Types Of Road Users Research Articles

Factors that predict hazard perception in older adult road-users: A systematic review

Background: Older adults are more likely to be at-fault and killed in road crashes, and this has been argued to be due to their declining hazard perception (HP). There has been no comprehensive review on what factors predict this decline in HP ability for older adults. Objectives: The aim of this systematic review is to identify any predictors of HP in older adults across all road-user types. Data Sources: The search was indexed in the Medline, PsycINFO, and Scopus during January 2022. Studies had to be peer reviewed and written in English language. Participants had to be road-users over the age of 60. Studies had to investigate a relationship between a predictor and HP. Results: 21 articles met the inclusion criteria, 20 for drivers and one for pedestrians. Seven predictors were examined. Results suggested that driving experience and auditory distraction were the most consistent predictors of HP. HP training for drivers significantly improved HP. Results were mixed for visual abilities, cognitive abilities, and age. Training for pedestrians was not a significant predictor of HP. Limitations: Grey literature was not reviewed. Conclusions: Whilst results related to age were mixed, most studies suggested that advancing age is associated with HP decline. Driving experience appeared to be a protective factor against decline in HP. Contrast and motion sensitivity may be important in identifying at-risk drivers. Cognitive function was not a consistent predictor of HP. Auditory distractors consistently negatively impacted HP. Results indicated that there could be potential benefits of HP training. There is a dearth of research into HP in vulnerable road user types. Implications: By identifying the predictors of HP, road safety strategies such as holistic training programs could be developed to assist with keeping older adult road-users safe. Future research is necessary to explore HP in older pedestrians, cyclists, and motorcyclists.

Measuring the Level of Road Safety through Road Safety Audit– A Case Study from Himalayan Expressway

National Highways (NH) carry the major portion of the total traffic in India. Road safety on NH is therefore of paramount importance. In the present study, a road safety audit has been performed for a 4-lane NH using Star Rating method. VIDA software developed by International Road Assessment Programme (IRAP) is used for finding the Star Rating of the road sections. This safety rating has been determined for four road user types: Vehicle occupant, Motorcyclist, Pedestrian and Bicyclist. The purpose of the study is to measure the level of road safety and lower the severity level by proposing countermeasures. The case study is a 5(km) section of NH-5 from Sanwara toll plaza to Jabali in the state of Himachal Pradesh in India. Encroachment on the land, roadside activities, insufficient infrastructure, imperfections in the geometric design, and non-motorized access were some of the severe safety flaws identified through the study process. The Star Rating results indicated that among all the road user types, the vehicle occupant is much safer than the others.

Pattern of Road Traffic Injuries and Their Pre-hospitalization Factors Reported at a Public Tertiary Healthcare Facility and Rural Private Healthcare Facility in Rajasthan, India.

We aimed to report the pattern of road traffic injuries (RTIs) and pre-hospitalization factors of road traffic injuries among the accident victims reported at an urban and arural healthcare facility in the Jaipur district, Rajasthan. This cross-sectional study was conducted in a tertiary-level, urban public healthcare facility in Jaipur city and a secondary-level, rural private facility in nearby Chomu town. The study participants were all those who encountered road traffic injury and visited any of these healthcare facilities to seek care. The study tool included information on demographics, type of road user, vehicles, accidents, roads, environment, and other pre-hospitalization factors. Data collectors were nurses trained to collect data using the tablet-based application. Data were analyzed using proportions/percentages. Bivariate analysis was done to assess the significance of differences between categories of factors and between rural and urban facilities. Among 4,642 cases, 93.8% were enrolled in the urban facility, and the remaining were enrolled in the rural facility. Predominantly, males (83.9%) and young adults 18-34 years (58.9%) were reported in both study facilities. Among the accident victims reported at the urban facility, major groups were educated up to the primary level (25.1%) or graduate level (21.9%). About 60% of them were drivers. Most of these injuries occurred on urban roads (50.2%) or two-lane roads (42%). About three-fourths of the injured were using two-wheeler geared vehicles, and 46.7% were overtaking or turning the vehicle when the accident happened. The majority of cases (61.6%) did not require hospitalization. Among the rural facility participants, 27.2% were graduates, and 24.7% were below primary education. Most of these injuries happened on the national highway (35.8%) or rural roads (33.3%). Most of them used two-wheeler geared (80.1%) at the time of the accident. Most were injured while doing normal straight driving (80.5%). Most participants (80.1%)in the rural facility did not follow the traffic rules, and 43.9% required hospitalization. Young males were the most affected age group by road traffic injuries. Differential patterns of road traffic injuries and pre-hospital factors were observed in urban and rural areas.

Age-specific characteristics of road traffic injuries among children and adolescents in South Korea

Objective Road traffic injuries (RTIs) are the leading cause of mortality among children and adolescents. This study aimed to identify and compare the age-specific epidemiology, clinical characteristics and factors related to severe RTIs among children and adolescents who had RTIs. Methods This multicenter cross-sectional study was conducted using data collected between January 2011 and December 2018 in the Emergency Department-based Injury In-depth Surveillance registry in South Korea. A total of 66,632 participants younger than 19 years who presented with RTIs to emergency departments (EDs) were classified under three age groups: preschoolers (age 0–6 years, n = 18,694), elementary school student (age 7–12 years, n = 21,251), and middle and high school student (age 13–18 years, n = 26,687). Data on demographic and injury-related factors were analyzed, and multivariate logistic regression was used to determine the factors related to severe RTIs, which were defined as the Excess Mortality Ratio-based Injury Severity Score ≥16. Results RTIs among children and adolescents were more common in boys (71.0%), during weekdays (39.7%), in the summer (31.1%), and between 12 noon and 6 pm (47.9%). The most common type of road users were passengers (preschoolers, 46.4%) and cyclists (age 7–12 years and age 13–18 years, 50.1% and 36.2%, respectively). The proportion of head injury was highest in the preschoolers group (57.3%). The length of ED stay, Excess Mortality Ratio-adjusted Injury Severity Score, and the proportion of intensive care unit admission increased with age. Nighttime (0–6 am), vulnerable road users (motorcyclists, bicyclists, and pedestrians), and use of emergency medical services were significantly associated with severe injury. Conclusions The three age groups of patients younger than 19 years with RTIs differed in the types of road user, proportions of injured body regions, and clinical outcomes. In an effort to reduce RTIs to children and adolescents, age-specific focused intervention should be considered. Additionally, the injury severity was found to be associated with nighttime occurrence, vulnerable road users, ED visit through emergency medical services, and nonuse of safety devices across all age group.

Sharing roads with automated vehicles: A questionnaire investigation from drivers’, cyclists’ and pedestrians’ perspectives

Despite the promised benefits, the introduction of Automated Vehicles (AVs) on roads will be confronted by many challenges, including public readiness to use those vehicles and share the roads with them. The risk profile of road users is a key determinant of their safety on roads. However, the relation of such risk profiles to road users’ perception of AVs is less known. This study aims to address the above research gap by conducting a cross-sectional survey to investigate the acceptance of Fully Automated Vehicles (FAVs) among different non-AV-user groups (i.e., pedestrians, cyclists, and conventional vehicle drivers). A total of 1205 road users in Queensland (Australia) took part in the study, comprising 456 pedestrians, 339 cyclists, and 410 drivers. The Theory of Planned Behaviour (TPB) is used as the theoretical model to examine road users’ intention towards sharing roads with FAVs. The risk profile of the participants derives from established behavioural scales and individual characteristics are also included in the acceptance model. The study results show that pedestrians reported lowest intention in terms of sharing roads with FAVs among the three groups. Drivers and cyclists in a lower risk profile group were more likely to report higher intention to share roads with FAVs than those in a higher risk profile group. As age increased, pedestrians were less likely to accept sharing roads with FAVs. Drivers who had more exposure time on roads were more likely to accept sharing roads with FAVs. Male drivers reported higher intention towards sharing roads than female drivers. Overall, the study provides new insights into public perceptions of FAVs, specifically from the non-AV-user perspective. It sheds light on the obstacles that future AVs may encounter and the types of road users that AV manufacturers and policymakers should consider closely. Specifically, groups such as older pedestrians and road users who engage in more risky behaviours might resist or delay the integration of AVs.

Injury severity and injury patterns in older participants in road traffic

Older people are or remain increasingly mobile for longer and participate in road traffic as car drivers or passengers, cyclists, and pedestrians. Regardless of their role in causing accidents, they are more likely to be seriously injured due to their higher vulnerability. If they are involved in an accident they suffer increasingly more from severe injuries, which consequently leads to longer hospitalization times. These aspects are even more applicable for persons aged75 years or more than for persons aged 65-74 years. From aGerman in-depth accident study (GIDAS) analysis of the individual injuries of different types of road users, the most frequently severely injured body regions as well as the leading injuries can be derived. Primarily head and thorax injuries are of importance and secondarily also injuries to the lower extremities (especially for cyclists and pedestrians). The majority of the presented results confirm findings from comparable studies; however, this study was conducted for the first time on the basis of the abbreviated injury scale (AIS) 2015 and some individual injuries (especially commotio cerebri, which dominates in almost all age and road user groups) were upgraded from AIS1 to AIS2 in the latest AIS revision. As aresult, the current results partly show significant increases in injury severity, especially for the head, compared to earlier studies based on the AIS 2008.

Shared space multi-modal traffic modeling using LSTM networks with repulsion map and an intention-based multi-loss function

Shared space is an innovative, yet controversial concept of traffic regulation that features the coexistence of different types of road users (cars, motorcycles, bicycles, pedestrians, etc.), with the same priority (no traffic lights or signs) and in the same, unsegregated environment. The effect on traffic conditions, as well as on safety, has not yet been systematically documented due to the lack of dedicated traffic models and simulation tools. In this paper, we develop a variation of the Occupancy LSTM network, enhanced with spatial and temporal proximity aspects and a sophisticated, intention-based loss function that models interactions in a shared space environment and predicts the trajectories of vehicle and pedestrian users. The model achieves a significant prediction accuracy, which allows its exploitation for simulating shared space conditions. Moreover, a simulation experiment is designed to evaluate the concept of shared space in terms of efficiency and safety. Results indicate that the interactions that take place in such an environment would lead to a slight increase of travel time for both types of users (compared to free flow conditions) and a low number of possible conflicts.

Examining the Trends in Motor Vehicle Traffic Deaths in New York City, 1999-2020.

Monitoring and understanding the trends in motor vehicle traffic (MVT) mortality is crucial for developing effective interventions and tracking progress in reducing deaths related to MVT. This study aimed to assess the trends in MVT mortality in New York City from 1999 through 2020. Publicly available de-identifiable mortality data were abstracted from the Centers for Disease Control and Prevention's Wide-ranging Online Data for Epidemiologic Research. MVT deaths were identified using the International Classification of Diseases Codes, 10th Revision: V02-V04 (.1, .9), V09.2, V12-V14 (.3-.9), V19 (.4-.6), V20-V28 (.3-.9), V29-V79 (.4-.9), V80 (.3-.5), V81.1, V82.1, V83-V86 (.0-.3), V87 (.0-.8), and V89.2. Age adjusted mortality rates (AAMR) were abstracted by county (Bronx; Kings; Queens; New York), age (in years) (< 25; 25-44; 45-64; ≥ 65), sex (male; female), race/ethnicity (Non-Hispanic Black; Non-Hispanic White; Asian/Pacific Islander; Hispanic), and road user type (motor vehicle occupant; motorcyclist; pedal cyclist; pedestrian). Joinpoint regression models were fitted to estimate the annual percentage change (APC) and average annual percentage change (AAPC) in AAMR during the study period. The Parametric Method was used to compute 95% confidence intervals (CI). Between 1999 and 2020, a total of 8,011 MVT deaths were recorded in New York City. Mortality rates were highest among males (age adjusted mortality rate (AAMR) = 6.4 per 100,000; 95% CI: 6.2, 6.5), Non-Hispanic Blacks (AAMR = 4.8; 95% CI: 4.6, 5.0), older adults (AAMR = 8.9; 95% CI: 8.6, 9.3), and persons from Richmond County (AAMR = 5.2; 95% CI: 4.8, 5.7). MVT death rates, overall, have declined by 3% per year (95% CI: -3.6, -2.3) from 1999 to 2020. The rates have fallen or stabilized by race/ethnicity, county of residence, road user type, and age group. In contrast, rates have increased by 18.1% per year among females and by 17.4% per year in Kings County from 2017 to 2020.The results of this study draw attention to the worsening trends in MVT mortality among females and in Kings County, New York City. Further investigation is needed to determine the underlying behavioral, social, and environmental factors contributing to this increase, such as polysubstance or alcohol abuse, psychosocial stressors, access to medical and emergency care, and compliance with traffic laws. These findings emphasize the importance of developing targeted interventions to prevent MVT deaths and ensure the health and safety of the community.

Characteristics of crash-involved drink and drug car drivers and motorcyclists

Objective Drug driving is an issue of growing concern among Australian jurisdictions, including South Australia. In order to have an appropriate response to drug driving in regard to policy and enforcement, it is important to have sound knowledge about the patterns of drug use among motorists and the associated risks of this behavior. Method To this end, this study examined the characteristics of 1,277 hospitalized road users in South Australia in the years 2014 to 2017, with reference to whether or not they tested positive for alcohol or other drugs (the three drugs tested for according to the South Australian Road Traffic Act (1961): THC, methamphetamine, MDMA). This examination used a database combining hospital data, police-reported crash data, licensing information, and the result of alcohol and drug tests conducted by Forensic Science SA. Results It was found that more motorists were positive for one or more of the three illicit drugs than for alcohol, reversing long established trends. Comparisons were made between alcohol and drug free motorists, alcohol positive motorists, drug positive motorists, and motorists positive for both drugs and alcohol, with drivers of cars and motorcyclists analyzed separately where possible. Findings include: that those combining drugs and alcohol only comprise a small proportion of hospitalized motorists; that drug drivers tend to be younger than other hospitalized motorists; that drivers are more likely to test positive to alcohol or methamphetamine, while motorcyclists are more likely to test positive to THC; motorists testing positive to drugs and/or alcohol tend to exhibit a range of other risky behaviors; and motorists testing positive to drugs and/or alcohol tend to sustain more severe injuries in the event of a crash. Conclusions Preventing drink and drug driving is important not only for reducing crash numbers but also injury severity in the event of a crash. Substance use differs by road user type and age, which has potential implications for enforcement practices.

Analysis of Transport and Vehicular Road Crash Cases in Metro Manila from 2016 to 2020

Introduction. Metro Manila, the metropolitan center and seat of the national government, is composed of 16 cities and 1 municipality, and considered as the second-most populous region in the Philippines. Transport is a key sector that is needed for accessibility and economic progress. Yet, the question on safety of the roads of Manila remains as road crashes continue to be reported.Objective. The study aims to determine the trend of road crashes in Metro Manila, and the factors associated with both fatality and injury among three types of road users – the drivers, the passengers, and the pedestrians.Methods. A retrospective analysis of 523,059 road crash data between 2016 to 2020 was done. Using descriptive statistics, the road crash variables analyzed in the study were (1) crash classification according to damage to property, fatal, and non-fatal crash, (2) road user type according to driver, passenger, and pedestrian, (3) vehicle type, (4) junction type, and (5) risky road user behavior. Logistic and multinomial regression models were used to determine whether these variables were significant with road user fatality and injury.Results. The analysis of the MMARAS database (n=523,059) showed an increasing trend of road crashes occurred since 2016 and peaked in 2019, and declined in 2020. Majority (436,367, 83.426%) were damage to property, followed by non-fatal or injurious cases (84751, 16.203%) and fatal outcomes (1941, 0.371%). Drivers have the greatest number of fatalities and injuries compared to passengers and pedestrians. Cars (513482 52.322%) and motorcycles (136641, 13.923%) remain the major types of vehicles involved in road crashes. The factors that were significantly associated with increased odds ratio for driver death were involvement of pedicabs (OR=10.937, p=0.000), motorcycles (OR=55.061, p=0.000), bus (OR=5.835, p=0.000), truck (OR=7.073, p=0.000), hit object (OR=11.007, p=0.000), self-accident (OR=6.149, p=0.000), and collisions in bridges/flyovers (OR=2.713, p=0.010)). The factors that were significantly associated with increased odds ratio for passenger fatality were the involvement of motorcycle (OR=3.75, p=0.021), angle impact (OR=42.01, p=0.002), multiple collision (OR=18.42, p=0.040), self-accident (OR=32.66, p=0.010), and lost control (OR=82.98, p=0.001). The factors significantly associated with pedestrian fatality were hit and run (OR=56.04, p=0.000), hit pedestrian (OR=1085.17, p=0.000), and crashes in bridges/flyover (OR=4.20, p=0.025). Meanwhile, multinomial regression showed that classification of crash and vehicle type were significantly associated with fatal and non-fatal crashes.Conclusion. The study showed the trend of fatality and injury among drivers, passengers, and pedestrians from2016-2020, and factors of road crashes in Metro Manila including vehicle type, road behaviors, collision type and junction type.

Humans vs, machines; motorcyclists and car drivers differ in their opinion and trust of self-drive vehicles

Self-drive vehicles have the potential to revolutionise transport systems, however their adoption by mainstream users is highly dependent on a range of factors including trust. Moreover, perceptions of self-drive cars are likely to be highly dependent on the lived-experience of different road user types. Motorcyclists have high impressions of road-vulnerability and distrust for other road users. This distrust stems from the evidence that the vast number of motorcycle crashes occur as a consequence of other-driver error. We therefore hypothesised that compared with car drivers, vulnerable road users such as motorcyclists would report high levels of other-driver distrust, but high levels of trust in self-drive cars. We conducted semi-structured interviews with motorcyclists and car drivers and found that motorcyclists are indeed distrustful of other drivers but have higher levels of trust for self-drive cars compared with car drivers, while car drivers have low levels of trust for self-drive cars, but high levels of trust for other drivers. Motorcyclists were also more likely to report a perspective of trust that centred around their own personal safety on the road. This study provides valuable insights into different road user’s perceptions of AVs.

Do bicyclists and pedestrians support their city as an autonomous vehicle proving ground? Evidence from Pittsburgh

Autonomous vehicles (AVs) have made significant progress in recent years, including entering the testing stage on urban roads. However, there still is a relative lack of knowledge on the public acceptance of AV road tests in their cities. This paper fills this gap by modeling the survey data collected by BikePGH in Pittsburgh. Special attention was paid to two types of typical vulnerable road users, bicyclists and pedestrians. An ordered probit model was built to investigate the factors associated with bicyclists’ and pedestrians’ willingness to support their city as an AV proving ground. The model results indicated that adults aged 65 years and older were more likely to support AV testing than those aged 25-44 years old. Bicyclists’ and pedestrians’ attitudes on the perceived safety and benefits of AVs were positively associated with the willingness to support their city as an AV proving ground. Also, we applied a mediation model to explore the suppressor variable, finding that the influence of interactive experience on bicyclists’ and pedestrians’ willingness to support AV tests in their city was mainly suppressed by the perceived safety of AVs. We recommend AV companies protect the rights of vulnerable road users when testing their AVs on proving grounds.

Crossing the street in front of an autonomous vehicle: An investigation of eye contact between drivengers and vulnerable road users.

Communication between road users is a major key to coordinate movement and increase roadway safety. The aim of this work was to grasp how pedestrians (Experiment A), cyclists (Experiment B), and kick scooter users (Experiment C) sought to visually communicate with drivengers when they would face autonomous vehicles (AVs). In each experiment, participants (n = 462, n = 279, and n = 202, respectively) were asked to imagine themselves in described situations of encounters between a specific type of vulnerable road user (e.g., pedestrian) and a human driver in an approaching car. The human driver state and the communicative means of the approaching car through an external Human-Machine Interface (eHMI) were manipulated between the scenarios. The participants were prompted to rate from "never" to "always" (6-point Likert scale) the frequency with which they would seek eye contact with the human driver either in order to express their willingness to cross or to make their effective decision to cross. Our findings revealed that a passive human driver in an AV with no visual checking on the road triggered a decline in vulnerable road users' desire to communicate by eye contact (Experiments A-C). Moreover, the results of Experiment C demonstrated that the speed screen, the text message screen, and the vibrating mobile app eHMI signals diminished kick scooter users' desire to communicate visually with the human driver, with some age-based differences. This suggested a better comprehension of the approaching car's intentions by the kick scooter users, driven by the features of the eHMI.

Estimate of the magnitude of risky and protective behaviors associated with road traffic injuries in capitals participating in the Life in Traffic Project of Brazil.

BackgroundBrazil occupies the fifth position in the ranking of the highest mortality rates due to RTI in the world. With the objective of promoting traffic safety and consequently reducing deaths, Brazil created the Life in Traffic Project (LTP). The main goal of LTP is reducing 50% of RTI deaths, by promoting interventions to tackle risk factors, such as driving under the influence of alcohol and excessive and/or inappropriate speed. Thus, the aim of this study was to estimate the magnitude of risky and protective factors for RTI in capitals participating in the LTP in Brazil. We estimated these factors according to sociodemographic (age group, sex, education, race and, type of road user).MethodsA total of 5,922 car drivers and motorcyclists from 14 Brazilian capitals participating in the LTP were interviewed. Data collection was carried out in sobriety checkpoints at night and consisted of the administration of an interview and a breathalyzer test. Risky and protective behaviors associated with RTI were investigated. Covariates of the study were: age, sex, education, race and, type of road user. Poisson multiple regression analysis was used to assess the relationship between variables of interest.ResultsThe prevalence of individuals with positive blood alcohol concentration (BAC) was 6.3% and who reported driving after drinking alcohol in the last 30 days was 9.1%. The others risky behaviors reported were: driving at excessive speed on roads of 50 km/h, using a cell phone for calls while driving, using a cell phone to send or read calls while driving, running a red light. Use of seatbelts and helmets showed prevalence above 96,0% Use of seatbelts showed prevalence of 98.6% among car drivers, and helmet use was described by 96.6% of motorcycle drivers. Most risky behaviors were more prevalent in younger age groups (except BAC measurement higher in older participants), in males (except for cell phone use), in participants with higher education level and without a driver’s license.ConclusionExcessive speed and driving under the influence of alcohol, defined as priorities within the LTP, need more consistent interventions, as they still have considerable prevalence in the cities investigated. The factors described such as cell phone usage and passing red traffic lights should also need to be prioritized as a focus on promoting traffic safety.

Approaching intersections: Gaze behavior of drivers depending on traffic, intersection type, driving maneuver, and secondary task involvement

Urban intersections are hotspots for crashes because they provide a location for several traffic streams and types of road users to cross. A main cause of crashes is the misinformation of drivers as they fail to sense relevant visual information. We aimed to analyze the gaze behavior of car drivers in a variety of intersection scenarios, bringing together the partial findings of previous research, and examine the interdependencies of the contributing factors to provide a database for driver modeling. In a driving simulator study with 59 participants, we varied intersection scenarios regarding drivers’ right of way (yield sign, green traffic light), intersection type (T junction, X intersection), surrounding traffic (none, irrelevant, relevant), and intended driving maneuver (left turn, right turn, going straight). A total of 25 intersection scenarios were presented in a within-subjects design to a control group and a group with a cognitive load task (counting back in numbers of two). Fixations were coded regarding defined areas of interest in the field of view and separated according to three segments of the intersection approach: 75–50 m, 50–25 m, and 25–0 m before entering the intersection. The results show that the effect of surrounding traffic, secondary task engagement, and the intended driving maneuver changed dramatically depending on the right of way of the driver. Surrounding traffic primarily affected gaze behavior in scenarios of ceding the right of way close to the intersection entry. The cognitive load task increased fixations on the road center especially in situations where the driver had the right of way, but less in situations of ceding the right of way. Interactions with the type of intersection were only apparent for different driving maneuvers. This study provides a detailed and comprehensive picture of drivers’ attentional processes when approaching intersections which is relevant for understanding and modeling of driver behavior in urban traffic.

Measuring the Level of Road Safety through Road Safety Audit and Star Rating Method – A Case Study from Himalayan Expressway

National Highways (NH) carry the major portion of the total traffic in India. Road safety on NH is therefore of paramount importance. In the present study, a road safety audit has been performed for a 4-lane NH using Star Rating method. ViDA software developed by International Road Assessment Programme (iRAP) is used for finding the Star Rating of the road sections. This safety rating has been determined for four road user types: Vehicle occupant, Motorcyclist, Pedestrian and Bicyclist. The purpose of the study is to measure the level of road safety and lower the severity level by proposing countermeasures. The case study is a five Kilometre (km) section of NH-5 from Sanwara toll plaza to Jabali in the state of Himachal Pradesh in India. Encroachment on the land, roadside activities, insufficient infrastructure, imperfections in the geometric design, and non-motorized access were some of the severe safety flaws identified through the study process. The Star Rating results indicated that among all the road user types, the vehicle occupant is much safer than the others.

The long-memory temporal dependence of traffic crash fatality for different types of road users

This study investigates the long-memory auto-correlations within daily fatality time series data of the driver, passenger, bicyclist, and pedestrian, and the long-memory cross-correlations between the fatality series of different road users. The analysis is based on the traffic crash fatalities in Florida during the period 1975–2015. A detrended fluctuation analysis (DFA) and a detrended cross-correlation analysis (DCCA) are used for capturing the long-memory auto-correlations and the cross-correlations, respectively. The investigation is conducted through the following steps: (1) identifying the periodicity of the traffic fatalities series via traditional signal processing methods; (2) removing the season effects identified by simple average value analysis and principal component analysis (PCA) from the original time series; (3) based on the original and processed series, exploring the long-memory auto-correlations and cross-correlations in the time series data of different road users. The results of DFA indicate that the auto-correlations of the fluctuations in the daily fatalities are positive for all road users regardless of the seasonal effects. The results of DCCA indicate that the fluctuation in the fatalities for any type of road user is positively associated with that for other road users. The fluctuation in traffic fatalities for any road user is therefore not random-walk but correlated to their fluctuations in the last time unit and that of other road users during the same period. The findings of this study add to the understanding of the long-memory property in traffic fatalities and provide implications for the development of time series models in the traffic safety field.

Can Complete-Novice E-Bike Riders Be Trained to Detect Unmaterialized Traffic Hazards in the Urban Environment? An Exploratory Study

Although hazard perception is an important skill found to be crucial for negotiating traffic among various types of road users, few studies have systematically investigated e-bike riders’ ability to perceive potential unmaterialized hazardous situations or aimed to enhance these abilities through training. The present study explored the formation of two hazard perception training interventions based upon exposing young complete-novice e-bike riders to a vast array of materialized traffic hazards, with the aim of evaluating their effectiveness in enriching the ability to anticipate unmaterialized hazards. Young complete-novice e-bike riders were allocated into one of two intervention modes (‘Act and Anticipate Training’ or ‘Predictive and Commentary Training’) or a control group (ten in each group). AAT members underwent a theoretical tutorial, then observed clips depicting real-time hazardous situations footage taken from an e-bike rider’s perspective and were asked to perform a hazard detection task. PCT members underwent a theoretical tutorial, then a ‘what might happen next?’ task, followed by observation of video footage with expert commentary. A week later, participants were requested to complete a hazard perception test, during which they viewed ten videos and pressed a response button whenever they identified a hazardous situation. Overall, participants in both interventions were more aware of potential unmaterialized hazards compared to the control in both their response sensitivity and verbal descriptions. Trainees were responsive to the developed training interventions. Thus, actively detecting materialized hazards may produce effective training that enriches these road users’ hazard perception skills and allows them to safely negotiate traffic. Advantages of each of the training methodologies along with implications for intervention strategies, licensing, and policy development are discussed.

UI Design of eHMI of Autonomous Vehicles

In recent years there has been an increasing trend for autonomous vehicles (AV) to feature an external human-machine interface (eHMI). This study investigates the usability issues of an eHMI composed of light bands and displays that need to communicate with multiple types of road users and how designers intend to map all this and cover all these needs in one user interface design. In the first experiment, a physical prototype was built in a conventional car and shown to 18 participants. In the second experiment, the same eHMI concept, with improvements made from the first usability test, was shown to 500 participants in a digital prototype. In both tests, the usability of eHMIs, as well as the overall acceptance level of AVs before and after reviewing the eHMI concept, were evaluated. The results indicate that our eHMI designs positively influenced overall acceptance because they have clearer driving information and sense the visibility of the AV system. In close traffic negotiations when AVs communicate on the basis of what they sense and perceive, people felt uncomfortable with AVs perceiving them, which will be an increasingly important issue in the design conversation between fully autonomous AVs and general road users.

Prevalence of alcohol among drivers, riders and pedestrians injured in road traffic crashes in Cameroon: A cross-sectional study

This study aims to determine the prevalence of alcohol among injured road traffic crash victims (motor vehicle drivers, motorcycle riders, and pedestrians) admitted to three major health centers in Cameroon (one in Douala and two in Yaoundé). This study also investigated the associations between alcohol use and some socio-demographic and injury characteristics among injured road users, such as gender and age, level of education, religion, type of road user, time of day and week, and injury severity. Alcohol use was measured using breathalyzers, and data on age, gender, education level, religion, type of road user, time of the crash, crash characteristics, and injury severity were recorded using a questionnaire. Of the 350 participants, 30.9% had blood alcohol concentrations (BACAC s) above 0.08% (legal limit for drivers); the proportion was highest among motorcycle riders (36.5%), followed by pedestrians (24.8%) and motor vehicle drivers (18.9%). The proportion with BACAC above 0.08% was highest on weekend nights and among those who were most seriously injured. Those who reported being Muslims had a lower prevalence of alcohol. Multivariable logistic regression analysis confirmed those associations. Many road traffic injuries could have been avoided if the patient had not consumed alcohol. Actions should therefore be taken to reduce the proportion of alcohol-impaired road users.