Game-based situation awareness training for child and adult cyclists

The efficacy of hazard perception training and education: A systematic review and meta-analysis

BACKGROUND

Hazard perception (HP) has been argued to improve with experience, with numerous training programs having been developed in an attempt to fast track the development of this critical safety skill. To date, there has been little synthesis of these methods.

OBJECTIVE

The present study sought to synthesise the literature for all road users to capture the breadth of methodologies and intervention types, and quantify their efficacy.

DATA SOURCES

A systematic review of both peer reviewed and non-peer-reviewed literature was completed. A total of 57 papers were found to have met inclusion criteria.

RESULTS

Research into hazard perception has focused primarily on drivers (with 42 studies), with a limited number of studies focusing on vulnerable road users, including motorcyclists (3 studies), cyclists (7 studies) and pedestrians (5 studies). Training was found to have a large significant effect on improving hazard perception skills for drivers (g = 0.78) and cyclists (g = 0.97), a moderate effect for pedestrians (g = 0.64) and small effect for motorcyclists (g = 0.42). There was considerable heterogeneity in the findings, with the efficacy of training varying as a function of the hazard perception skill being measured, the type of training enacted (active, passive or combined) and the number of sessions of training (single or multiple). Active training and single sessions were found to yield more consistent significant improvements in hazard perception.

CONCLUSIONS

This study found that HP training improved HP skill across all road user groups with generally moderate to large effects identified. HP training should employ a training method that actively engages the participants in the training task. Preliminary results suggest that a single session of training may be sufficient to improve HP skill however more research is needed into the delivery of these single sessions and long-term retention. Further research is also required to determine whether improvements in early-stage skills translate to improvements in responses on the road, and the long-term retention of the skills developed through training.

Development of a hazard prediction test for Chinese cyclists and its association with crash involvement

Introduction

Hazard perception is the ability to sense the road environment and predict and respond to the upcoming dangerous events, and this factor is closely related to cyclists' crash involvement. However, due to a lack of valid instruments, studies concerning the hazard predictions and crashes of cyclists in China remain limited. This study attempted to develop a hazard prediction test for cyclists.

Method

The experiment presented 44 video clips filmed from cyclists' perspectives to 61 children aged 13-16 years and 119 adults aged 18-30 years. After the video clip displayed a black screen, participants were asked to answer the following questions: "What is the hazard?" (question 1), "Where is the hazard?" (question 2), and "What happens next?" (question 3). The differences in test scores between cyclists with high and low levels of experience, cyclists of different ages, and crash-involved and noncrash-involved cyclists were compared to examine the validity of the test.

Results

The final test contained 21 video clips and the internal consistency reliabilities of the three questions were satisfactory. Experienced cyclists are better able to identify and predict hazards than are cyclists with less experience, and adult cyclists have better hazard prediction abilities than child cyclists. More importantly, crash-involved cyclists receiving lower scores with respect to their ability to identify and predict hazards than noncrash-involved cyclists, thus indicating that the discriminant validity of the test was acceptable.

Practical applications

This newly-developed test exhibits acceptable reliability and validity and can be used as an effective tool to measure the hazard prediction abilities of cyclists with different ages and levels of experience in China. The natural driving videos and test in the study may hold promise for future practical applications, and the implications for road safety are discussed.

Identifying motorist characteristics associated with youth bicycle-motor vehicle collisions

Objective: The objective of this study was to identify driver characteristics associated with youth bicycle-motor vehicle collisions in Alberta, Canada. Methods: Edmonton and Calgary police collision report data from the years 2010-2014 were used. From these data, motor vehicle collisions involving youth (<18 years old) were identified (cases). The controls were drivers who, over the same period, were involved in separate motor vehicle-only collisions but deemed not at fault using an automated culpability analysis. Control selection used the quasi-induced exposure method, assuming that not-at-fault drivers in collisions are representative of the typical driver (source population). Descriptive statistics, including proportions, medians, and interquartile ranges (as appropriate) were used to describe the characteristics of the case and control drivers. Purposeful variable selection techniques were used to inform multivariable logistic regression models and results are presented as adjusted odds ratios (aORs) and 95% confidence intervals (CIs). Results: Four hundred twenty-three drivers involved in youth bicycle-motor vehicle collisions were identified, as were 243,927 not-at-fault control drivers. Drivers >54 years old had higher odds of involvement in youth bicycle-motor vehicle collisions than drivers between 25 and 39 years old (aOR = 1.37; 95% CI, 1.03, 1.82). Compared to driving between 3:01 p.m. and 6:00 p.m., driving between 12:01 a.m. and 6:00 a.m. (aOR = 0.27; 95% CI, 0.11, 0.66), between 6:01 a.m. and 9:00 a.m. (aOR = 0.61; 95% CI, 0.44, 0.85), or between 9:01 a.m. and 12:00 p.m. (aOR = 0.26; 95% CI, 0.16, 0.41) had lower odds of bicyclist collision, whereas driving between 6:01 p.m. and 12:00 a.m. had higher odds (aOR = 1.34; 95% CI, 1.01, 1.79). Driving a truck/van had lower odds of bicyclist collision compared to driving a passenger car (aOR = 0.67; 95% CI, 0.48, 0.94). Conclusions: Culpability analysis is typically applied to motorists to identify transient exposures; however, this study used culpability analysis to select control drivers who could be compared with drivers involved in youth bicycle-motor vehicle collisions. This study highlights motorist characteristics in youth bicycle-motor vehicle collisions. In doing so, we hope to inform primary prevention strategies for motorists and the environment that will reduce collisions.