Investigating the impact of a novel active gap metering signalization strategy on driver behavior at highway merging sections

A safe headway to the lead vehicle is important to reduce conflicts with merging vehicles from highway on-ramps. Previous research has outlined the advantage of gap metering strategies to yield sufficient space to merging vehicles and improve highway capacity during peak hours. However, prevailing gap metering systems fail to indicate the minimum required gap and leave it to the drivers’ judgment to adjust their headway. This paper proposes a new Active Gap Metering (AGM) signalization that helps outer lane drivers to adjust their headway to the lead vehicle when approaching highway ramps with incoming vehicles. This AGM signalization represents a combination of pavement markings and an innovative Variable Message Sign (VMS). The AGM system was tested alone and in combination with additional variable speed limits (VSL) in distinct environments of the Doha Expressway in the State of Qatar using a driving simulator. The driving behavior of 64 drivers was analyzed using repeated-measures ANOVA. The results showed that the AGM effectively influenced the drivers’ behavior on the right stream lane. Drivers did gradually increase the distance to the lead vehicle, which resulted in optimal headways to merging on-ramp vehicles. Most importantly, the minimum time-to-collision (TTC_min) to the merging vehicle was increased by an additional 1–1.5 s as compared to no treatment. The proposed AGM signalization can, therefore, be considered by policymakers to influence drivers’ headways at critical merging sections.     

Different level automation technology acceptance: Older adult driver opinion

The increase in the number of older adult drivers in developed countries has raised safety concerns due to the decline in their sensory, motor, perceptual, and cognitive abilities which can limit their driving capabilities. Their driving safety could be enhanced by the use of modern Automated Driver Assistance Systems (ADASs) and might totally resolved by full driving automation. However, the acceptance of these technologies by older adult drivers is not yet well understood. Thus, this study investigated older adult drivers’ intention to use six ADASs and full driving automation through two questionnaires with 115 and 132 participants respectively in Rhode Island, USA. A four-dimensional model referred to as the USEA model was used for exploring older adult drivers’ technology acceptance. The USEA model included perceived usefulness, perceived safety, perceived ease of use, and perceived anxiety. Path Analysis was applied to evaluate the proposed model. The results of this study identified the important factors in older adult drivers’ intention to use ADASs and full driving automation, which could assist stakeholders in improving technologies for use by older drivers.     

Effectiveness of the compensatory strategy adopted by older drivers: Difference between professional and non-professional drivers

It has been a controversial issue for the effect of ageing population on driving safety. Apparently, drivers’ physiological and cognitive performances deteriorate with age. However, older drivers may compensate for the elevated risk by adjusting their behaviors, known as compensatory strategy. Despite the extensive research on this topic, the compensatory strategy of older professional drivers is not well understood since many studies focused on the differences in compensatory behavior between older and young drivers. Professional drivers tend to be more skillful and able to cope with the unfavorable driving environments, thus presenting a higher capability to mitigate the risk. This study attempts to examine the compensatory behavior and its safety effect amongst older professional drivers, as compared to those of older non-professional drivers, using the driving simulator approach. In the driving simulator experiment, participants were asked to follow a leading vehicle for one hour, and two sudden brake events were presented. 41 (mid-aged and older) drivers completed the driving tests. Each participant was required to complete a car-following test, either under high or low traffic flow conditions. Performance indicators include driving capability (i.e. lateral control, longitudinal control, and brake reaction time) and compensatory behavior (i.e. average speed, and time headway). Additionally, two modified traffic conflict measures: time exposed time-to-collision (TET) and time integrated time-to-collision (TIT) are applied to indicate the traffic conflict risk. The random parameter Tobit models were estimated to measure the association between conflict risk and driver attributes, and random intercept models were used to assess other driving performance indicators. Results show that despite the impaired lateral control performance and longer brake reaction time of older drivers, the likelihood of severe traffic conflict of older drivers is lower than that of mid-aged drivers. Furthermore, though both older professional and older non-professional drivers adopted longer time headway, the reduction in the risk of severe traffic conflict is more profound among the older professional drivers. Such findings suggest that older professional drivers are more capable of mitigating the possible collision risk by adopting the compensatory strategy, as compared to older non-professional drivers. This justifies the existence of compound effect by the compensatory strategy of older driver and better driving skills of professional driver. This research provides useful insights into driver training and management strategies for employers, as older drivers would become a major cohort in the transportation industry.     

Effects of forward collision warning technology in different pre-crash scenarios

The forward collision warning (FCW) system is expected to reduce rear-end crashes; however, its effects on driving behavior and safety have not been thoroughly investigated, specifically the effect variations between different pre-crash scenarios. To identify these variations, this study conducted a driving simulator experiment and compared the FCW’s effects between three pre-crash scenarios: the freeway scenario, the arterial scenario and the intersection dilemma zone scenario. Thirty-nine participants were involved in the experiment. The results showed that the adaptation of driver behavior in impending rear-end collision events resulted from both the FCW and the scenario. The intersection dilemma zone scenario has indications of slowing down, which encouraged drivers to take a more aggressive response strategy under the FCW; the arterial scenario might be regarded as an “easy-to-handle” situation in which a significant portion of drivers adopted moderate level of response strategy under the FCW; both the intersection dilemma zone scenario and freeway scenario have burdened driving tasks, and this might deteriorate a driver’s ability to adapt to the FCW. In addition, different types of drivers experienced varied benefits from the FCW in each scenario. The FCW would be particularly recommended for non-experienced drivers in the freeway scenario and for female drivers in the arterial scenario; moreover, in the scenario of the intersection dilemma zone, the FCW would be particularly recommended for drivers who have a crash/citation before. The results also support specific FCW designs which are able to highlight the collision risk. This study demonstrated that it would be better to indicate the effects of the FCW under the restriction of specific scenario features and develop the FCW based on that.     

Distracted driving caused by voice message apps: A series of experimental studies

Hand-free voice message apps are frequently used by young people while driving. Previous studies have identified voice message apps as a common source of driving distraction. To quantitatively evaluate the factors contributing to driving distractions, three simulated driving experiments were designed using a dual-task experimental paradigm. In Experiment 1, participants completed several common tasks related to voice messages in WeChat with or without manual operations (perceptual-motor distraction). Experiments 2 and 3 further took into consideration the cognitive distraction level, measured by task difficulty and task frequency. The results showed that, in comparison with undistracted driving, the perceptual-motor distraction related to voice message app use significantly (ps < 0.05) weakened young drivers’ driving performance with respect to the standard deviation of lateral position (SDLP) between two cars (0.24 m), response time (0.21 s) and error rate (0.12) to turning lights, and collision percentage (0.54%), similar to the effects induced by non-voice-based apps. There were also significant differences (ps < 0.05) between driving with secondary tasks with and without continuous manual operations in the SDLP between two cars (0.19 m) and in the response time (0.18 s) and error rate (0.10) to turning lights, which indicates that the distracting effect produced by voice-message apps comes from the related manual operations. The effects of cognitive distraction on driving performance mainly depended on task difficulty level. High-difficulty secondary tasks via a voice message app significantly (ps < 0.05) weakened the driving performance in response time (by 0.13 s and 0.13 s compared to low-difficulty and baseline conditions, respectively) and error rate (by 0.07 and 0.07 compared to low-difficulty and baseline conditions, respectively) to turning lights and collision percentage (by 0.90% and 0.80% compared to low-difficulty and baseline conditions, respectively). The findings provide a theoretical reference for analysing the distracting components of voice messages and suggest that drivers should limit the use of these kinds of apps during driving.     

The role of drivers’ social interactions in their driving behavior: Empirical evidence and implications for car-following and traffic flow

Models for describing the microscopic driving behavior rarely consider the “social effects” on drivers’ driving decisions. However, social effect can be generated due to interactions with surrounding vehicles and affect drivers’ driving behavior, e.g., the interactions result in imitating the behavior of peer drivers. Therefore, social environment and peer influence can impact the drivers’ instantaneous behavior and shift the individuals’ driving state. This study aims to explore empirical evidence for existence of a social effect, i.e., when a fast-moving vehicle passes a subject vehicle, does the driver mimic the behavior of passing vehicle? High-resolution Basic Safety Message data set (N = 151,380,578) from the Safety Pilot Model Deployment program in Ann Arbor, Michigan, is used to explore the issue. The data relates to positions, speeds, and accelerations of 63 host vehicles traveling in connected vehicles with detailed information on surrounding environment at a frequency of 10 Hz. Rigorous random parameter logit models are estimated to capture the heterogeneity among the observations and to explore if the correlates of social effect can vary both positively and negatively. Results show that subject drivers do mimic the behavior of passing vehicles –in 16 percent of passing events (N = 18,099 total passings occurred in freeways), subject vehicle drivers are observed to follow the passing vehicles accelerating. We found that only 1.2 percent of drivers normally sped up (10 km/hr in 10 s) during their trips, when they were not passed by other vehicles. However, if passed by a high speed vehicle the percentage of drivers who sped up is 16.0 percent. The speed change of at least 10 km/hr within 10 s duration is considered as accelerating threshold. Furthermore, the acceleration of subject vehicle is more likely if the speed of subject driver is higher and more surrounding vehicles are present. Interestingly, if the difference with passing vehicle speed is high, the likelihood of subject driver’s acceleration is lower, consistent with expectation that if such differences are too high, the subject driver may be minimally affected. The study provides new evidence that drivers’ social interactions can change traffic flow and implications of the study results are discussed.     

Investigating sex,masculinity and femininity in relation to impulsive driving and driving anger expression

Human factors constitute a class of prominent road safety related factors. In the present study, human factors of driving were studied by investigating sex differences and gender roles in relation to impulsive driving and driving anger expression. A total of 425 drivers between the ages of 18 and 56 (M = 25.46, SD = 7.58) participated to the study and completed a series of questionnaires including a demographic information form, the Bem Sex Roles Inventory, the Impulsive Driver Behaviour Scale and the Driving Anger Expression Inventory. According to the ANCOVA results, male drivers showed higher functional impulsivity, lack of premeditation and use of the vehicle to express anger than female drivers. Additionally, hierarchical regression analyses showed that masculinity was positively associated with functional impulsivity, urgency and the dimensions of aggressive anger expression. However, femininity was positively associated with functional impulsivity and adaptive/constructive anger expression, but negatively associated with the dimensions of dysfunctional impulsivity and aggressive anger expression. Overall, the results showed the significant solo effects of masculinity and femininity on impulsive driver behaviours and driving anger expression, over and above the effects of sex, and the interaction between sex and gender roles. In the present study, previously reported findings indicating the relationships between sex and gender roles and driving anger expression were supported and extended by providing the literature with the contribution of answering the question how sex and gender roles are related to impulsive driver behaviours. The findings of the two related concepts of impulsive driving and driving anger expression were discussed in light of the current literature. Contributions, implications and future research directions concerning road safety practices were presented.     

The mediation effect of emotion dysregulation in the relationship between anger and aggression on the road in a sample of Spanish drivers

Aggressive behaviour on the road is one of the most studied topics in human factors, given it has been related to both risky behaviour and traffic crashes. While previous research has proposed trait driving anger as one of the better predictors, mediation variables which could explain this relationship have not deserved attention. The current research aimed to explore the mediation effect of emotion regulation in this relationship. The sample consisted of 472 Spanish drivers, who completed a set of self-reports regarding trait driving anger, frequency of aggressive behaviours at the wheel, and difficulties in emotion regulation. The results showed significant relationship among the variables in almost all the cases. Furthermore, a SEM analysis showed that difficulties in emotion regulation significantly mediated the relationship between trait driving anger and each way of the aggressive behaviours (verbal, physical, using own vehicle, and displaced). These results have important implications in the design of strategies focused on the improvement of emotion regulation to reduce aggressive behaviours in drivers. Finally, the limitations of the study are commented.     

Evaluating driver comprehension of the roadway environment to retain accountability of safety during driving automation

Driver comprehension is a substantial component of situation awareness that involves the ability of an individual to understand the significance of an object, traffic sign, or hazard while driving. An increase in crashes related to autonomous driving systems has raised a concern regarding the safety of other roadway users due to the diminishing accountability resulting from a general lack of understanding of the limitations or disregard of the safety protocols by users. To keep drivers vigilant when engaged in partial automated systems, a methodology to monitor real-time driver comprehension was proposed. A driving simulator study consisting of 90 participants, equally split between males and females, was executed to establish driver comprehension in six different variations of driving difficulty. Joint probability density functions were created by considering percent time spent gazing, answers to probe questions, and driving performance. Based on these density functions, five levels of comprehension were devised and assigned thresholds. Overall, as task difficulty increased, a non-linear deterioration in driving speed along with an increase in total gaze duration was observed before comprehension was attained. A two-step validation protocol was also proposed to ensure similar levels of comprehension to non-automated driving from the human driver, when engaged in early forms of automation. The proposed real-time driver comprehension monitoring constitutes a first step toward developing a methodology to reinstate the accountability of safety of other roadway users when engaged in driver-in-the-loop automation systems.     

Safe driving and road-crossing tasks: A particular case of successful transfer of learning

The current study examines whether crucial safe driving skills are associated with safe road-crossing skills as pedestrians. The main research question was whether skills that are acquired from the point of view of a driver are associated with the skills of pedestrians in different platforms or settings. Furthermore, the study examines whether task performance on one platform (driving) primes an operator for task performance on another (road-crossing as a pedestrian) or vice versa. Sixty people took part in this study and completed a demographic questionnaire, a Driving Behavior Questionnaire, a Pedestrian Behavior Scale and two computerized tests – a Hazard Perception Test for Drivers and a Hazard Perception Test for Pedestrians.We found that the better the participants detect hazards on the road as drivers, the better they detect hazards as pedestrians as well, and that most of the participants’ self-reported values regarding their driving and their road-crossing as pedestrians are correlated. The study revealed an association between years of seniority in driving and the number of driving hours per week, and some behavioral variables as pedestrians – meaning that exposure to the road as a driver may be related to safer behavior as a pedestrian.