Trial-by-trial feedback fails to improve the consideration of acceleration in visual time-to-collision estimation.

When judging the time-to-collision (TTC) of visually presented accelerating vehicles, untrained observers do not adequately account for acceleration (second-order information). Instead, their estimations only rely on vehicle distance and velocity (first-order information). As a result, they systemically overestimate the TTC for accelerating objects, which represents a potential risk for pedestrians in traffic situations because it might trigger unsafe road-crossing behavior. Can training help reduce these estimation errors? In this study, we tested whether training with trial-by-trial feedback about the signed deviation of the estimated from the actual TTC can improve TTC estimation accuracy for accelerating vehicles. Using a prediction-motion paradigm, we measured the estimated TTCs of twenty participants for constant-velocity and accelerated vehicle approaches, from a pedestrian's perspective in a VR traffic simulation. The experiment included three blocks, of which only the second block provided trial-by-trial feedback about the TTC estimation accuracy. Participants adjusted their estimations during and after the feedback, but they failed to differentiate between accelerated and constant-velocity approaches. Thus, the feedback did not help them account for acceleration. The results suggest that a safety training program based on trial-by-trial feedback is not a promising countermeasure against pedestrians' erroneous TTC estimation for accelerating objects.

The impact of target speed on pedestrian, bike, and speeding crash frequencies.

This research aims to investigate the influence of adopting the target speed concept on different types of crashes including pedestrian, bike, and speeding-related crashes. The Target speed is the highest speed that vehicles should operate on a roadway segment in a specific context. Based on the reviewed literature, this is the first study to investigate the relationship between target speed and crash frequency. Hence, big data including probe-vehicle data, traffic characteristics, geometric features, and land use attributes were utilized to develop crash prediction models. The main contributions of this research are to quantify the impacts of target speed on traffic safety considering context categories and to conclude the potential recommendations to lower different types of crashes. The 85th percentile speed was calculated and utilized in the developed models. Three crash prediction models were developed for pedestrian, bike, and speeding-related crashes. They were used in the analysis to quantify the impact of adopting target speed on different crash types. The results showed a significant reduction in the three crash types when using the target speed. Most of the improvements took place in three context categories: C3C: Suburban Commercial Segments, C3R: Suburban Residential Segments, and C4: Urban General Segments. Hence, this research recommends adopting target speed specifically in urban and suburban areas. Further, it suggests considering some measures to lower vulnerable road users' and speeding-related crashes. Following the recommendations of this research would help to reduce different types of crash frequency, hence, improving the mobility and safety for all users in different context classifications.

Investigating surrogate safety measures at midblock pedestrian crossings using multivariate models with roadside camera data.

This study aims to evaluate and compare Surrogate Safety Measures (SSMs) at five midblock Rectangular Rapid Flashing Beacons (RRFB) and two midblock Pedestrian Hybrid Beacons (PHB) sites in Florida using extensive video data collected over the study period of July to November 2021. Computer vision and data processing resulted in four pedestrian SSMs, namely spatial gap, temporal gap, relative time to collision (RTTC) and Post Encroachment Time (PET). An initial investigation of the SSMs using Mann-Whitney-Wilcoxon tests revealed significant differences in the SSM values across different treatment types and hours of the day. Additionally, univariate regression of spatial gap, and multivariate regression of temporal gap, RTTC and PET revealed significant differences of SSMs across RRFB and PHB sites. The study considered both linear and non-linear (gamma, inverse Gaussian and lognormal) regression models. After considering various traffic and operational parameters, the data were aggregated for each pedestrian-vehicle interaction on each lane to create a total of 395 observations. The SSMs included average spatial gap, temporal gap, RTTC and PET for each interaction of pedestrian and vehicle on each lane. The results indicated that non-linear models performed better than the linear models. Moreover, the presence of the PHB, weekday, signal activation, lane count, pedestrian speed, vehicle speed, land use mix, morning period and pedestrian starting position from the sidewalk have been found to be significant determinants of the SSMs. Results also suggest temporal SSMs increase at the PHB sites compared to the RRFB sites, indicating an improvement of traffic safety at PHB sites. However, the spatial gap decreased for PHB sites compared to the RRFB sites, which suggests that pedestrians tend to start to cross the RRFB sites when they perceive vehicles to be further away than at the PHB sites.

Kinematic cues in driver-pedestrian communication to support safe road crossing.

OBJECTIVE: Right-of-way negotiation between drivers and pedestrians often relies on explicit (e.g., waving) and implicit (e.g., kinematic) cues that signal intent. Since effective driver-pedestrian communication is important for reducing safety-relevant conflicts, this study uses information theory to identify vehicle kinematic behaviors that provide the greatest information gain and serve as cues for pedestrians to cross safely. DATA SOURCES: A driver-pedestrian dataset with 348 interactions was extracted from a large naturalistic driving data collection effort. It includes 325 instances of a pedestrian crossing the vehicle's path and 23 instances in which the vehicle did not yield to a pedestrian. Kinematic data were collected from the vehicle's CAN. Pedestrian behaviors, driver cues, and contextual information were manually annotated from a forward-facing video. METHODS: We used kernel density estimation to quantify the probabilities of vehicle acceleration, speed, and standard deviation of speed, for a given vehicle position and pedestrian behavior. Mutual information was then calculated between the estimated distributions given a pedestrian behavior (crossing/not crossing; walking/pausing) across intersection types (protected, e.g., stop signs; designated, e.g., crosswalks; and undesignated, e.g., jaywalking). RESULTS: The patterns mutual information conveyed by vehicle kinematics differed across measures (acceleration, speed, and standard deviation of speed) reaching peak values (in bits of information) at different distances from the pedestrian path. The mutual information conveyed by vehicle acceleration and pedestrian crossing behaviors peaked the farthest from the pedestrian path in the designated crossings, about 18 m away from the pedestrian path, with a difference in median deceleration of 1.01 m/s2 (p < 0.001) between pedestrian pausing and walking epochs. For protected crossings, the peak in mutual information occurred closer (10 m) to the pedestrian path, where median vehicle deceleration was significantly lower (0.55 m/s2; p < 0.05) in pausing epochs compared to walking epochs. For undesignated crossings, the peak in mutual information was the closest to the pedestrian crossing path, around 5 m, and was associated with a stronger deceleration behavior in pedestrian crossing epochs (-0.33 m/s2; p < 0.1). Vehicle speed demonstrated a similar sensitivity to distance from the pedestrian path across intersection types. Lastly, looking at the outcome of pedestrian behavior (i.e., crossing/not crossing), we find that the mutual information conveyed by acceleration, speed, and standard deviation of speed, peaked when the vehicle was at 30 m (stronger braking -0.37 m/s2; p < 0.1) and 10 m away, with greater acceleration (0.81 m/s2; p < 0.001) and faster speeds (2.41 m/s; p < 0.001) in pedestrian crossing epochs. SIGNIFICANCE OF RESULTS: This study examined driver-pedestrian information exchange using vehicle kinematic behavioral cues. We find that the differences in mutual information are shaped by multiple factors including the intersection type. In general, there was less mutual information gain in protected crossings which may be explained by unambiguous right-of-way rules guiding driver and pedestrian behavior, reducing the need for negotiation. Driver-pedestrian interactions in designated crossings seem to take place over a larger distance range compared to undesignated or protected crossings. These findings may support the design of automated driving and pedestrian safety systems that are able to consider the type, strength, and timing of kinematic cues to optimize driver-pedestrian negotiation. Eventually, such systems may enhance safe, efficient, and social interactions with pedestrians.

The impact of different service states of tunnel lighting on traffic safety.

The service states of tunnel lighting will directly affect the lighting conditions, which affect traffic safety. Therefore, it is imperative to evaluate and predict traffic safety accurately in different lighting states. In this research, three hundred experimental scenarios of the service states of tunnel lighting were designed and implemented to evaluate the impact of different service states of tunnel lighting on traffic safety. The evaluation was achieved through a visual identification experiment in a physical tunnel. The experimental results show higher simulated vehicle speeds pose a greater threat to traffic safety. The severity of lighting attenuation contributes to an increased risk to traffic safety. An increase in the number of luminaires failure also poses a greater threat to traffic safety. The newly proposed traffic safety factor was employed to evaluate traffic safety quantitatively in road tunnels. To improve the accuracy and comprehensiveness of the traffic safety factor prediction in different lighting service states, an advanced neural network prediction system was developed. The prediction system was constructed using the Sparrow Search Algorithm (SSA) to optimize Extreme Learning Machine (ELM) neural network, and the dataset from the experiment was used for the prediction model. The SSA-ELM neural network model is a reliable model that can predict the traffic safety factor comprehensively and accurately. The recommended threshold value for the traffic safety factor is 0.6. When the value falls below 0.6, it shows that the service states of tunnel lighting pose a threat to traffic safety in the tunnel. These findings can provide insights into the safe and energy-efficient maintenance of road tunnels.

Effect of distance information and number of warning signs on driving safety of young adults near road work zones in China.

The continuous growth of automobile ownership and road mileage in China has brought a lot of road maintenance work. The work zone shall be set for road maintenance work. Due to the road characteristics near the work zone, more accidents and a higher accident risk exist. Traffic signs are one of the essential means to ensure traffic safety. The location and number of road work signs (sign level) play a crucial role in driver safety near the work zone. The repeated road work signs can form a warning system to regulate driver behavior. This paper evaluates the effect of the number of warning signs with and without distance information on driver behavior (psychological load and physiological characteristics) near the work zone. The matter-element extension model is used for comprehensive evaluation. The study resulted in several findings. First, adding distance information improves the difficulty and time of visual recognition and enhances driver alertness. On the other hand, too many road signs are not conducive to maintaining driver alertness. Second, distance information on the work signs and the repeated setting of road warning signs add extra burden on the driver and increase driver fatigue. Third, driver's response to the repeated road work signs will gradually become stable; The speed transition under the warning signs Levels 2 and 3 are more stable than that under the warning sign Levels 1 and 4. Finally, the warning sign level shall not be more than 3. If the advanced warning area is short, it is recommended to select a warning sign Level 1. If the advanced warning area is relatively long, it is recommended to choose a warning sign Level 2. Finally, adding distance information will improve the overall effect of the warning scheme. These findings can provide a valuable reference for setting the road work signs near the work zone in practice in China.

Road safety hazards for children while commuting to school: Findings from a pilot study in Karachi, Pakistan.

INTRODUCTION: Road traffic injuries are a leading cause of mortality and morbidity among children. Travelling to and from school is a major risk exposure for children around the globe. OBJECTIVE: The purpose of this study was to assess road traffic injury hazards for school children during dropp-off or picked-up times. METHODS: This observational cross-sectional study included 94 public and private schools in Karachi, Pakistan. A structured observational tool was used to collect data on school demographics, the road traffic environment, infrastructure, injury hazards in vehicles used by school children, and child pedestrian injury risk and road use behaviors. RESULTS: A total of 860 observations of school children, drivers of vehicles transporting children, schools, and vehicles were recorded. Most schools (n = 83, 88%) did not have designated parking spaces around the school; only one public school had a parking area. Only one private school had a zebra crossing around the school premises. Very few schools (n = 13, 14%), mostly private (n = 12) had pedestrian sidewalks. Only 35 (18%) adult motorcyclists, out of 199, were wearing a helmet, and eight (6%), out of 145, car passengers were wearing seatbelts. Compressed natural gas (CNG) cylinders were installed in 83 (35%), out of 235, observed vehicles. The remaining 152 (65%) did not have CNG cylinders or they were not visible to our data collectors. In 55 (23%) observations, bus passengers stepped off the bus in the middle of the road. Most pedestrians (n = 266, 99.5%) did not use a Zebra crossing. More than a quarter (n = 74, 28%) of pedestrians looked left and right before crossing the road. CONCLUSION: While traveling to school, either by walking or taking vehicular trips, children face many road traffic injury hazards in Karachi. Pedestrians and passengers exhibited risky behaviors while using roads. Further initiatives are advised from a public health viewpoint aiming at minimizing transport-related hazards.

Reducing deaths and injury from road traffic crashes through multisectoral collaboration.

Introduction: road traffic injuries are the eighth cause of mortality globally, killing about 1.35 million people and leaving more than 50 million others with permanent injuries and disabilities yearly. In Tanzania, the impact of road traffic crashes is still high despite a noticeable reduction in the number of associated injuries. This paper seeks to lay the foundation for promoting multisectoral actions and collaborations in dealing with public health concerns due to increased consequences caused by road traffic deaths and injuries. Methods: in 2015, a multisectoral approach was adopted to implement a 5-year (2015-2020) road safety program that aimed to advocate for amendment of the Road Traffic Act of 1973, Chapter 168 Revised Edition 2002. A series of consultative sessions were held between government and non-state actors, including different committees formed to feed each other on the agenda. The program was implemented through the Ministry of Health and the Ministry of Home Affairs in collaboration with World Health Organisation and civil society organisations. Results: it has been noted that there is a direct relation with a set of combined policy-level interactions seeking to improve the legal environment for road safety. The program committee, civil society organisations, and parliamentarians' forum were solicited as essential stakeholders in advancing policy reform. Together they conducted a series of consultative meetings, resulting in having a Bill tabled in the Parliament as a first draft. This informed policymakers and raised their attention to the magnitude of road traffic crashes and the country's social and economic burden. Conclusion: efforts still need to be expanded to analyse the existing data to understand the extent to which risk factors contribute to road crashes, injuries, and deaths. There is a need to have a strong Government involvement in strengthening ownership and sustainability of any public health intervention, such as road safety.

Nanoparticles for cancer therapy: a review of influencing factors and evaluation methods for biosafety

Nanoparticles are widely used in the biomedical field for diagnostic and therapeutic purposes due to their small size, high carrier capacity, and ease of modification, which enable selective targeting and as contrast agents. Over the past decades, more and more nanoparticles have received regulatory approval to enter the clinic, more nanoparticles have shown potential for clinical translation, and humans have increasing access to them. However, nanoparticles have a high potential to cause unpredictable adverse effects on human organs, tissues, and cells due to their unique physicochemical properties and interactions with DNA, lipids, cells, tissues, proteins, and biological fluids. Currently, issues, such as nanoparticle side effects and toxicity, remain controversial, and these pitfalls must be fully considered prior to their application to body systems. Therefore, it is particularly urgent and important to assess the safety of nanoparticles acting in living organisms. In this paper, we review the important factors influencing the biosafety of nanoparticles in terms of their properties, and introduce common methods to summarize the biosafety evaluation of nanoparticles through in vitro and in body systems (AU)

Safety risk assessment for autonomous vehicle road testing.

OBJECTIVE: Road testing can accelerate the development and validation of autonomous vehicles (AVs). AV road testing can come with high safety risks, particularly in a complex road traffic environment, due to the immaturity of AV technology. A priori safety risk assessments of the road traffic environment before AV road testing are of great importance, allow the quantifying of risk levels in different road scenarios, and provide guidelines for AV road testing in low to high-risk environments. METHODS: This study proposes a framework, namely Safety Risk Assessment for AV road testing (SRAAV), based on the probability and severity of five categories of potential AV accidents. Four groups of influencing factors are considered comprehensively in assessing AV safety risk, and their impacts are quantified using impact coefficients derived from a Bayesian network and empirical AV road testing data. The safety risk is assessed on a road section level, based on which an overall risk level is defined for a corridor and a region. Afterwards, the quantified safety risk is classified into four levels according to expert experience and knowledge, through a questionnaire survey. RESULTS: Applications of the proposed SRAAV framework are conducted for urban roads in Shanghai, and expressways in Shanghai and Gothenburg. The assessment results are validated using disengagement data from AV road testing. The results show that the SRAAV framework and its models could estimate the safety risk levels of road traffic environments for AV road testing in a sound way and have the flexibility for further extensions to be made. CONCLUSIONS: The framework and assessment results can provide technical support for determining where and when to grant permission for public roads to be used for AV road testing, and how to choose public roads from a low to a high risk level, guaranteeing the safety of AV public road testing.

Pedestrians' unsafe road-crossing behaviors in Iran: An observational-based study in West Azerbaijan.

OBJECTIVE: Pedestrians are one of the most vulnerable users in road traffic injuries (RTIs). The rate of pedestrians' fatality is high in Iran. It is worthwhile to investigate how pedestrians behave. This observational study aimed to investigate pedestrians' unsafe behaviors while crossing. METHODS: This cross-sectional study examined the behavior of 1095 pedestrians (69.7% men) using videotaping when they crossed at two intersections and three non-intersections on a weekend and two working days in the morning, at noon, and in the evening. The information obtained was classified into 5 domains including adherence to traffic rule, violation, environmental barriers, visibility, and distraction. Data were analyzed using Stata version 17. RESULTS: About 60% of the pedestrians ignored the crosswalk and crossed the street wherever they wanted. More than 30% ignored the vehicles passing and crossed the street inattentively. About 60% of the pedestrians committed violations. More than half of pedestrians crossed unsafe crossings diagonally or in a hurry. More than 35% wore dark clothing and had low visibility, and nearly 30% were distracted. Adolescent pedestrians did not adhere traffic rules about 6 times more than the young adult pedestrians. Pedestrians who did not adhere to traffic rules in the morning were significantly more than in the evening. Men committed a violation 1.47 times more than women. The results showed that the pedestrians committed a violation in the morning significantly more than in the evening. CONCLUSION: The occurrence of pedestrians' unsafe behaviors in Maku was high. Unsafe behaviors were high among men and young adult pedestrians. Therefore, it's essential to implement educational interventions via different media as well as environmental interventions by different organizations to improve safe behavior among pedestrians.

Spatial analysis of road traffic crashes and user based assessment of road safety: A case study of Rotterdam.

OBJECTIVE: To perform a spatial analysis of Road Traffic Crashes (RTCs) and assess road safety issues from the perspective of road users. PROBLEM STATEMENT: Although many initiatives have been taken to reduce the occurrence and severity of RTCs, they continue to persist. Existing research often investigates the spatial occurrence of RTCs or the perception of road safety issues from the road user. In doing this, only a limited number of factors that contribute to RTCs can be revealed, whereas in most RTC occurrences a multitude of factors plays a role. A more integrated approach combining both knowledge areas can contribute to improving road safety. METHODS: RTCs that occurred from 2018 to 2020 in Rotterdam, in the Netherlands, were spatially analyzed. This was performed using Network Kernel Density Estimation (NKDE) analysis. Two zones within the study area were selected to understand road users' perceptions of road safety through a survey. Furthermore, opinions toward possible recommendations for improving road safety were also collected through key informant interviews. RESULTS: NKDE resulted in a hot-spot map of the road segments in the study area that showed the frequency of RTCs using different colors. The road segments were classified based on the number of RTCs from 2018 to 2020, ranging from zero to 17.9 RTCs per kilometer. This led to the selection of a hot and cold spot zone for further analysis. The road user perception survey resulted in the discovery of qualitative responses that can be used to improve road safety in future and the possible recommendations would be well received by them. The key-informant interviews acted as a backup to the opinions given by the road users and provided insights on what is being done in the study area to improve road safety. CONCLUSION: The synthesis of findings unveiled why road users perceive some areas as dangerous and which road policies need to be revised to improve road safety in Rotterdam.

Effect of a Gun Safety Video on Children's Behavior Around Real Guns: A Randomized Clinical Trial.

Importance: Firearms are the leading cause of death for children in the US. It is therefore crucial to identify effective ways to reduce firearm injuries among children. Objective: To test the effectiveness of a gun safety video vs a car safety video on decreasing unsafe behaviors around real guns after exposure to a violent movie with vs without guns. Design, Setting, and Participants: Of 245 participants aged 8 to 12 years, 226 were tested (13 did not complete the laboratory portion, 4 had technical problems, and 2 did not respond to follow-up inquiries). Data were collected from February 2 to October 16, 2022. Participants were recruited via Facebook ads, ResearchMatch, and parent or guardian referrals. The study was conducted in 2 parts. Children watched a safety video at home 1 week before coming to the laboratory at The Ohio State University. Interventions: Pairs of children were randomly assigned to watch a 1-minute gun or car safety video at home. In the laboratory, they were randomly assigned to watch a 20-minute clip from a violent PG-rated movie with or without guns. Next, they played with games and toys for 20 minutes in another room that contained 2 disabled 9-mm handguns hidden in a file cabinet drawer. Sessions were videotaped via a hidden camera. Main Outcomes and Measures: Outcomes were whether children told an adult, touched a handgun, handled it, or pulled the trigger. Control variables were age, gender, race and ethnicity, trait aggressiveness, age-inappropriate media exposure, firearm attitude and interest, presence of firearms at home, and whether children had taken a firearm safety course. Results: Of 226 children (mean [SD] age, 9.99 [1.38] years; 113 [52.3%] male), 216 (95.6%) found a gun and were included in analyses. Those who saw the gun (vs car) safety video were more likely to tell an adult about the gun they found (38 of 112 [33.9%] vs 11 of 104 [10.6%]), were less likely to touch the gun (44 of 112 [39.3%] vs 70 of 104 [67.3%]), held the gun fewer seconds if they did touch it (mean [SD], 42.04 [121.46] vs 98.96 [195.10]), were less likely to pull the trigger at all (10 of 112 [8.9%] vs 31 of 104 [29.8%]), and pulled the trigger fewer times (mean [SD], 4.20 [20.17] vs 7.23 [15.75]). Being male, exposure to age-inappropriate movies, and gun interest were related to unsafe behavior. Prior completion of a firearm safety course, having guns at home, and negative gun attitudes were related to safe behavior. Conclusions: In this trial of children assigned to watch a gun or car safety video, watching a gun safety video reduced children's unsafe behavior around real guns. Children who had previously taken a gun safety course, had guns in the home, and had negative attitudes toward guns were less likely to engage in unsafe behavior around real guns. To encourage safe firearm behavior, children should be educated about gun safety and should not watch age-inappropriate media. Trial Registration: ClinicalTrials.gov Identifier: NCT05257837.

The association between diabetes and safe driving: A systematic search and review of the literature and cross-reference with the current guidelines.

AIMS: We conducted this review to characterize the quality of evidence about associations between diabetes and safe driving and to evaluate how these findings are reflected within current guidelines available to support clinicians and their patients with diabetes. METHODS: The first stage entailed a systematic search and review of the literature. Evidence surrounding harms associated with diabetes and driving was identified, screened, extracted and appraised for quality utilizing the Newcastle Ottawa Scales (NOS). Next, relevant guidelines regarding driving and diabetes were sourced and summarized. Finally, the identified guidelines were cross-referenced with the results of the systematic search and review. RESULTS: The systematic search yielded 12,461 unique citations; 52 met the criteria for appraisal. Fourteen studies were rated as 'high', two as 'medium' and 36 as 'low'. Studies with ratings of 'high' or 'medium' were extracted, revealing a body of inconsistent methods and findings. These results, cross-referenced with the guidelines, suggest a lack of agreement and a limited evidence base to justify recommendations. CONCLUSIONS: The results presented emphasize the need for a better understanding of the impacts of diabetes on safe driving to inform evidence-based guidelines.

Reliability of the 44-question Home Fall Hazard Assessment Tool and demographic characteristics associated with home hazards among the Thai elderly.

Background: The 44-question Thai Home Fall Hazard Assessment Tool (Thai-HFHAT) was developed to assist healthcare professionals in identifying the risk of falls among community-dwelling older adults from their home environment. However, the reliability of this tool has not been studied. This study aimed to examine the reliability of the 44-question Thai-HFHAT and determine the demographic characteristics associated with home hazards. Methods: A descriptive cross-sectional study design was used to evaluate inter-rater reliability. The participants in this study were 51 older people from various types of Thai houses: a one-story elevated house, a one-story non-elevated house, and a house with two or more floors, 51 caregivers of older patients, and 5 village health volunteers (VHV). A prospective design was used to evaluate test-retest reliability with older people at different times in their homes. All participants answered 44 Thai-HFHAT questions to determine inter-rater and test-retest reliabilities. The reliabilities were analyzed using an intra-class correlation coefficient (ICC). Demographic characteristics including sex, occupation, and education were used to identify the factors affecting home hazards, and linear regression was used to analyze. Results: The ICC of inter-rater reliability of the 44-question Thai-HFHAT was 0.74 (95% CI: 0.57-0.84) and the test-retest reliability was 0.80 (95% CI: 0.64-0.88) for the older adults, 0.80 (95% CI: 0.65-0.89) for the caregivers and 0.70 (95% CI: 0.477-0.83) for the VHV. In demographic variables, personal business career and education level (grades 1-3) had significant relations with the total number of home hazards in the 44-questions Thai-HFHAT. Conclusions: The 44-question Thai-HFHAT is suitable for home hazard assessment among older adults in Thailand. Further studies are needed to investigate changes in the house environment after using the 44-question Thai-HFHAT to determine which changes can reduce fall risk.

Pedestrian Crossing Sensing Based on Hough Space Analysis to Support Visually Impaired Pedestrians.

There are many visually impaired people globally, and it is important to support their ability to walk independently. Acoustic signals and escort zones have been installed on pedestrian crossings for the visually impaired people to walk safely; however, pedestrian accidents, including those involving the visually impaired, continue to occur. Therefore, to realize safe walking for the visually impaired on pedestrian crossings, we present an automatic sensing method for pedestrian crossings using images from cameras attached to them. Because the white rectangular stripes that mark pedestrian crossings are aligned, we focused on the edges of these rectangular stripes and proposed a novel pedestrian crossing sensing method based on the dispersion of the slope of a straight line in Hough space. Our proposed method possesses unique characteristics that allow it to effectively handle challenging scenarios that traditional methods struggle with. It excels at detecting crosswalks even in low-light conditions during nighttime when illumination levels may vary. Moreover, it can detect crosswalks even when certain areas are partially obscured by objects or obstructions. By minimizing computational costs, our method achieves high real-time performance, ensuring efficient and timely crosswalk detection in real-world environments. Specifically, our proposed method demonstrates an impressive accuracy rate of 98.47%. Additionally, the algorithm can be executed at almost real-time speeds (approximately 10.5 fps) using a Jetson Nano small-type computer, showcasing its suitability as a wearable device.

Vibrotactile Alerting to Prevent Accidents in Highway Construction Work Zones: An Exploratory Study.

Struck-by accidents are the leading cause of injuries in highway construction work zones. Despite numerous safety interventions, injury rates remain high. As workers' exposure to traffic is sometimes unavoidable, providing warnings can be an effective way to prevent imminent threats. Such warnings should consider work zone conditions that can hinder the timely perception of alerts, e.g., poor visibility and high noise level. This study proposes a vibrotactile system integrated into workers' conventional personal protective equipment (PPE), i.e., safety vests. Three experiments were conducted to assess the feasibility of using vibrotactile signals to warn workers in highway environments, the perception and performance of vibrotactile signals at different body locations, and the usability of various warning strategies. The results revealed vibrotactile signals had a 43.6% faster reaction time than audio signals, and the perceived intensity and urgency levels on the sternum, shoulders, and upper back were significantly higher than the waist. Among different notification strategies used, providing a moving direction imposed significantly lower mental workloads and higher usability scores than providing a hazard direction. Further research should be conducted to reveal factors that affect alerting strategy preference towards a customizable system to elicit higher usability among users.

Automated Road Defect and Anomaly Detection for Traffic Safety: A Systematic Review.

Recently, there has been a substantial increase in the development of sensor technology. As enabling factors, computer vision (CV) combined with sensor technology have made progress in applications intended to mitigate high rates of fatalities and the costs of traffic-related injuries. Although past surveys and applications of CV have focused on subareas of road hazards, there is yet to be one comprehensive and evidence-based systematic review that investigates CV applications for Automated Road Defect and Anomaly Detection (ARDAD). To present ARDAD's state-of-the-art, this systematic review is focused on determining the research gaps, challenges, and future implications from selected papers (N = 116) between 2000 and 2023, relying primarily on Scopus and Litmaps services. The survey presents a selection of artefacts, including the most popular open-access datasets (D = 18), research and technology trends that with reported performance can help accelerate the application of rapidly advancing sensor technology in ARDAD and CV. The produced survey artefacts can assist the scientific community in further improving traffic conditions and safety.