Measuring the effect of the rainfall on the windshield in terms of visual performance

doi:10.1016/j.aap.2013.10.008

Accident Analysis & Prevention

Volume 63, February 2014, Pages 83-88

https://doi.org/10.1016/j.aap.2013.10.008 Get rights and content

Highlights

•
We propose a methodology to assess visual performance through rain.
•
The visual performance of 40 observers were recorded under controlled rain.
•
Two tasks relevant for driving are considered: detection and reading.
•
Effects of rain level and wiper characteristics were found.

Abstract

Driving through rain results in reduced visual performance, and car designers have proposed countermeasures in order to reduce the impact of rain on driving performance. In this paper, we propose a methodology dedicated to the quantitative estimation of the loss of visual performance due to the falling rain. We have considered the rain falling on the windshield as the main factor which reduces visual performance in driving. A laboratory experiment was conducted with 40 participants. The reduction of visual performance through rain was considered with respect to two driving tasks: the detection of an object on the road (contrast threshold) and reading a road sign. This experiment was conducted in a laboratory under controlled artificial rain. Two levels of rain intensity were compared, as well as two wiper conditions (new and worn), while the reference condition was without rain. The reference driving situation was night driving. Effects of both the rain level and the wipers characteristics were found, which validates the proposed methodology for the quantitative estimation of rain countermeasures in terms of visual performance.

Section snippets

Road safety under rain

Rain may affect driving performance, and since the beginning of automotive transport, car designers have considered this issue. They have proposed countermeasures in order to reduce the impact of rain as early as 1903, when Mary Anderson proposed the first patent for a windshield wiper (Anderson, 1903). In addition to wipers, rain effects are also mitigated by improved windshield design, automotive lighting and road lighting. Considering the high impact of rain on vision, and even though the

Materials and methods

Based on our literature review, we have considered the rain falling on the windshield as the main factor which reduces the visual performance in driving. An experiment was conducted in order to quantify the reduction of visual performance through rain with respect to two reference driving tasks: the detection of an object on the road and reading a road sign. This experiment was conducted in a laboratory under controlled artificial rain. Two levels of rain intensity were compared, as well as two

Target detection performance

An ANOVA with Word and Rain as within-participants factors (Word (2) × Rain (3)) showed an effect of the contrast class as expected (F_(8,312) = 222.22; η² = 0.85; p < .05), as well as an effect of the rain level (F_(2,78) = 29.75; η² = 0.433; p < .05), and an interaction between contrast class and Rain (F_(16,624) = 2.82; η² = 0.068; p < .05).

After removing the “no rain” condition, in an ANOVA with Word, Rain and Wipers as within-participants factors (Word (2) × Rain (2) × Wipers (2)), the effect of the wipers was found

Discussion

A methodology was developed, in order to assess the performance of a driver visibility system through rain. The system consists in two parts: first, a laboratory system, where calibrated rain can be produced in order to simulate rain over a car's windshield, in a dark tunnel, under controlled illumination. The second part of the methodology consists in an experimental protocol. Two visual tasks have been selected, one related to hazard detection (target detection), the other related to road

Acknowledgements

We wish to thank Jérome Cazard, Jean-Luc Bicard and Philippe Morange, who participated to the rain system settings and experiment passing, Eric Dumont for helpful discussions on the manuscript, and Stéphane Jourdain (Valeo) who supplied the wipers. This work was partially supported by the SURVIE FUI project.

References (26)

J. Andrey et al.
A temporal analysis of rain-related crash risk
Accident Analysis and Prevention
(1993)
M. Colomb et al.
An innovative artificial fog production device improved in the European project “FOG”
Journal of Atmospheric Research
(2008)
J.B. Edwards
The relationship between road accident severity and recorded weather
Journal of Safety Research
(1998)
K. Keay et al.
The association of rainfall and other weather variables with road traffic volume in Melbourne
Accidents Analysis and Prevention
(2005)
Anderson, M., 1903. Window-cleaning device. Patent 743 801, United State Patent...
J. Andrey et al.
Weather and Transportation in Canada
(2003)
V. Bhise et al.
Predicting driver seeing distance in natural rainfall
Human Factors
(1981)
M. Blanco
Relationship between Driver Characteristics, Nighttime Driving Risk Perception, and Visual Performance under Adverse and Clear Weather Conditions and Different Vision Enhancement Systems
(2002)
R. Brémond et al.
A target visibility level and detection distance on a driving simulator
Lighting Research and Technology
(2013)
E. Chung et al.
Effect of rain on travel demand and traffic accidents

V. Cavallo et al.

Distance perception of rear lights in fog

Humans Factors

(2001)

Commission Internationale de l’Eclairage, 2002. CIE Collection on glare. Publications No. 146–147....

K. Garg et al.

Vision and rain

International Journal of Computer Vision

(2007)

Cited by (26)

Visual function correlates of self-reported vision-related nighttime driving difficulties
2024, Journal of Optometry
To investigate the visual function correlates of self-reported vision-related night driving difficulties among drivers.
One hundred and seven drivers (age: 46.06 ± 8.24, visual acuity [VA] of 0.2logMAR or better) were included in the study. A standard vision and night driving questionnaire (VND-Q) was administered. VA and contrast sensitivity were measured under photopic and mesopic conditions. Mesopic VA was remeasured after introducing a peripheral glare source into the participants' field of view to enable computation of disability glare index. Regression analyses were used to assess the associations between VND-Q scores, and visual function measures.
The mean VND-Q score was -3.96±1.95 logit (interval scale score: 2.46±1.28). Simple linear regression models for photopic contrast sensitivity, mesopic VA, mesopic contrast sensitivity, and disability index significantly predicted VND-Q score (P<0.05), with mesopic VA and disability glare index accounting for the greatest variation (21 %) in VND-Q scores followed by photopic contrast sensitivity (19 %), and mesopic contrast sensitivity (15 %). A multiple regression model to determine the association between the predictors (photopic contrast sensitivity, mesopic VA, mesopic contrast sensitivity, and disability index) and VND-Q score yielded significant results, F (4, 102) = 8.58, P < 0.001, adj. R² = 0.2224. Seeing dark-colored cars was the most challenging vision task.
Changes in mesopic visual acuity, photopic and mesopic contrast sensitivity, as well as disability glare index are associated with and explain night driving-related visual difficulties. It is recommended to incorporate measurement of these visual functions into assessments related to driving performance.
Identification of fog Particle Size Distribution by a radiative transfer equation inversion
2024, Journal of Quantitative Spectroscopy and Radiative Transfer
For autonomous driving applications, we investigate the fog Droplet Size Distribution (DSD) identification from spectral radiation measurements in the range 350 nm–2500 nm by inverting the 1D stationary radiative transfer equation (RTE). This distribution together with Lorenz–Mie scattering theory allow to compute the optical properties (scattering coefficient, absorption coefficient, and scattering phase function). The inverse problem is based on a cost function minimization by using a gradient descent-based algorithm. In order to calculate the gradient, the method proposed in this work relies on the introduction of an adjoint problem of the RTE which can contain an in-scattering term. The work is then not restricted to the Beer–Lambert case as often encountered in the literature. We present some numerical results obtained on synthetic forescattering and backscattering measurements. The robustness of the reconstruction is studied numerically by adding several noise levels to the measurements.
Yellow thermoplastic road markings with high retroreflectivity: Demonstration study in Texas
2021, Case Studies in Construction Materials
Citation Excerpt :
For comparison, the standard requirements call for initial RL of only 175 mcd/m²/lx; there are no demands for RW or for keeping of the performance [69,70]. Road visibility during rain is reduced [71], which decreases the quality of external cues available to a driver. Under such conditions, the role of road markings as uniform guiding features should be increasing; unfortunately, a layer of moisture on glass beads surface is reducing the effective RI to nil and RL (under such conditions: RW) drops significantly.
Road markings are a niche category of industrial coatings with requirements related to both the coating itself and the layer of glass beads on top of it that furnish retroreflectivity (R_L) – their key property, particularly needed during driving at night time and in rainy weather conditions. The most frequently used glass beads, with refractive index 1.5, are capable of delivering R_L reaching only about 400 mcd/m²/lx in white and 200 mcd/m²/lx in yellow markings; very low retroreflectivity under wet conditions, seldom exceeding 50 mcd/m²/lx can be obtained. Recently introduced ‘premium’ glass beads, with refractive index marginally increased, to 1.6–1.7, can yield more than twice as high R_L. It was envisaged that high R_L in a yellow road marking could be achieved if a structure with high vertical profile were reflectorised with these premium glass beads. Because of strict compositional requirements for road markings used in North America, a demonstration trial was made possible due to a special specification that allowed some departure from the fixed standards, but within new high-level demands related to R_L under both dry and wet conditions. The tested material was a thermoplastic mass applied as regular dots that, due to round surface, would facilitate rainwater drainage, thus permitting the glass beads surface to be exposed to deliver adequete R_L also under wet conditions. The performance achieved in the field was excellent: after 30 days, R_L 894 mcd/m²/lx under dry and 160 mcd/m²/lx under wet conditions were achieved. Moreover, the applied road marking system maintained the required performance for 12 months (R_L 774 mcd/m²/lx), while the control failed (R_L<100 mcd/m²/lx). The outcome of this demonstration is expanding the knowledge related to this specific type of industrial maintenance coatings and should be of profound interest to road administrators who are searching for improved performance of road marking materials to increase road safety, particularly on major thoroughfares.
Determination of the impact of rainfall on road accidents in Thailand
2021, Heliyon
Citation Excerpt :
Previous studies have reported significant positive associations between rainfall and road accidents (Bergel-Hayat et al., 2013; Brodsky and Hakkert, 1988; Hermans et al., 2006). Heavy rain is a danger because of the reduced road skid resistance associated with a wet road (Bernardin et al., 2014). However, some publications claim that rainfall can also be a protective factor with decreases in road accidents observed during heavy rain.
The World Health Organization has highlighted that the number of deaths worldwide due to road accidents increases every year. It recommends that countries improve road safety for all people by providing sustainable and safe transport systems by 2030, efforts are especially required within Low Middle-Income Countries (LMICS). This study is the first to investigate the impact of rainfall on road accidents in Thailand. Thai emergency data were collected from the National Institute for Emergency Medicine (NIEM) between 2012 to 2018. A time-series design with generalized linear model (GLM) was applied to analyse the associations between road accidents and rainfall. The results are reported using relative risk (RR) at 95% confidence intervals compared with dry days. The effects of long-term trends, seasonality, day of the weeks, public holidays and other meteorological factors were controlled in the GLM. A meta-analysis was applied to summarise the estimate effect of rain groups stratified by the Northern and Southern provinces.
Findings reported a significant increase in road accidents due to high rainfall levels both in the Southern and the Northern provinces. The pooled estimate risks in the Southern provinces have higher estimated risks than the Northern provinces. Both Northern and Southern provinces showed the rain group with 10–20 mm/day having the highest pooled estimated risk with RR = 1.052, (95% CI: 1.026–1.079) and RR = 1.062, (95% CI: 1.043–1.082), respectively, while surprisingly, heavy rain with more than 20 mm/day reported a reduction of risks. Road accidents can therefore be associated with rainfall. It is recommended that rainfall is factored into ambulance forecast models and warning systems, allowing for improvements in ambulance service efficiency. Policymakers need to integrate road safety policies that reduce road accidents in wet weather.
Development of Crash Prediction Model using Artificial Neural Network (ANN): A Case Study of Hyderabad, India
2023, Journal of The Institution of Engineers (India): Series A
IDENTIFICATION OF FOG PARTICLE SIZE DISTRIBUTION BY A RADIATIVE TRANSFER EQUATION INVERSION
2023, Proceedings of the International Symposium on Radiative Transfer

View all citing articles on Scopus

View full text

Measuring the effect of the rainfall on the windshield in terms of visual performance

Highlights

Abstract

Section snippets

Road safety under rain

Materials and methods

Target detection performance

Discussion

Acknowledgements

Accident Analysis and Prevention

Journal of Atmospheric Research

Journal of Safety Research

Accidents Analysis and Prevention

Weather and Transportation in Canada

Predicting driver seeing distance in natural rainfall

Human Factors

Relationship between Driver Characteristics, Nighttime Driving Risk Perception, and Visual Performance under Adverse and Clear Weather Conditions and Different Vision Enhancement Systems

A target visibility level and detection distance on a driving simulator

Lighting Research and Technology

Effect of rain on travel demand and traffic accidents

Distance perception of rear lights in fog

Humans Factors

Vision and rain

International Journal of Computer Vision