Naturalistic Driving Study in Brazil: An Analysis of Mobile Phone Use Behavior while Driving

The effects of distraction on younger drivers: A neurophysiological perspective

Distracted driving remains a significant cause of traffic accidents globally, including in Australia. However, many younger drivers still admit to using a phone while driving. A simulated driving study investigated the neurophysiological effects of visual, auditory, and higher-order cognitive (i.e., requiring the use of executive functions) distraction on young drivers. In total, 24 young adults aged 18-25 years completed four 8 min simulated driving sessions while concurrently engaging in various distractor tasks. Neurophysiological arousal was measured via EEG. Additionally, subjective workload and objective driving performance were assessed. Frontal beta and gamma power exhibited their highest levels during tasks involving higher-order cognitive and visual demands. The higher-order cognitive condition was rated as the most mentally demanding. In comparison, the visual condition had the most significant impact on both the standard deviation of speed and standard deviation of lateral positioning. This study has significant implications for all road users, particularly those aged 18-25 years, and it reinforces the importance of not using a phone while driving.

"It is a different type of policing than in the bush": Police officers' perceptions of the differences in enforcement of the phone use while driving legislation in rural and urban areas

Mobile phone use while driving continues to be a significant road safety concern, despite the severe legal countermeasures to reduce this behaviour. Phone use while driving-related crashes have been demonstrated to be an issue in rural areas, yet research into the impact of legal sanctions on phone use while driving has primarily focussed on urban areas. Therefore, this study aimed to investigate differences in enforcement of phone use while driving between rural and urban environments as reported by police officers. In addition, to provide necessary context, this study aimed to explore how the police officers perceive differences in drivers' engagement in phone use while driving between rural and urban environments. To address these aims, a total of 26 police officers from Queensland, Australia (18 with both rural and urban experience, 6 with only rural experience and 2 with only urban experience) completed an interview. A total of seven themes were developed from the data. Several differences between rural and urban environments were identified concerning different types of phone offending behaviour, as well as different resources, management and infrastructure that can impact police enforcement. For example, it was suggested that drivers in rural areas have less reasons to use their phone while driving. Nevertheless, when this behaviour does occur, it is more challenging to enforce this law in rural compared to urban environments. The results not only provide important contextual information for phone use while driving research, but also suggest that enforcement strategies for this behaviour may need to be recontextualised to incorporate the more nuanced aspects of rural policing.

Is distraction on the road associated with maladaptive mobile phone use? A systematic review

Maladaptive Mobile Phone Use (MMPU) (also known as Smartphone Addiction, Nomophobia, Fear of Missing Out, or Problematic Mobile Phone Use) is a growing mental health problem. However, the health and safety consequences of MMPU remain unexplored in many real-life contexts. A potential setting where MMPU may have some negative repercussions is on the road. It is well established that road users (e.g., drivers, motorcyclists, pedestrians, and cyclists) increasingly injure themselves or others due to distractions such as phone use while on the road. Emerging research suggests that MMPU is a possible determinant of this risky behaviour. Therefore, it is essential to investigate the relationship between MMPU and mobile phone use behaviour on the road, as it could help guide and improve interventions aimed at increasing road safety. This systematic review investigated the relationship between maladaptive mobile phone use and mobile phone use behaviour on the road in terms of attitudes and risk perception, intention, phone use engagement, performance changes, and safety outcomes. A total of 44 studies were identified with 47 unique samples of road users, of which 68.1% (32/47) were comprised of drivers, 19.1% (9/47) were pedestrians, 8.5% (4/47) were unspecified road users, and there was one group of motorcyclists and cyclists. Our findings confirmed that MMPU is related to risky behaviour on the roads. In the 29 studies considering observed or self-reported behaviour, 90.9% (30/33) found that road users who scored higher in MMPU are more likely to use their phones on the road as cyclists, drivers, motorcyclists, and pedestrians. Of the nine studies that analysed performance changes, 55.6% (5/9) showed evidence that MMPU changes the performance of road users engaging in mobile phone use, meaning that there is evidence suggesting that MMPU determines the level of impairment. Of the nine studies that analysed the safety-related-outcomes, 66.7% (6/9) found that the higher the MMPU score, the more likely road users are to experience safety-critical traffic events. This review contributes to the literature by showing a pathway between the negative health consequences of MMPU and road trauma. We also identified that the quality of the studies was generally low due to study design and blinding aspects. This field of research also lacks standard practices as researchers avoid using established and well-validated questionnaires, often creating new ones to measure MMPU. This hinders the generalisability of the findings and raises questions about the construct validity and external validity of MMPU. The usefulness of future research would be enhanced by a consistent methodological approach using the same scales based on standard behavioural definitions. The cross-disciplinary nature of MMPU effects means that transport and road safety professionals need to work with healthcare professionals and technology organisations to understand and address MMPU as a contributing factor to road crashes.

Drivers' self-regulatory behaviors in active and responsive scenarios

OBJECTIVE

Drivers usually appear to self-regulate their driving behaviors in situations considered to be challenging, such as mobile phone-distracted driving. It is important to clarify how drivers self-regulate their actual behaviors. In addition, few studies investigated driver distraction in active and responsive scenarios. Therefore, the present study aimed to gain a better understanding of drivers' actual self-regulation of driving behaviors and phone use behaviors while mobile phone-distracted driving in active and responsive scenarios. The contribution of compensatory beliefs to self-regulation was also explored.

METHODS

This study was conducted using a 2 (mobile phone use behaviors: phone calling vs. WeChat messaging) × 2 (scenarios: active vs. responsive) within-group design. A total of 34 participants completed a driving simulation experiment. The dependent variables of drivers' driving behaviors, phone use behaviors, and physiological data were collected. Participants' compensatory belief was also measured.

RESULTS

The results showed that the speed reduction in the stages with WeChat messaging was significantly greater than that in the stages with phone calls, and the speed reduction in the responsive scenario was significantly greater than that in the active scenario. Participants would adopt relatively equal phone-use-related self-regulatory behaviors in active and responsive scenarios. Participants with higher compensatory beliefs had relatively greater speed reduction in most scenarios, but fewer phone-use-related self-regulatory behaviors. In addition, the respiratory rate could contribute to evaluating the changes in drivers' physiological status during phone calling-distracted driving.

CONCLUSIONS

Participants would self-regulate driving behaviors and phone use behaviors according to different distracted driving tasks and scenarios. The driving-related self-regulation in WeChat messaging scenarios and responsive scenarios was greater. There was a trend in the effect of compensatory beliefs on actual self-regulatory behaviors, which needs to be further verified in the future. This study contributes to the verification of the different actual driving-related and phone-use-related self-regulatory behavior of drivers in active and responsive mobile phone distracted driving scenarios.

Driver Behavior Profiling and Recognition Using Deep-Learning Methods: In Accordance with Traffic Regulations and Experts Guidelines

The process of collecting driving data and using a computational model to generate a safety score for the driver is known as driver behavior profiling. Existing driver profiles attempt to categorize drivers as either safe or aggressive, which some experts say is not practical. This is due to the "safe/aggressive" categorization being a state that describes a driver's conduct at a specific point in time rather than a continuous state or a human trait. Furthermore, due to the disparity in traffic laws and regulations between countries, what is considered aggressive behavior in one place may differ from what is considered aggressive behavior in another. As a result, adopting existing profiles is not ideal. The authors provide a unique approach to driver behavior profiling based on timeframe data segmentation. The profiling procedure consists of two main parts: row labeling and segment labeling. Row labeling assigns a safety score to each second of driving data based on criteria developed with the help of Malaysian traffic safety experts. Then, rows are accumulated to form timeframe segments. In segment labeling, generated timeframe segments are assigned a safety score using a set of criteria. The score assigned to the generated timeframe segment reflects the driver's behavior during that time period. Following that, the study adopts three deep-learning-based algorithms, namely, Deep Neural Network (DNN), Recurrent Neural Network (RNN), and Convolutional Neural Network (CNN), to classify recorded driving data according to the established profiling procedure, and selects the most suitable one for a proposed recognition system. Various techniques were used to prevent the classification algorithms from overfitting. Using gathered naturalistic data, the validity of the modulated algorithms was assessed on various timeframe segments ranging from 1 to 10 s. Results showed that the CNN, which achieved an accuracy of 96.1%, outperformed the other two classification algorithms and was therefore recommended for the recognition system. In addition, recommendations were outlined on how the recognition system would assist in improving traffic safety.

Investigating the Effect of Social and Cultural Factors on Drivers in Malaysia: A Naturalistic Driving Study

Road accidents are increasing every year in Malaysia, and it is always challenging to collect reliable pre-crash data in the transportation community. Existing studies relied on simulators, police crash reports, questionnaires, and surveys to study Malaysia’s drivers’ behavior. Researchers previously criticized such methods for being biased and unreliable. To fill in the literature gap, this study presents the first naturalistic driving study in Malaysia. Thirty drivers were recruited to drive an instrumented vehicle for 750 km while collecting continuous driving data. The data acquisition system consists of various sensors such as OBDII, lidar, ultrasonic sensors, IMU, and GPS. Irrelevant data were filtered, and experts helped identify safety criteria regarding multiple driving metrics such as maximum acceptable speed limits, safe accelerations, safe decelerations, acceptable distances to vehicles ahead, and safe steering behavior. These thresholds were used to investigate the influence of social and cultural factors on driving in Malaysia. The findings show statistically significant differences between drivers based on gender, age, and cultural background. There are also significant differences in the results for those who drove on weekends rather than weekdays. The study presents several recommendations to various public and governmental sectors to help prevent future accidents and improve traffic safety.

A systematic review on sensor-based driver behaviour studies: coherent taxonomy, motivations, challenges, recommendations, substantial analysis and future directions

In the plan and development of Intelligent Transportation Systems (ITS), understanding drivers behaviour is considered highly valuable. Reckless driving, incompetent preventive measures, and the reliance on slow and incompetent assistance systems are attributed to the increasing rates of traffic accidents. This survey aims to review and scrutinize the literature related to sensor-based driver behaviour domain and to answer questions that are not covered so far by existing reviews. It covers the factors that are required in improving the understanding of various appropriate characteristics of this domain and outlines the common incentives, open confrontations, and imminent commendations from former researchers. Systematic scanning of the literature, from January 2014 to December 2020, mainly from four main databases, namely, IEEEXplore, ScienceDirect, Scopus and Web of Science to locate highly credible peer-reviewed articles. Amongst the 5,962 articles found, a total of 83 articles are selected based on the author's predefined inclusion and exclusion criteria. Then, a taxonomy of existing literature is presented to recognize the various aspects of this relevant research area. Common issues, motivations, and recommendations of previous studies are identified and discussed. Moreover, substantial analysis is performed to identify gaps and weaknesses in current literature and guide future researchers into planning their experiments appropriately. Finally, future directions are provided for researchers interested in driver profiling and recognition. This survey is expected to aid in emphasizing existing research prospects and create further research directions in the near future.

Is organized carpooling safer? Speeding and distracted driving behaviors from a naturalistic driving study in Brazil

Carpooling consists of drivers and passengers sharing a journey and its costs. Nowadays, in the context of mobility as a service, organized carpooling encompasses a service and trust relationship between drivers and passengers, by matching common routes and splitting cost through mobile phone applications. Therefore, passengers expect a certain level of travel quality and safety. In this context, this research aims to verify the hypothesis that drivers in an organized carpooling situation (CP) show safer driving behavior in terms of speeding (SP) and mobile phone use while driving (MPU) in comparison with non-carpooling (NCP) drivers. The research is based on data from the Brazilian Naturalistic Driving Study (NDS-BR) conducted in the City of Curitiba, with 40.45 driving hours and a traveled distance of 895.87 km. Methodology included the selection of safety performance indicators on SP and MPU, use of nonparametric Wilcoxon signed rank test for safety performance indicator comparisons and Pearson Chi-Square to test the association between CP or NCP and low or high indicator values. Hypothesis test results point in the same direction and partially confirm the initial assumption that CP induces safer behavior in terms of speeding. The statistically sound results showed that CP drivers engaged in less speeding episodes and mobile phone use duration in comparison to NCP drivers, as well as lower speed while using a mobile phone. In addition, driver behavior in CP and NCP situations also differed in terms of the type of MPU, with the proportion of types of use that demand a higher level of visual and manual distraction being higher among NCP drivers. In summary, these results confirm the initial hypothesis of safer driving behavior during carpooling in terms of MPU while driving.

Distracted Behavior of Pedestrians While Crossing Street: A Case Study in China

Pedestrians are the most vulnerable road users in the traffic system and thousands of pedestrians are injured or killed globally as a result of traffic crashes every year. With their popularity and enriched functions, mobile phones are playing an increasingly important role in people's lives, and records of vehicle crashes involving pedestrians have shown the hazards caused by distraction of mobile phone use, especially in the context of crossing the street. The present study employed the theory of planned behavior (TPB) to investigate the behavior of using a mobile phone while crossing the street in China. An online questionnaire based on the TPB framework was developed to collect data, and 387 eligible samples were retained after inspection. Mobile phone use while crossing the street is prevalent in China (i.e., 53%). The results show that three standard TPB constructs (i.e., attitudes, intention and perceived behavioral control) emerged as significant predictors of the behavior of using mobile phone while crossing, and two extended constructs (i.e., situation, mobile phone involvement) also significantly predicted the behavior. In addition, for this population, intention was the strongest predictor of the behavior among these significant constructs. Moreover, the results were discussed and compared with some existing studies and safety interventions were also provided.