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.     

Key factors associated with Australian parents’ willingness to use an automated vehicle to transport their unaccompanied children

This study aimed to identify the key factors associated with Australian parents' willingness to use an automated vehicle to transport their unaccompanied child(ren). Seven hundred and seventy-five participants completed the online survey (M = 40.7 years, SD = 8.9 years, Range = 18.0–65.0 years; Female: 56.4%). Most participants reported that they would 'never' use an automated vehicle to transport their unaccompanied child(ren) (43.5%). The results of a logistic regression model showed that participants' age, gender, level of education, propensity for technology adoption, aberrant driving behaviours, awareness of advanced driver assistance safety (ADAS) technologies, perceived knowledge regarding automated vehicles, as well their requirements for assurance-related vehicle features were significantly associated with their willingness to use an automated vehicle to transport their unaccompanied child(ren), χ2(12) = 137.41, p < 0.001). Overall, the findings suggest that Australian parents are mostly unwilling to use an automated vehicle to transport their unaccompanied child(ren) unless various reassurance features and technologies (i.e., microphones, camera, ability to summon assistance if the vehicle breaks down) are embedded in the vehicle. Therefore, automated vehicle manufacturers are encouraged to consider these requirements when prototyping their designs so that all user groups, including child occupants, can benefit from the impending arrival of automated technologies.     

Factors influencing public awareness of autonomous vehicles: Empirical evidence from Brisbane

Growing concerns, regarding transport disadvantage and increased socioeconomic disparities, demand innovative ways to improve equity and make transportation systems smarter. One of the most anticipated developments within the field of smart mobility is driving automation systems. Autonomous vehicles (AVs) have the potential to improve accessibility, affordability, safety and efficiency of transport systems, but come with risks including the intensification of private vehicle travel. Understanding public awareness is an important step to determine whether motivation and intention to use AVs will impact on its potential. This paper aims to investigate factors influencing public awareness of AVs as a solution to transport disadvantage. The study applies an ordinal logistic regression analysis to analyse survey data collected from the residents of Brisbane (Australia). Our findings reveal that awareness is positively correlated within young and middle-aged adults, low-income residents, disability, public transport users, and those who feel unsafe on public transport, while an increase in the number of household vehicles is negatively correlated. The study provides insights into public awareness towards the potential benefits of AVs, and highlights potential opportunities and challenges associated with these expectations.     

From sport to eco: A case study of driver inputs on electric vehicle efficiency

This study focuses on driver-induced changes to vehicle energy and emissions performance by altering drivetrain configurations. It defines and examines the motivations for the use of drive modes in plug-in hybrid electric vehicles (PHEVs). Drive modes are defined as user-selectable drivetrain configurations that allow drivers to change vehicle performance aspects such as altering its propulsion status from electric to gas, changing the steering responsiveness, suspension stiffness, and regenerative braking strength. Despite the direct impact they have on the vehicle’s energy usage, greenhouse gas emissions, and local air emissions, the impact of drive modes are not traditionally measured as part of the vehicle’s performance and certification tests. The impact of drive mode choice can explain a portion of the discrepancy between PHEVs expected and on road performance as a recent study by the authors found that the use of certain modes can result in a 15–30% increase in total energy usage in a vehicle traveling at freeway speeds.This is the first study to examine the motivations for the use of these drive modes and provides an overview of PHEV drive modes, classifying them into two main mode categories (propulsion adjustment and driver experience) and eight different mode types based on their intended purpose. This is followed by a logistic regression of 11 indicators for mode usage taken from a survey of over 4,500 PHEV owning households, showing that gender and the number of long-distance trips were the most commonly associated with usage across mode types.     

Human factors evaluation of an in-vehicle active traffic and demand management (ATDM) system

This research study focused on the evaluation of an emulated in-vehicle Active Traffic and Demand Management (ATDM) system on Interstate 66 in Northern Virginia. Traditional ATDM systems rely on infrastructure-mounted variable message signs (VMS) to provide information (speed limits, lane availability, etc.) to the traveling public. By providing information about dynamic roadway conditions on an in-vehicle device, the ATDM may improve driving safety and performance by allowing drivers to remain consistently aware of forthcoming traffic conditions and roadway requirements; even when external signage is inaccessible. This study represents an initial investigation of an emulated in-vehicle ATDM to provide developers with design guidance and ensure that unintended consequences, such as distraction, do not undermine the potential benefits.Twenty younger and 20 older participants, accompanied by a member of the research team, experienced the following ATDM features on an in-vehicle device (IVD) mounted to the dashboard: (1) dynamic speed limits, (2) dynamic lane use/shoulder control, (3) High Occupancy Vehicle (HOV) restrictions, and (4) roadway information from variable message signs. The IVD was equipped with auditory and visual alerts notifying the driver when relevant visual information was updated. Research questions addressed distraction and driver behavior associated with use of the system. Qualitative and quantitative participant data was acquired from the instrumented vehicle, various questionnaires, and researcher observation.Several key findings were uncovered: (1) The IVD, as tested, did not warrant classification as a source of distraction according to the NHTSA guidelines; v2) There was a significant difference in eye-glance durations to the IVD when comparing the VMS alerts to both the speed limit and lane management alerts; and (3) The speed limit alert motivated participants to alter their speed (per survey results and participant speed data).     

Using the UTAUT2 model to explain public acceptance of conditionally automated (L3) cars: A questionnaire study among 9,118 car drivers from eight European countries

We investigated public acceptance of conditionally automated (SAE Level 3) passenger cars using a questionnaire study among 9,118 car-drivers in eight European countries, as part of the European L3Pilot project. 71.06% of respondents considered conditionally automated cars easy to use while 28.03% of respondents planned to buy a conditionally automated car once it is available. 41.85% of respondents would like to use the time in the conditionally automated car for secondary activities. Among these 41.85%, respondents plan to talk to fellow travellers (44.76%), surf the internet, watch videos or TV shows (44%), observe the landscape (41.70%), and work (17.06%). The UTAUT2 (Unified Theory of Acceptance and Use of Technology) was applied to investigate the effects of performance and effort expectancy, social influence, facilitating conditions, and hedonic motivation on the behavioural intention to use conditionally automated cars. Structural equation analysis revealed that the UTAUT2 can be applied to conditional automation, with hedonic motivation, social influence, and performance expectancy influencing the behavioural intention to buy and use a conditionally automated car. The present study also found positive effects of facilitating conditions on effort expectancy and hedonic motivation. Social influence was a positive predictor of hedonic motivation, facilitating conditions, and performance expectancy. Age, gender and experience with advanced driver assistance systems had significant, yet small (<0.10), effects on behavioural intention. The implications of these results on the policy and best practices to enable large-scale implementation of conditionally automated cars on public roads are discussed.     

A focus group study on the potential of autonomous vehicles as a viable transportation option: Perspectives from people with disabilities and public transit agencies

Autonomous vehicle (AV) technology is becoming one of the most promising alternatives to improve mobility for people with disabilities. Nevertheless, how people with disabilities perceive AV as transportation services has not been explored. Also, limited information exists about how public transit agencies comprehend and perceive autonomous vehicle transportation (AVT) services. This study discusses mobility issues for people with disabilities and explores the potential of AVT to serve that population, particularly those with visual impairments or physical disabilities. Researchers conducted six focus groups comprising people with disabilities (N = 23) and public transit service experts (N = 10) in Austin, Texas and Houston, Texas. Each session was audio-recorded and analyzed using conventional content analysis. This study identified people with disabilities’ mobility issues related to: (1) current transit services (including fixed-route and paratransit services) and (2) the quality of neighborhood built environments. Both people with disabilities and transit experts expected that AVT could mitigate current mobility issues, especially in improved built environments. However, participants with disabilities also expressed concerns and anxieties regarding AVT. Transit experts agreed that more targeted strategies would be needed to overcome possible barriers to AVT for people with disabilities. This study provides insights on shaping AVT strategies and policies relevant to improving mobility for people with disabilities.     

Psychometric properties of the Driving Behaviour Scale (DBS) among polish drivers

Anxiety can negatively affect an individual’s psychological wellbeing and lead to mild-to-moderate functional impairment in various areas of their lives. Despite this, the relationship between anxiety and driving performance has received very little empirical attention. The Driving Behaviour Scale (Clapp, Olsen, Beck, et al., 2011, Clapp, Olsen, Danoff-Burg, et al., 2011) was developed as a measure of anxious driving behaviours to support research in this area. The current study details adaptation and validation of the Driving Behaviour Scale (DBS; Clapp, Olsen, Beck, et al., 2011, Clapp, Olsen, Danoff-Burg, et al., 2011) in 310 university students in Poland. The overall internal consistency for the DBS was 0.76, while the two subscales demonstrated acceptable internal consistency (safety/cautious = 0.75 and hostile/aggressive behaviours = 0.85). The reliability estimates for performance deficit returned a lower coefficient of 0.65. Factor analysis produced a three-factor solution that supported the original structure of the DBS. The DBS may be utilised as a measure of driving anxiety in samples drawn from the general population.     

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.     

Handing control back to drivers: Exploring the effects of handover procedure during transitions from Highly Automated Driving

The operational capabilities of automated driving features are limited and sometimes require drivers’ intervention through a transition of control. Assistance at an operational level might be extremely beneficial during transitions but the literature lacks evidence on the topic. A simulator study was conducted to investigate the potential impacts that lateral assistance systems might have while the Automated Driving System (ADS) hands back control to the driver. Results showed that drivers benefitted from a strong Lane Keeping Assist during the first phase of the transfer, helping them to keep the lane centre. However, assisting the drivers at an operational level did not enhance their capability of addressing a more complex task, presented as a lane change. In fact, it was more task-specific assistance (Blind-spot assist) that allowed drivers to better cope with the tactical decision that the lane change required. Moreover, longer exposure to lane-keeping assist systems helped them in gaining awareness of the surrounding traffic and improved the way drivers interacted with the Blind-spot assist.