How does drivers' visual search change as a function of experience? A systematic review and meta-analysis

Developing a taxonomy of hazards and hazard mitigation strategies for Motorised mobility scooter users

The increased use of motorised mobility scooters (MMSs) presents a road safety challenge as using a MMS has risks for the user, pedestrians, and other road users. In relation to enhancing MMS driving safety, much of the training and available literature focuses on training vehicular control. Equally important is the need to investigate higher-order cognitive skills involved in driving MMSs, particularly hazard perception. Through a large questionnaire study with MMS users, we develop a taxonomy of the types of hazard MMS users encounter when crossing roads and strategies that are used to negotiate these hazards. Whilst MMS experience modulated hazard perception and strategy use, a core set of hazards and strategies were identified that have policy and practice implications for training interventions and the built environment. Exploration of the advantages and disadvantages of MMS use indicated its impact on various wellbeing outcomes as well as some potential barriers to use.

The evaluation of eye-catching effect in freeway tunnel entrance zone based on fixation behavior characteristics

OBJECTIVE

The visual attraction of the freeway tunnel entrance zone will affect the driver's visual performance and visual workload, and then affect the driving safety. The purpose of this study is to explore the influence of different visual attraction conditions in the entrance zone of the freeway tunnel on driver's fixation behavior, and then evaluate the impact of eye-catching effect on driving safety.

METHODS

Thirty-five participants were recruited for the naturalistic driving experiment. Four different visually attractive driving scenarios (baseline, landscape-style architecture, tip slogan, and billboard) were selected. Participants' fixation behavior data were collected using an eye-tracking device. The effects of the visual attraction conditions in the freeway tunnel entrance zones were analyzed on driver fixation duration, number of fixations, fixation deviation, and pupil diameter.

RESULTS

The results demonstrated significant effects of different visual attractions in the entrance zone of the freeway tunnel on drivers' fixation behavior. Under the visual attraction of the billboard, drivers exhibited the most number of fixations. And under the visual attraction of tip slogan, drivers had the longest average fixation duration, the smallest horizontal fixation deviation, the largest vertical fixation deviation, and the highest pupil diameter and its coefficient of variation.

CONCLUSIONS

It can be concluded that different visual attractions in the freeway tunnel entrance zone have different effects on the eye-catching effect of drivers, by influencing the fixation behavior characteristics of drivers. Billboard is most effective in capturing drivers' visual attention, and tip slogan requires greater attention allocation and visual cognitive effort from drivers, resulting in the highest visual cognitive workload. This study highlights the complex relationship between visual attraction and its performance on driver fixation behavior. The insights from this study can provide valuable references for the design and optimization of the visual environment in the entrance zone of freeway tunnels.

Visual and steering behaviours during lane departures: a longitudinal study of interactions between lane departure warning system, driving task and driving experience

Lane Departure Warning Systems (LDWS) generate a warning in case of imminent lane departure. LDWS have proven to be effective and associated human-machine cooperation modelled. In this study, LDWS acceptance and its impact on visual and steering behaviour have been investigated over 6 weeks for novice and experienced drivers. Unprovoked lane departures were analysed along three driving tasks gradually more demanding. These observations were compared to a baseline condition without automation. The number of lane departures and their duration were dramatically reduced by LDWS, and a narrower visual spread of search during lane departure events was recorded. The findings confirmed LDWS effectiveness and suggested that these benefits are supported by visuo-attentional guidance. No specific influence of driving experience on LDWS was found, suggesting that similar cognitive processes are engaged with or without driving experience. Drivers' acceptance of LDWS lowered after automation use, but LDWS effectiveness remained stable during prolonged use.Practitioner summary: Lane Departure Warning Systems (LDWS) have been designed to prevent lane departure crashes. Here, LDWS assessment over a 6-week period showed a major drop in the number of lane departure events increasing over time. LDWS effectiveness is supported by the guidance of drivers' visual attention during lane departure events.

Comparison of Experienced and Novice Drivers' Visual and Driving Behaviors during Warned or Unwarned Near-Forward Collisions

Forward collision warning systems (FCWSs) monitor the road ahead and warn drivers when the time to collision reaches a certain threshold. Using a driving simulator, this study compared the effects of FCWSs between novice drivers (unlicensed drivers) and experienced drivers (holding a driving license for at least four years) on near-collision events, as well as visual and driving behaviors. The experimental drives lasted about six hours spread over six consecutive weeks. Visual behaviors (e.g., mean number of fixations) and driving behaviors (e.g., braking reaction times) were collected during unprovoked near-collision events occurring during a car-following task, with (FCWS group) or without FCWS (No Automation group). FCWS presence reduced the number of near-collision events drastically and enhanced visual behaviors during those events. Unexpectedly, brake reaction times were observed to be significantly longer with FCWS, suggesting a cognitive cost associated with the warning process. Still, the FCWS showed a slight safety benefit for novice drivers attributed to the assistance provided for the situation analysis. Outside the warning events, FCWS presence also impacted car-following behaviors. Drivers took an extra safety margin, possibly to prevent incidental triggering of warnings. The data enlighten the nature of the cognitive processes associated with FCWSs. Altogether, the findings support the general efficiency of FCWSs observed through a massive reduction in the number of near-collision events and point toward the need for further investigations.

Adaptive forward collision warning system for hazmat truck drivers: Considering differential driving behavior and risk levels

The risky driving behavior of hazmat truck drivers is a crucial factor in many severe traffic accidents. In-vehicle Advanced Driving Assistance Systems (ADAS), integrating vehicle active safety and driver assistance technology, has been installed into hazmat trucks aiming to reduce driving risks during emergencies. This paper presents an enhanced dynamic Forward Collision Warning (FCW) model tailored for hazmat truck drivers with different driving characteristics and risk levels. Our objective is to determine the optimal moment to alert drivers during risky situations. The novelty of our approach lies in analyzing the driver's response mechanism to the warning by considering their characteristics and real-time driving risk levels. We employ a multi-objective optimization method that integrates real-time driving risk, driver acceptance, and driving comfort to calculate the optimal warning time. Our findings indicate that the appropriate warning time is similar for all drivers under high-level risks, while significant differentiation exists for different driver categories under mid-level and low-level risks. Additionally, aggressive drivers tend to follow leading vehicles closely and exhibit lower deceleration intentions when faced with dangers compared to normal and cautious drivers. Our research outcomes enable the development of user profiles for hazmat truck drivers based on extensive historical driving records, facilitating the analysis of driver response differences to FCWs. This enhances driving safety and improves driver trust in ADAS systems.

An exploration of the role of driving experience on self-reported and real-world aberrant driving behaviors

A significant proportion of global road crashes are attributed to unsafe driving behaviors. The current study aimed to explore potential differences in driving behaviors across experienced and novice drivers using two separate approaches; a questionnaire study and an instrumented vehicle study (IVS). The analysis of 260 questionnaires and 1,372 traffic interactions within the IVS revelated that driving experience affects driving performance for different driving tasks. Factor analysis of the questionnaire data revealed the impact of driving errors, lapses, violations, and aggressive violations on the behavior of novice and experienced drivers. Behavioral models of novice and experienced drivers encountering other road users were determined using binary logistic regression. The results showed that novice drivers were more likely to engage in driving violations while experienced drivers were more likely to engage in aggressive violations. Unauthorized speeding, zigzag movements, using a mobile phone while driving, and unauthorized overtaking on roads were the most frequent driving violations by novice drivers. The most frequent aggressive violations by experienced drivers were tempting other drivers to create a race and chasing other drivers. These findings may be used as a framework to facilitate safer driving behaviors by reducing errors, lapses, violations and aggressive violations, and facilitating safety-promoting attitudes.

A Focus Group Study to Explore Risky Ridership among Young Motorcyclists in Manipal, India

Road crash injuries have emerged as a significant public health issue in many low and middle-income countries in recent years. In India, motorized two-wheelers comprise 70% of the vehicle population and are considered the most vulnerable road users. Road crash injury is common among the young-aged population leading to premature deaths. It is essential to understand risky riding behaviors to develop accurate, evidence-based risk reduction programmes that fit the target population’s characteristics and the intervention setting. The current study aims to improve the understanding of the typical characteristics of motorcycle crashes among young riders in India, primarily focusing on the prevalence and role of risky riding behaviors. Five focus group discussions with eight to ten participants in each group (N = 35) were conducted in Manipal, in the Karnataka state of Southwestern India. A thematic analysis was completed using MAXQDA software to identify, analyze, and report on themes within the data. Speeding, riding under the influence of alcohol, and the poor maintenance of motorcycles were indicated as leading causes of crashes. Furthermore, using mobile phones while riding, violations of the traffic rules, and helmet non-use were identified as other risky behaviors among young riders. Future research can be taken up in other settings for the target population. Generational awareness with the involvement of young riders, government authorities, university officials, and the Regional Transport Office can be initiated. Engaging young riders, government authorities, university officials, and the Regional Transport Office through behavioral interventions such as persuasive communication techniques, an active experimental approach (such as the use of a simulator), and regulating the licensing procedure can reduce the number of road crashes.

An Exploration of Characteristics and Time Series Forecast of Fatal Road Crashes in Manipal, India

Road crashes are the sixth leading cause of death in India. There has been a fourfold increase in the number of road traffic crashes in India in the last four decades and an increase of 9.8 times in the fatalities associated with that exponential increase. Manipal is a coastal place with a population of approximately 50,000 inhabitants lying in between the western Mountain range and the Arabian sea. The study’s objective is to explore the characteristics of fatal road crashes in Manipal from 2008–2018 using the data pertaining to fatal crashes retrieved from the office of the superintendent of police. Furthermore, it aims to forecast crashes by time series analysis prediction. The results show that most of the fatal crashes are due to exceeding the lawful speed limit, followed by driving under the influence of alcohol and going ahead and overtaking. The time series analysis forecasted the number of fatal crashes until the year 2025 and predicted that there will be an increase in the number of fatal road crashes by 4.5%. The results also provide essential leads for initiating specific intervention programmes targeting the causes of fatal road crashes.

The Static and Dynamic Analyses of Drivers’ Gaze Movement Using VR Driving Simulator

Drivers collect information of road and traffic conditions through a visual search while driving to avoid any potential hazards they perceive. Novice drivers with lack of driving experience may be involved in a car accident as they misjudge the information obtained by insufficient visual search with a narrower field of vision than experienced drivers do. In this regard, the current study compared and identified the gap between novice and experienced drivers in regard to the information they obtained in a visual search of gaze movement and visual attention. A combination of a static analysis, based on the dwell time, fixation duration, the number of fixations and stationary gaze entropy in visual search, and a dynamic analysis using gaze transition entropy was applied. The static analysis on gaze indicated that the group of novice drivers showed a longer dwell time on the traffic lights, pedestrians, and passing vehicles, and a longer fixation duration on the navigation system and the dashboard than the experienced ones. Also, the novice had their eyes fixed on the area of interests straight ahead more frequently while driving at an intersection. In addition, the novice group demonstrated less information at 2.60 bits out of the maximum stationary gaze entropy of 3.32 bits that a driver can exhibit, which indicated that their gaze fixations were concentrated. Meanwhile, the experienced group displayed approx. 3.09 bits, showing that their gaze was not narrowed on a certain area of interests, but was relatively evenly distributed. The dynamic analysis results showed that the novice group conducted the most gaze transitions between traffic lights, pedestrians and passing vehicles, whereas experienced drivers displayed the most transitions between the right- and left-side mirrors, passing vehicles, pedestrians, and traffic lights to find more out about the surrounding traffic conditions. In addition, the experienced group (3.04 bits) showed a higher gaze transition entropy than the novice group (2.21 bits). This indicated that a larger entropy was required to understand the visual search data because visual search strategies changed depending on the situations.

Risky motorcycle riding behaviour among young riders in Manipal, India

BACKGROUND

Motorcycles are one of the most commonly used transportation modes in low and middle-income countries. In India, motorized two-wheelers comprise 70% of the total vehicle population, and motorcycle users are considered the most vulnerable road users. It is essential to understand the risky riding behaviour and associated factors among the motorcyclists to develop evidence-based traffic safety programs targeting motorcycle riders. The purpose of the current study was two-fold. First, it aimed to determine the appropriate structure of a modified version of the MRBQ among young riders in Manipal, India. Second, it assessed to what extent MRBQ factors were associated with self-reported crash involvement and violations.

METHODS

The motorcycle rider behaviour questionnaire (MRBQ) is a 43-item scale that assesses five aspects of risky motorcycle rider behaviour, i.e., violations, control errors, traffic errors, stunts, and protective equipment. The MRBQ, along with measures of socio-demographic variables and the number of motorcycle crashes, was filled out by 300 young motorcycle riders who were in the age group of 18-25 years and had been riding for at least the past three years (93% males, 92.3% students).

RESULTS

Five factors emerged out of the MRBQ after an exploratory factor analysis: traffic errors, control errors, stunts, protective equipment, and violations. Cronbach's alpha for these factors ranged from .66 to .82. Reports of performing stunts and committing violations were positively associated with self-reported near-crash experiences over the past three months. Riders reporting stunts, violations and using a motorcycle of 125-200 cc reported having received more fines in the last three months. These findings were confirmed in both univariate and multivariate binary logistic regression models.

CONCLUSION

The study assessed the factor structure of a modified version MRBQ and the extracted factors associations with self-reported crash involvement. The factor structure revealed in the current study is consistent with MRBQ factor structures found in other countries. However, the support for a relationship between MRBQ factors and self-reported crashes was less significant. The findings suggest that if replicated by future studies, local policymakers are advised to focus on the five MRBQ factors while planning future interventions to achieve a reduction in the number of road crashes among motorcyclists.

User Monitoring in Autonomous Driving System Using Gamified Task: A Case for VR/AR In-Car Gaming

Background: As Automated Driving Systems (ADS) technology gets assimilated into the market, the driver’s obligation will be changed to a supervisory role. A key point to consider is the driver’s engagement in the secondary task to maintain the driver/user in the control loop. This paper aims to monitor driver engagement with a game and identify any impacts the task has on hazard recognition. Methods: We designed a driving simulation using Unity3D and incorporated three tasks: No-task, AR-Video, and AR-Game tasks. The driver engaged in an AR object interception game while monitoring the road for threatening road scenarios. Results: There was a significant difference in the tasks (F(2,33) = 4.34, p = 0.0213), identifying the game-task as significant with respect to reaction time and ideal for the present investigation. Game scoring followed three profiles/phases: learning, saturation, and decline profile. From the profiles, it is possible to quantify/infer drivers’ engagement with the game task. Conclusion: The paper proposes alternative monitoring that has utility, i.e., entertaining the user. Further experiments with AR-Games focusing on the real-world car environment will be performed to confirm the performance following the recommendations derived from the current test.

The Role of Eye Tracking Technology in Assessing Older Driver Safety

A growing body of literature is focused on the use of eye tracking (ET) technology to understand the association between objective visual parameters and higher order brain processes such as cognition. One of the settings where this principle has found practical utility is in the area of driving safety.

METHODS

We reviewed the literature to identify the changes in ET parameters with older adults and neurodegenerative disease.

RESULTS

This narrative review provides a brief overview of oculomotor system anatomy and physiology, defines common eye movements and tracking variables that are typically studied, explains the most common methods of eye tracking measurements during driving in simulation and in naturalistic settings, and examines the association of impairment in ET parameters with advanced age and neurodegenerative disease.

CONCLUSION

ET technology is becoming less expensive, more portable, easier to use, and readily applicable in a variety of clinical settings. Older adults and especially those with neurodegenerative disease may have impairments in visual search parameters, placing them at risk for motor vehicle crashes. Advanced driver assessment systems are becoming more ubiquitous in newer cars and may significantly reduce crashes related to impaired visual search, distraction, and/or fatigue.