Reflective Clothing Research Articles

SDCB-YOLO: A High-Precision Model for Detecting Safety Helmets and Reflective Clothing in Complex Environments

The correct wearing of safety helmets and reflective vests is of great significance in construction sites, offices, and civil engineering sites. Aiming to address the issues of low detection accuracy and high algorithm complexity caused by complex background environments in the small target detection of safety helmets and reflective clothing using existing algorithms, an improved algorithm based on YOLOv8n is proposed. Firstly, the SE module is utilized to reduce interference in complex environments. Next, the IOU function is modified to speed up calculations. Then, a lightweight universal upsampling operator (CARAFE) is employed to obtain a larger receptive field. Finally, the Bidirectional Feature Pyramid Network is used to replace the Concat module of the original head layer. Based on these four modifications made to the model, this article names the new model SDCB-YOLO, derived from the initial letters of the four respective modules. The experimental results show that the mAP of the SDCB-YOLO model on the test set reached 97.1%, which is 4.6% higher than YOLOv5s and 3.5% higher than YOLOv8n. Additionally, the model boasts a parameter count of 3,094,304, a computational load of 8.4 GFLOPs, and a model size of 6.13 MB. Compared to YOLOv5s, with a parameter count of 7,030,417, a computational cost of 16.0 GFLOPs, and a model size of 13.79 MB, the SDCB-YOLO model is significantly smaller. When compared to YOLOv8n, with a parameter count of 3,011,628, a computational complexity of 8.2 GFLOPs, and a model size of 6.11 MB, the SDCB-YOLO model’s parameters and model size are only slightly increased, while maintaining a comparable computational load. Therefore, the improved detection algorithm presented in this article not only ensures the lightweight nature of the model but also significantly enhances its detection accuracy.

YOLOv8-MPEB small target detection algorithm based on UAV images

Target detection in Unmanned Aerial Vehicle (UAV) aerial images has gained significance within UAV application scenarios. However, UAV aerial images present challenges, including large-scale changes, small target sizes, complex scenes, and variable external factors, resulting in missed or false detections. This study proposes an algorithm for small target detection in UAV images based on an enhanced YOLOv8 model termed YOLOv8-MPEB. Firstly, the Cross Stage Partial Darknet53 (CSPDarknet53) backbone network is substituted with the lightweight MobileNetV3 backbone network, consequently reducing model parameters and computational complexity, while also enhancing inference speed. Secondly, a dedicated small target detection layer is intricately designed to optimize feature extraction for multi-scale targets. Thirdly, the integration of the Efficient Multi-Scale Attention (EMA) mechanism within the Convolution to Feature (C2f) module aims to enhance the extraction of vital features and suppress superfluous ones. Lastly, the utilization of a bidirectional feature pyramid network (BiFPN) in the Neck segment serves to ameliorate detection errors stemming from scale variations and complex scenes, thereby augmenting model generalization. The study provides a thorough examination by conducting ablation experiments and comparing the results with alternative algorithms to substantiate the enhanced effectiveness of the proposed algorithm, with a particular focus on detection performance. The experimental outcomes illustrate that with a parameter count of 7.39 M and a model size of 14.5 MB, the algorithm attains a mean Average Precision (mAP) of 91.9 % on the custom-made helmet and reflective clothing dataset. In comparison to standard YOLOv8 models, this algorithm elevates average accuracy by 2.2 percentage points, reduces model parameters by 34 %, and diminishes model size by 32 %. It outperforms other prevalent detection algorithms in terms of accuracy and speed.

YOLO-FL: A target detection algorithm for reflective clothing wearing inspection

In recent years, target detection has been widely used in specific dress detection, to reduce the probability of accidents in certain fields such as construction sites, traffic management, etc. However, the detection of professional dress, especially reflective clothing, is mainly relied on manual detection so far, with the disadvantages of low efficiency and high time consumption. To this end, we focus on reflective clothing and propose the YOLO-FL detection algorithm based on YOLOV4-tiny. Firstly, a new intersection and union ratio calculation method KIoU is proposed and introduced into the original K-means++ clustering method to avoid the influence brought by distance in the original K-means++ clustering method. Secondly, the SPPF module is introduced into the neck network to make the feature information of different scales fully integrated and obtain a richer feature representation. Finally, the label smoothing strategy is used to optimize the loss function of the network model to prevent the network from overfitting and to improve the generalization ability of the model to a certain extent. We tested on the self-made reflective clothing dataset, and the mAP and F1 values of the YOLO-FL algorithm were 91.14% and 0.85, respectively, which improved by 8.29% and 0.12, respectively, compared with the original algorithm. In addition, experiments on PASCAL VOC and MS-COCO datasets show that the accuracy of the YOLO-FL algorithm has significantly improved (+4.77% on the Pascal VOC benchmark and +2.49% on the MS-COCO benchmark), and has excellent migration generalization performance.

PEDESTRIANS’ SAFETY IN POLAND AND USE OF REFLECTIVE MATERIALS

The subject of pedestrian safety is particularly important in Poland, where the risk of mortality is very high compared to other European Union (EU) countries. In Poland, 60% of all killed pedestrians lost their lives at night, mostly away from urban areas. The current article focuses onpedestrians’compliance with the law requirements of the mandatory use of reflective elements at night in non-urban areas since its introduction in Poland in 2014 based on adata analysis and survey on pedestrians’ attitudes and behaviours. An analysis of pedestrian accidents, fatalities, and serious injuries at night five years before and five years after 2014 showed an improvement inpedestrian safety more in non-urban areas (where the law on reflective elements is obligatory) than in urban areas. This study is the first published work to present comprehensive results from an in-depth national survey about people’sattitudes and behaviours regarding theuse of reflective elements. The data were obtained from 600 observed and 400 questioned pedestrians in 2018. Observationsfrom 2018 showed that only 21% of pedestrians respected the obligation towear reflective elements at night outside urban, even though 46% of respondents declared in questionnaires that they wore such elements. Pedestrians who usedreflective devicesin non-urban areas at night were mainly young people aged 40 years old or younger. They used reflective clothing (shoes, trousers, backpacks); 79% of observed pedestrians did not wear reflective elements at night according to questionnaires from 2018. More pedestrians (60%) who didn’t use any reflective wore black clothing, whichmade them not visible to drivers and put them atrisk of being killed. A comparison of thedata showed a positive change in pedestrians’ attitudes due to this obligation.In 2015 only 35% of respondents knew that the use of reflective elements was obligatory in some situations; in 2018, almost half of them (46%) did. The analysis carried out in the present study indicated that the preventive action of introducing the mandatory use of reflective elements at night by pedestrians outside urban areas has slowly improved the safety of pedestrians anddecreased the numbers of accidents, seriousinjuries, and fatalities. Changes introduced intoPolish traffic rules have improvedpedestrians’ safety on roads since 2014; however, there is still an immense need tocarry on social actions and campaigns promoting the use of reflective elements to educate road users to change pedestrians’ behaviours.

Using latent class clustering and binary logistic regression to model Australian cyclist injury severity in motor vehicle–bicycle crashes

Introduction: In recent years, Australia is seeing an increase in the total number of cyclists. However, the rise of serious injuries and fatalities to cyclists has been a major concern. Understanding the factors affecting the fatalities and injuries of bicyclists in crashes with motor vehicles is important to develop effective policy measures aimed at improving the safety of bicyclists. This study aims to identify the factors affecting motor vehicle-bicycle (MVB) crashes in Victoria, Australia and introducing effective countermeasures for the identified risk factors. Method: A data set of 14,759 MVB crash records from Victoria, Australia between 2006 and 2019 was analyzed using the binary logit model and latent class clustering. Results: It was observed that the factors that increase the risk of fatalities and serious injuries of bicyclists (FSI) in all clusters are: elderly bicyclist, not using a helmet, and darkness condition. Likewise, in areas with no traffic control, clear weather, and dry surface condition (cluster 1), high speed limits increase the risk of FSI, but the occurrence of MVB crashes in cross intersection and T-intersection has been significantly associated with a reduction in the risk of FSI. In areas with traffic control and unfavorable weather conditions (cluster 2), wet road surface increases the risk of FSI, but the areas with give way sign and pedestrian crossing signs reduce the risk of FSI. Practical Applications: Recommendations to reduce the risk of fatalities or serious injury to bicyclists are: improvement of road lighting and more exposure of bicyclists using reflective clothing and reflectors, separation of the bicycle and vehicle path in mid blocks especially in high-speed areas, using a more stable bicycle for the older people, monitoring helmet use, improving autonomous emergency braking, and using bicyclist detection technology for vehicles.

A spatiotemporal analysis of motorcyclist injury severity: Findings from 20 years of crash data from Pennsylvania

Motorcyclists face higher risks of severe injuries in crashes compared to motor vehicle drivers who are often protected by seatbelts and airbags during collisions. A report by the National Highway Traffic Safety Administration reveals that motorcyclists have 27 times the risk of fatality in traffic crashes as much as motor vehicle drivers. Previous studies have identified a list of risk factors associated with motorcyclist injury severity and generated valuable insights for countermeasures to protect motorcyclists in crashes. These studies have shown that wearing helmets and/or motorcycle-specific reflective clothing and boots, driving alcohol/drug-free, and obeying traffic regulations are good practices for safe motorcycling. However, these practices and other risk factors are likely to interact with local geographic, socio-economic, and cultural contexts, leading to diversified correlations with motorcyclist injury severity, which remains under-explored. Such correlations may exhibit variations across space and time. The objective of this study is to revisit the correlates of motorcyclist injury severity with a focus on the spatial and temporal variations of correlations between risk factors and injury severity. This study employed an integrated spatiotemporal analytical approach to mine comprehensive statewide 20 years’ motorcycle-involved traffic crashes (N = 50,823) in Pennsylvania. Non-stationarity tests were performed to examine the significance of variations in spatially and temporally local correlations. The results show that most factors, such as helmet, engine size, vehicle age, pillion passenger, at-fault striking, and speeding, hold significant non-stationary relationships with motorcyclist injury severity. Furthermore, cluster analysis of estimations reveals the regional similarities of correlates, which may help practitioners develop regional motorcyclist safety countermeasures.

Randomized trials and self-reported accidents as a method to study safety-enhancing measures for cyclists—two case studies

A large number of studies show that high visibility in traffic is important in the struggle of getting the attention from other road users and thus an important safety factor. Cyclists have a much higher risk of being killed or injured in a traffic accident than car drivers so for them high visibility is particularly important. A number of studies have examined the effect of high visibility, such as reflective clothing, but most studies have been primitive, the data limited and the results very uncertain.In this paper we describe the safety impact of increased visibility of cyclists through two randomised controlled trials: permanent running lights on bicycles and a yellow bicycle jacket, respectively.The effect of running lights was studied through a trial where the lights were mounted to 1,845 bicycles and 2,000 others comprised a control group. The bicycle accidents were recorded every two month in a year through self-reporting on the Internet. Participants were asked to report all cycling accidents independently of severity to avoid differences between participants as regards to which accidents were reported. They reported a total of 255 accidents i.e. 7 accidents per 100 cyclists. The results showed that the incidence rate for multiparty bicycle accidents with personal injury was 47% lower for cyclists with permanent running light. The difference is statistically significant at the 5% level.The effect of a yellow bicycle jacket was examined through a trial with 6,800 volunteer cyclists. The half of the group received a bicycle jacket and the other half comprised a control group. Both groups reported every month all their bicycle accidents independently of severity on the Internet. They reported a total of 694 accidents i.e. 10 accidents per 100 cyclists. The treatment group was asked each month if they carried the jacket on their last cycling trip. The results showed that on a random day the treatment group carried the jacket or other fluorescent cycling garment on 77% of their cycle trips. The incidence rate for multiparty accidents with personal injury was 38% lower than the control group. The difference is statistically significant at the 5% level.The trials were not blind and it seems that the lack of blinding has influenced the level of the groups accident reporting. To address this bias we used a correction factor formed by the difference in the number of single accidents of the two groups.The experiences with self-reporting of accidents via a web based questionnaire sent by e-mail with one respective two month intervals were very good; in both trials more than 80% answered all questionnaires whereas less than 2% did not answer, and the quality of the self-reported accident was considered high.

Bicyclist biomotion visibility aids: a 3D eye-tracking analysis

PurposeThe purpose of this paper is to investigate the effectiveness of biomotion visibility aids for nighttime bicyclists compared to other configurations via 3D eye-tracking technology in a blind between-subjects experiment.Design/methodology/approachA total of 40 participants were randomly assigned one of four visibility aid conditions in the form of videos: biomotion (retroreflective knee and ankle bands), non-biomotion (retroreflective vest configuration), pseudo-biomotion (vertical retroreflective stripes on the back of the legs), and control (all-black clothing). Gaze fixations on a screen were measured with a 3D eye-tracking system; coordinate data for each condition were analyzed via one-way ANOVA and Tukey’s post-hoc analyses with supplementary heatmaps. Post-experimental questionnaires addressed participants’ qualitative assessments.FindingsSignificant differences in eye gaze location were found between the four reflective clothing design conditions in X-coordinate values (p<0.01) and Y-coordinate values (p<0.05).Practical implicationsThis research has the potential to further inform clothing designers and manufacturers on how to incorporate biomotion to increase bicyclist visibility and safety.Social implicationsThis research has the potential to benefit both drivers and nighttime bicyclists through a better understanding of how biomotion can increase visibility and safety.Originality/valueThere is lack of literature addressing the issue of the commonly administered experimental task of recognizing bicyclists and its potential bias on participants’ attention and natural driving state. Eye-tracking has the potential to implicitly determine attention and visibility, devoid of biases to attention. A new retroreflective visibility aid design, pseudo-biomotion, was also introduced in this experiment.

Use of conspicuity aids by cyclists and risk of crashes involving other road users: Population based case-control study

Abstract Background Cycling can improve health and well-being by reducing inactivity. Concern about collision crashes may be a barrier to participation since collision crashes can lead to significant mortality and morbidity. The conspicuity of cyclists may be a contributory factor in some collision crashes. This study investigated whether increased conspicuity aid use (such as reflective or fluorescent clothing) is associated with a reduced risk of collision crashes for cyclists in a UK city. Methods A matched case-control study was undertaken. Cases were adult cyclists involved in a collision crash causing injury. Controls were adult cyclists matched to cases by time of day, day of week and geographical area of travel. Exposures, potential confounders and route were reported by participants. Odds ratios (OR) and 95% confidence intervals were calculated using conditional logistic regression. Results 76 cases and 272 controls were included. 69.7% of cases and 65.4% of controls reported using a conspicuity aid on the crash (cases) or index (controls) journey. The unadjusted OR for a collision crash when using any conspicuity aid vs none was 1.2 (95% CI 0.7 to 2.2) and 2.4 (95% CI 1.1 to 5.6) after adjustment for age, gender, index of multiple deprivation score, route risk score and previous bicycle crash. Conclusion This study found no evidence that cyclists using conspicuity aids were at reduced risk of a collision crash compared to non-users after adjustment for confounding, but there was some evidence of an increase in risk. Bias and residual confounding from differing route selection and cycling behaviours in users of conspicuity aids are possible explanations for these findings. Conspicuity aids may not be effective in reducing collision crash risk for cyclists in highly-motorised environments when used in the absence of other bicycle crash prevention measures such as increased segregation or lower motor vehicle speeds.

Built environment effects on cyclist injury severity in automobile-involved bicycle crashes

This analysis uses a generalized ordered logit model and a generalized additive model to estimate the effects of built environment factors on cyclist injury severity in automobile-involved bicycle crashes, as well as to accommodate possible spatial dependence among crash locations. The sample is drawn from the Seattle Department of Transportation bicycle collision profiles. This study classifies the cyclist injury types as property damage only, possible injury, evident injury, and severe injury or fatality. Our modeling outcomes show that: (1) injury severity is negatively associated with employment density; (2) severe injury or fatality is negatively associated with land use mixture; (3) lower likelihood of injuries is observed for bicyclists wearing reflective clothing; (4) improving street lighting can decrease the likelihood of cyclist injuries; (5) posted speed limit is positively associated with the probability of evident injury and severe injury or fatality; (6) older cyclists appear to be more vulnerable to severe injury or fatality; and (7) cyclists are more likely to be severely injured when large vehicles are involved in crashes. One implication drawn from this study is that cities should increase land use mixture and development density, optimally lower posted speed limits on streets with both bikes and motor vehicles, and improve street lighting to promote bicycle safety. In addition, cyclists should be encouraged to wear reflective clothing.

Recent developments in reflective cold protective clothing

Purpose – The purpose of this paper is to present some new results about reflective cold protective clothing (i.e. those featuring metal coatings), and compare and contrast the data with other recent research work. Design/methodology/approach – The authors used a thermal manikin and a guarded hot plate to determine the thermal resistance of different textile assemblies and garment featuring plasma-deposited metal-coated insulation and interlayers. Findings – Depending on the exact approach, the authors show that metal coatings can increase the thermal resistance of textile assemblies by ∼30-75 per cent. Practical implications – New data on reflective cold weather clothing show that metal coatings could be an important addition to cold weather clothing, especially those featuring high air permeability/optical porosity insulation. Plasma-deposited metal coatings cause the lowest increase in weight. Originality/value – This paper provides new data about the efficacy, in terms of thermal resistance, of metal coatings for cold weather clothing.

Bicycle Safety

Bicycle Safety

A customized vision system for tracking humans wearing reflective safety clothing from industrial vehicles and machinery.

This article presents a novel approach for vision-based detection and tracking of humans wearing high-visibility clothing with retro-reflective markers. Addressing industrial applications where heavy vehicles operate in the vicinity of humans, we deploy a customized stereo camera setup with active illumination that allows for efficient detection of the reflective patterns created by the worker's safety garments. After segmenting reflective objects from the image background, the interest regions are described with local image feature descriptors and classified in order to discriminate safety garments from other reflective objects in the scene. In a final step, the trajectories of the detected humans are estimated in 3D space relative to the camera. We evaluate our tracking system in two industrial real-world work environments on several challenging video sequences. The experimental results indicate accurate tracking performance and good robustness towards partial occlusions, body pose variation, and a wide range of different illumination conditions.

Seeing pedestrians at night: effect of driver age and visual abilities.

To quantify the effects of driver age on night-time pedestrian conspicuity, and to determine whether individual differences in visual performance can predict drivers' ability to recognise pedestrians at night. Participants were 32 visually normal drivers (20 younger: M=24.4years±6.4years; 12 older: M=72.0years±5.0years). Visual performance was measured in a laboratory-based testing session including visual acuity, contrast sensitivity, motion sensitivity and the useful field of view. Night-time pedestrian recognition distances were recorded while participants drove an instrumented vehicle along a closed road course at night; to increase the workload of drivers, auditory and visual distracter tasks were presented for some of the laps. Pedestrians walked in place, sideways to the oncoming vehicles, and wore either a standard high visibility reflective vest or reflective tape positioned on the movable joints (biological motion). Driver age and pedestrian clothing significantly (p<0.05) affected the distance at which the drivers first responded to the pedestrians. Older drivers recognised pedestrians at approximately half the distance of the younger drivers and pedestrians were recognised more often and at longer distances when they wore a biological motion reflective clothing configuration than when they wore a reflective vest. Motion sensitivity was an independent predictor of pedestrian recognition distance, even when controlling for driver age. The night-time pedestrian recognition capacity of older drivers was significantly worse than that of younger drivers. The distance at which drivers first recognised pedestrians at night was best predicted by a test of motion sensitivity.

The relationship between visibility aid use and motor vehicle related injuries among bicyclists presenting to emergency departments

BackgroundLittle is known about the effectiveness of visibility aids (VAs; e.g., reflectors, lights, fluorescent clothing) in reducing the risk of a bicyclist–motor-vehicle (MV) collision. PurposeTo determine if VAs reduce the risk of a bicyclist–MV collision. MethodsCases were bicyclists struck by a MV and assessed at Calgary and Edmonton, Alberta, Canada, emergency departments (EDs) from May 2008 to October 2010. Controls were bicyclists with non-MV injuries. Participants were interviewed about their personal and injury characteristics, including use of VAs. Injury information was collected from charts. Odds ratios (ORs) and 95% confidence intervals (CIs) were estimated for VAs during daylight and dark conditions, and adjusted for confounders using logistic regression. Missing values were imputed using chained equations and adjusted OR estimates from the imputed data were calculated. ResultsThere were 2403 injured bicyclists including 278 cases. After adjusting for age, sex, type of bicycling (commuting vs. recreational) and bicyclist speed, white compared with black (OR 0.52; 95% CI 0.28, 0.95), and bicyclist self-reported light compared with dark coloured (OR 0.67; 95% CI 0.49, 0.92) upper body clothing reduced the odds of a MV collision during daylight. After imputing missing values, white compared with black (OR 0.57; 95% CI: 0.32, 0.99) and bicyclist self-reported light compared with dark coloured (OR 0.71; 95% CI 0.52, 0.97) upper body clothing remained protective against MV collision in daylight conditions. During dark conditions, crude estimates indicated that reflective clothing or other items, red/orange/yellow front upper body clothing compared with black, fluorescent clothing, headlights and tail lights were estimated to increase the odds of a MV collision. An imputed adjusted analysis revealed that red/orange/yellow front upper body clothing colour (OR 4.11; 95% CI 1.06, 15.99) and tail lights (OR 2.54; 95% CI: 1.06, 6.07) remained the only significant risk factors for MV collisions. One or more visibility aids reduced the odds of a bicyclist MV collision resulting in hospitalization. ConclusionsBicyclist clothing choice may be important in reducing the risk of MV collision. The protective effect of visibility aids varies based on light conditions, and non-bicyclist risk factors also need to be considered.

Visibility-related characteristics of crashes involving bicyclists and motor vehicles – Responses from an online questionnaire study

Bicyclists are among the most vulnerable of road users, with high fatal crash rates. Although visibility aids have been widely advocated to help prevent bicycle-vehicle conflicts, to date no study has investigated, among crash-involved cyclists, the kind of visibility aids they were using at the time of the crash. This study undertook a detailed investigation of visibility factors involved in bicyclist-motor-vehicle crashes. We surveyed 184 bicyclists (predominantly from Australia via internet cycling forums) who had been involved in motor vehicle collisions regarding the perceived cause of the collision, ambient weather and general visibility, as well as the clothing and bicycle lights used by the bicyclist. Over a third of the crashes occurred in low light levels (dawn, dusk or night-time), which is disproportionate given that only a small proportion of bicyclists typically ride at these times. Importantly, 19% of these bicyclists reported not using bicycle lights at the time of the crash, and only 34% were wearing reflective clothing. Only two participants (of 184) nominated bicyclist visibility as the cause of the crash: 61% attributed the crash to driver inattention. These findings demonstrate that crash-involved bicyclists tend to under-rate and under-utilise visibility aids as a means of improving their safety.

Helmet and reflective clothing use among motorcyclists in Kenya: a survey of use, knowledge, attitudes, and practices in two districts

BackgroundRoad traffic injuries (RTIs) contribute to a significant proportion of the burden of disease in Kenya. Motorcycle-related RTIs are a significant contributor to this burden.Aims/Objectives/PurposeThis study assesses helmet wearing and...

DO VISIBILITY AIDS REDUCE THE RISK OF MOTOR-VEHICLE INJURY IN BICYCLISTS?

BackgroundThere is limited literature regarding the effectiveness of visibility aids (eg, reflectors, lights, fluorescent clothing) in reducing the risk of a bicyclist- motor-vehicle (MV) collision.ObjectivesTo determine if visibility aids reduce...

Burden and risk factors for road traffic injuries in two districts of Kenya: a descriptive analysis

BackgroundA combination of increasing vehicle volume on the road, evolving mix of vehicles, poor infrastructure, and unsafe vehicles has led to increasing road traffic crashes, injuries and fatalities in Kenya.Aims/Objectives/PurposeThis...

Even Moderate Visual Impairments Degrade Drivers' Ability to See Pedestrians at Night

To determine the effect of moderate levels of refractive blur and simulated cataracts on nighttime pedestrian conspicuity in the presence and absence of headlamp glare. The ability to recognize pedestrians at night was measured in 28 young adults (M = 27.6 years) under three visual conditions: normal vision, refractive blur, and simulated cataracts; mean acuity was 20/40 or better in all conditions. Pedestrian recognition distances were recorded while participants drove an instrumented vehicle along a closed road course at night. Pedestrians wore one of three clothing conditions and oncoming headlamps were present for 16 participants and absent for 12 participants. Simulated visual impairment and glare significantly reduced the frequency with which drivers recognized pedestrians and the distance at which the drivers first recognized them. Simulated cataracts were significantly more disruptive than blur even though photopic visual acuity levels were matched. With normal vision, drivers responded to pedestrians at 3.6- and 5.5-fold longer distances on average than for the blur or cataract conditions, respectively. Even in the presence of visual impairment and glare, pedestrians were recognized more often and at longer distances when they wore a "biological motion" reflective clothing configuration than when they wore a reflective vest or black clothing. Drivers' ability to recognize pedestrians at night is degraded by common visual impairments, even when the drivers' mean visual acuity meets licensing requirements. To maximize drivers' ability to see pedestrians, drivers should wear their optimum optical correction, and cataract surgery should be performed early enough to avoid potentially dangerous reductions in visual performance.