crashes. The aim of this study was to examine the involvement in different types of crashes for drivers from different age groups, by using the police-reported crash data from 2014 to 2016 in Shenzhen, China. A synthetic minority oversampling technique (SMOTE) together with edited nearest neighbors (ENN) were used to solve the data imbalance problem caused by the lack of crash records of older drivers. Logistic regression was utilized to estimate the probability of a certain type of crashes, and odds ratios that were calculated based on the logistic regression results were used to quantify the association between crash attributes and drivers’ crash involvement in different types of crashes. Results showed that drivers’ involvement patterns in different crash types were affected by different factors, and the involvement patterns differed among the examined age groups. Knowledge generated from the present study could help improve the development of countermeasures for driving safety enhancement.

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“…In terms of traffic environment, recognition errors account for 41% of the human driver errors, far higher than those of decision or performance 2. Poor visibility was confirmed as a critical hazard, significantly delaying driver reaction to the moving target 34 35. Unfortunately, such defects have been hardly overcome in AVs so far.…”

Section: Discussionmentioning

confidence: 99%

Approaching autonomous driving with cautious optimism: analysis of road traffic injuries involving autonomous vehicles based on field test data

Wang

Fuxiang

et al. 2020

Inj Prev

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ObjectivesTo examine the patterns and associated factors of road traffic injuries (RTIs) involving autonomous vehicles (AVs) and to discuss the public health implications and challenges of autonomous driving.MethodsData were extracted from the reports of traffic crashes involving AVs. All the reports were submitted to the California Department of Motor Vehicles by manufacturers with permission to operate AV test on public roads. Descriptive analysis and χ2 analysis or Fisher’s exact test was conducted to describe the injury patterns and to examine the influencing factors of injury outcomes, respectively. Binary logistic regression using the Wald test was employed to calculate the OR, adjusted OR (AOR) and 95% CIs. A two-tailed probability (p<0.05) was adopted to indicate statistical significance.Results133 reports documented 24 individuals injured in 19 crashes involving AVs, with the overestimated incidence rate of 18.05 per 100 crashes. 70.83% of the injured were AV occupants, replacing vulnerable road users as the leading victims. Head and neck were the most commonly injured locations. Driving in poor lighting was at greater risk of RTIs (AOR 6.37, 95% CI 1.47 to 27.54). Collisions with vulnerable road users or incidents happening during commute periods led to a greater number of victims (p<0.05). Autonomous mode cannot perform better than conventional mode in road traffic safety to date (p=0.468).ConclusionsPoor lighting improvement and the regulation of commute-period traffic and vulnerable road users should be strengthened for AV-related road safety. So far AVs have not demonstrated the potential to dramatically reduce RTIs. Cautious optimism about AVs is more advisable, and multifaceted efforts, including legislation, smarter roads, and knowledge dissemination campaigns, are fairly required to accelerate the development and acceptance.

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Night-time driving visibility associated with LED streetlight dimming

Cited by 20 publications

References 20 publications

Nighttime driving: visual, lighting and visibility challenges

Nighttime driving: visual, lighting and visibility challenges

Association between Crash Attributes and Drivers’ Crash Involvement: A Study Based on Police-Reported Crash Data

Approaching autonomous driving with cautious optimism: analysis of road traffic injuries involving autonomous vehicles based on field test data

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