Factors contributing to hit-and-run crashes in China

Hit-and-run accidents, or those where the perpetrator leaves the crash scene without reporting the event, are a serious concern because they can delay the rescue of victims, thereby increasing the fatality rate and severity of injuries. However, only a few studies exist on the factors that influence hit-and-run behavior, particularly in developing countries. Using data collected from Guangdong Province in China, this study applies a logistic regression model to analyze factors associated with hit-and-run behavior in five categories: crash attributes and human, vehicle, road, and environmental factors. This study finds that the probability of hit-and-run behavior increases with accidents that involve pedestrians, occur in dark driving conditions, and are caused by drivers who are male, middle-aged, and without a valid driver’s license, extensive driving experience, or automobile insurance. Therefore, we recommend closer supervision and better public education for different groups of people about traffic laws and regulations.     

Transition patterns of driving style from a traditional driving environment to a connected vehicle environment: A case of an extra-long tunnel road

To provide a better understanding of individual driver’s driving style classification in a traditional and a CV environment, spatiotemporal characteristics of vehicle trajectories on a road tunnel were extracted through a driving simulator-based experiment. Speed, acceleration, and rate of acceleration changes are selected as clustering indexes. The dynamic time warping and k-means clustering were adopted to classify participants into different risk level groups. To assess the driver behavior benefits in a CV environment, an indicator BI (behavior indicator, BI) was defined based on the standard deviation of speed, the standard deviation of acceleration, and the standard deviation of the rate of acceleration change. Then, the index BI of each driver was calculated. Furthermore, this paper explored driving style classification, not in terms of traditional driving environment, but rather the transition patterns from a traditional driving environment to a CV environment. The results revealed that inside a long tunnel, 80 % of drivers benefited from a CV environment. Moreover, drivers might need training before using a CV system, especially female drivers who have low driving mileage. In addition, the results showed that the driving style of 69 % of the drivers’ transferred from a high risk-level to a low risk-level when driving in a CV environment. The study results can be expected to improve driving training education programs and also to provide a valuable reference for developing individual in-vehicle human-machine interface projects and other proactive safety countermeasures.     

Analyzing pedestrian behavior when crossing urban roads by combining RP and SP data

Considering the high crash rates involving pedestrians on urban roads, it is highly relevant to understanding pedestrian crossing behavior. This paper is the first to combine stated preference (SP) and revealed preference (RP) data to evaluate the impact that individual attributes, trip characteristics, built environment, strategies to prevent unauthorized crossing, and traffic flows have on pedestrians crossing decisions in an urban context. SP and RP surveys were designed and collected in Barranquilla (Colombia) near pedestrian bridges or signalized intersections where direct crossings and a high concentration of pedestrian fatalities related to traffic accidents exist. A logit model was estimated using the data enrichment paradigm. Results show that pedestrians weigh risks and costs when choosing how to cross the road. The trajectories observed in the RP component suggest that people prefer direct crossings; nevertheless, pedestrian bridges and signalized intersections can be attractive alternatives if their location matches the origin or destination of the crossing, and no detour is needed to use them. Waiting time; safety; the fine imposed for jaywalking; personal security, and previous decisions are also variables that influence pedestrian behavior when crossing urban roads. These results can be helpful to urban planners and decision-makers interested in proposing appropriate pedestrian infrastructure. The data pooling technique and the inclusion of a cost-related variable (i.e., fine) allowed computing the willingness to pay and marginal substitution rates for attributes of the built environment and other characteristics associated with the crossing decision. Also, the inclusion of several crossing alternatives and situations allowed assessing pedestrian crossing preferences under different scenarios.     

Australian parents’ willingness to use a rideshare vehicle to transport their unaccompanied children

This study aimed to identify the key factors associated with Australian parents' willingness to use a rideshare vehicle to transport their unaccompanied child(ren). Six hundred and thirty-one participants completed an online survey (M = 39.2 years, SD = 10.5, Range = 18.0–70.0 years; Female: 63.4%). Most participants (62.1%) reported that they would 'never' use a rideshare vehicle to transport their unaccompanied child(ren). The results of a logistic regression model showed that participants': previous use of a rideshare vehicle with their child, annual mileage, propensity for technology adoption, aberrant driving behaviours, as well their requirements for vehicle features were significantly associated with their willingness to use a rideshare vehicle to transport their unaccompanied child, χ2(7) = 159.59, p < 0.001. Overall, the findings suggest that Australian parents are mostly ‘unwilling’ to use a rideshare vehicle to transport their unaccompanied children. Understanding the views of parents towards emerging transportation modes for their children is crucial for urban planning, traffic engineering, economic and social mobility and ultimately, on supporting safe modes of transportation.     

External communication of automated vehicles in mixed traffic: Addressing the right human interaction partner in multi-agent simulation

The urban traffic system is most likely to change in the next years to a mixed traffic with human drivers, vulnerable road users, and automated vehicles. In the past, the development of external communication approaches for automated vehicles focused on scenarios where an automated vehicle communicates with either a pedestrian or a human driver. However, interactions with more than one traffic partner are more realistic. Therefore, a study with 42 participants was conducted with a multi-agent simulation in which an automated vehicle interacted simultaneously with two participants, a pedestrian and a driver of a manual vehicle. In this study, two main scenarios were investigated in order to evaluate the safety and efficiency of the interactions and to determine whether the human road users feel correctly addressed. In one scenario, the pedestrian had to cross the road in front of the automated and the manual vehicle, which were approaching from different sides. In the other, the manual vehicle had to drive through a bottleneck in front of the oncoming automated vehicle, while the pedestrian had to cross the road after both vehicles passed. The communication approach of the automated vehicle consisted of implicit signals using a speed profile and lateral offset within its lane, and explicit signals using an external human–machine interface. The results of the study show that no collisions were observed in terms of safety and no significant negative effects on efficiency were measured. However, in contrast to single agent interactions, a majority of participants felt wrongly addressed in situations where the automated vehicle signals the right-of-way to the other human road user. It can be concluded that the communication approach of the automated vehicle needs to be modified in order to address certain road users more clearly.     

The role of values in road safety culture: Examining the valuation of freedom to take risk,risk taking and accident involvement in three countries

National focus on individual freedom versus paternalistic values is a fundamental theme, which defines the status of traffic safety in different countries. The present study examines the role of such values in road safety culture based on survey data from car and bus drivers from three countries with distinctly different road safety records: Norway (N = 596), Israel (N = 129) and Greece (N = 386). While Norway has the highest road safety level in Europe, and Israel also performs better than the EU average, the road safety level in Greece was far below the EU average. As these positions reflect differences in policies and national regulations in drivers’ freedom to take risk, we hypothesize a higher focus on individual freedom to take risk and lower focus on paternalism among the Greek drivers. Results indicate, in accordance with our hypothesis, that the Greek drivers value freedom to take risk in traffic higher than drivers from Norway and Israel. Greek drivers also expect higher levels of risk taking from other drivers in their country, they report higher levels of risky driving themselves, and are more often involved in accidents. Thus, it seems that values have an important role in Road Safety Culture (RSC), legitimizing and motivating risky driving, which are related to accidents. We found, however, contrary to our hypotheses, that the Greek drivers also had the most paternalistic attitudes among the drivers in the three countries. In the present paper, we try to solve this Greek paradox.     

A method in modeling interactive pedestrian crossing and driver yielding decisions during their interactions at intersections

Investigating pedestrian crossing and driver yielding decisions should be an important focus considering the high risks of pedestrians in exposed to motorized traffic. Limitations, however, exist in previous studies – variables considered previously have been limited; how their behavior affect each other (defined as interactive impacts) were not sufficiently considered. This paper aims to provide a methodological approach for pedestrian crossing and driver yielding decisions during their interactions, considering of different variable types including interactive impact variables, traffic condition variables, road design variables, and environment variables. A Distance-Velocity (DV) framework proposed in an earlier study is introduced for definitions and concepts in studying pedestrian-vehicle interactions. Logistic regression, support vector machines, neural networks and random forests, are introduced as candidate models. A case study involving six crosswalk locations is conducted, focusing on interactions between pedestrians and right-turn vehicles. The proposed methodological approach is applied, with the performance of the four machine learning methods compared in terms of model generalization and confusion matrix. The model with the best performance is further compared to the typical gap-based model. Results show that random forest and logistic regression models performed the best in modeling pedestrian crossing and driver yielding decisions respective, in terms of model generalization. Besides, the DV-based modeling method (average accuracy of over 90% for pedestrians and 80% for drivers) outperformed the traditional gap-based method in all test seeds. As a key finding, interactive impacts from each other (the pedestrian and the driver) act as a key contributing variable on their decisions.     

Personality and demographic differences in the perceived risks of potentially timid driving behaviours

Timid driving behaviours can be described as overly cautious and hesitant driving behaviours. Little research has examined behaviours that potentially resemble timid driving and how these behaviours are perceived by other drivers. This is despite the potential for these behaviours to be perceived in a way that leads to angry and aggressive retaliatory behaviours in some drivers (e.g., in anger-prone drivers). We conducted an online survey examining the perceived road safety risks of several behaviours that could potentially result from timid driving and their relationships with driver personality (trait anxiety, trait driving anger), behaviour (anxious driving, angry driving), and demographic (age, gender, annual mileage) background. Drivers (N = 439, M_age = 49.41 ± 5.59 years, aged 18–89) perceived excessively cautious and unpredictable braking behaviours as posing moderate levels of risk. Multiple linear regression analyses also indicated higher perceived risks of slow and excessively cautious behaviours in older, male, and anger prone drivers. No meaningful associations were found between driver characteristics and the risks of unpredictable braking behaviours. These results suggest that safety campaigns to reduce aggressive behaviour may benefit from targeting the perceptions of other drivers’ behaviours.     

Self-reported anger among ordinary and delivery electric bike riders in China: A comparison based on the cycling anger scale

As vulnerable traffic participants, electric bike (EB) riders have suffered from high collision casualties in recent years. Road user anger has been shown to affect riding behavior and lead to traffic accidents. Besides, studies have highlighted that there may be differences in road user anger in driving different vehicles due to varying perceptions of the relative vulnerability of vehicle type characteristics (control performance and cognitive processes). However, current road user anger investigations for two-wheelers have focused mainly on conventional cyclists, and little attention has been paid to e-bike riders, especially with the emerging group of delivery e-bike (DEB) riders. This study aims to develop a Cycling Anger Scale (CAS) for EB riders based on the Cycling Anger Scale and explore the road user anger experienced by EB riders and the differences between ordinary and delivery EB riders. The survey was conducted in Nanjing, China, and collected from 281 Ordinary EB (OEB) riders and 268 DEB riders. Exploratory factor analysis and confirmatory factor analysis are conducted to determine the revised four-factor structure of the 14-item CAS for EB. The results show that the scores of police interaction and cyclist interaction on the CAS subscales are significantly different between the OEB and DEB groups. The police interaction is the largest source of anger for both groups. Besides, the aggressive riding behaviors are significantly correlated with riding anger, which can be predicted by different aspects of riding anger for the two types of EB riders. This study provides a theoretical basis for designing intervention measures and safety education programs to enhance EB riders’ road safety.     

Effects of aging on whole body and segmental control while obstacle crossing under impaired sensory conditions

The ability to safely negotiate obstacles is an important component of independent mobility, requiring adaptive locomotor responses to maintain dynamic balance. This study examined the effects of aging and visual–vestibular interactions on whole-body and segmental control during obstacle crossing. Twelve young and 15 older adults walked along a straight pathway and stepped over one obstacle placed in their path. The task was completed under 4 conditions which included intact or blurred vision, and intact or perturbed vestibular information using galvanic vestibular stimulation (GVS). Global task performance significantly increased under suboptimal vision conditions. Vision also significantly influenced medial–lateral center of mass displacement, irrespective of age and GVS. Older adults demonstrated significantly greater trunk pitch and head roll angles under suboptimal vision conditions. Similar to whole-body control, no GVS effect was found for any measures of segmental control. The results indicate a significant reliance on visual but not vestibular information for locomotor control during obstacle crossing. The lack of differences in GVS effects suggests that vestibular information is not up-regulated for obstacle avoidance. This is not differentially affected by aging. In older adults, insufficient visual input appears to affect ability to minimize anterior–posterior trunk movement despite a slower obstacle crossing time and walking speed. Combined with larger medial–lateral deviation of the body COM with insufficient visual information, the older adults may be at a greater risk for imbalance or inability to recover from a possible trip when stepping over an obstacle.