Children's fear in traffic and its association with pedestrian decisions

INTRODUCTION

Research on risk for child pedestrian injury risk focuses primarily on cognitive risk factors, but emotional states such as fear may also be relevant to injury risk. The current study examined children's perception of fear in various traffic situations and the relationship between fear perception and pedestrian decisions.

METHOD

150 children aged 6-12-years old made pedestrian decisions using a table-top road model. Their perceived fear in the pedestrian context was assessed.

RESULTS

Children reported greater emotional fear when they faced quicker traffic, shorter distances from approaching traffic, and red rather than green traffic signals. Children who were more fearful made safer pedestrian decisions in more challenging traffic situations. However, when the least risky traffic situation was presented, fear was associated with more errors in children's pedestrian decisions: fearful children failed to cross the street when they could have done so safely. Perception of fear did not vary by child age, although safe pedestrian decisions were more common among the older children.

CONCLUSIONS

Children's emotional fear may predict risk-taking in traffic. When traffic situations are challenging to cross within, fear may appropriately create safer decisions. However, when the traffic situation is less risky, feelings of fear could lead to excessive caution and inefficiency. Practical applications: Child pedestrian safety interventions may benefit by incorporating activities that introduce realistic fear of traffic risks into broader safety lessons.

Effects of an in-vehicle eco-safe driving system on drivers' glance behaviour

We have designed a new in-vehicle eco-safe driving system and shown its effectiveness in prompting drivers to execute a fuel-saving and safe driving style (Vaezipour et al., 2018, submitted for publication). However, the system could also bring potential negative outcomes, i.e. driver distraction. This simulator study investigated drivers' glance behaviours as indicators of driver distraction when using our Eco-Safe Human-Machine-Interface (HMI). Four types of eco-safe information display conditions (baseline, advice only, feedback only, both advice and feedback) were tested on different traffic situations with varied road traffic complexity. Results showed that the eco-safe HMI system did not cause visual distraction. In contrast, the advice only or feedback only information improved forward gazing on the roadway. In addition, drivers tended to adapt their visual scanning strategies according to the traffic situations. In the car-following situation they paid longer glances to the forward roadway, while in the intersections they spent more time to look at the HMI system. The findings indicated that our eco-safe driving system improved drivers' eco-safe behaviours and meanwhile enhanced their visual attention on road while no evidence showed that drivers were distracted by it.

Analysis of safety factors for urban expressways considering the effect of congestion in Shanghai, China

Urban expressways are the key components of the urban traffic network. The traffic safety situation on expressways directly influences the efficiency of the whole network. A total of 48,325 crashes were recorded by Shanghai Expressway Surveillance System in a three-year period. Considering the different crash mechanisms under different congestion levels, models for the total crashes, non-congested-flow crashes and congested-flow crashes were respectively formulated based on the real-time traffic condition corresponding to each crash. Moreover, considering the potential spatial correlation among segments, the adjacent-correlated spatial and distance-correlated spatial models were formulated and compared to the traditional non-spatial-correlated model. A Bayesian approach was employed to estimate the parameters. The results showed that the congestion index, merging ratio, ramp density, and average daily traffic significantly affect the crash frequency. The safety factors in non-congested flow and congested flow are different; diverging behavior is more risky in non-congested flow, more lanes tend to increase the risk of crashes in congested flow, and horizontal curves tend to decrease the crash risk in congested flow but cause high risk in non-congested flow. In addition, the distance-correlated spatial model is found to be the best-fitting model. The results of this study suggested that dedicated safety countermeasures can be designed for different traffic situations on urban expressways.