Effects of an in-vehicle eco-safe driving system on drivers' glance behaviour

Get Ready for Take-Overs: Using Head-Up Display for Drivers to Engage in Non-Driving-Related Tasks in Automated Vehicles

OBJECTIVE

The study aims to investigate the potential of using HUD (head-up display) as an approach for drivers to engage in non-driving-related tasks (NDRTs) during automated driving, and examine the impacts on driver state and take-over performance in comparison to the traditional mobile phone.

BACKGROUND

Advances in automated vehicle technology have the potential to relieve drivers from driving tasks so that they can engage in NDRTs freely. However, drivers will still need to take-over control under certain circumstances.

METHOD

A driving simulation experiment was conducted using an Advanced Driving Simulator and real-world driving videos. Forty-six participants completed three drives in three display conditions, respectively (HUD, mobile phone and baseline without NDRT). The HUD was integrated with the vehicle in displaying NDRTs while the mobile phone was not. Drivers' visual (e.g. gaze, blink) and physiological (e.g. ECG, EDA) data were collected to measure driver state. Two take-over reaction times (hand and foot) were used to measure take-over performance.

RESULTS

The HUD significantly shortened the take-over reaction times compared to the mobile phone condition. Compared to the baseline condition, drivers in the HUD condition also experienced lower cognitive workload and physiological arousal. Drivers' take-over reaction times were significantly correlated with their visual and electrodermal activities during automated driving prior to the take-over request.

CONCLUSION

HUDs can improve driver performance and lower workload when used as an NDRT interface.

APPLICATION

The study sheds light on a promising approach for drivers to engage in NDRTs in future AVs.

Adopting an HMI for overtaking assistance - Impact of distance display, advice, and guidance information on driver gaze and performance

Conveying supporting information by an in-vehicle human-machine interface (HMI) overtaking assistance system represents a promising approach to facilitate safe overtaking maneuvers. Although various researchers have attempted to examine the safety of systems, numerous HMI concepts are not validated and the impacts of systems on driver behavior following exposure to a connected environment remain unclear. Thus, the objective of this study is to assess the effectiveness of various HMI concepts and their effects on drivers' gaze behavior and driving performance in the connected environment. Three types of supporting information, namely distance, advice and guidance, were designed based on implicit and explicit concepts and displayed on the HMI. The guidance information provides more detailed maneuver instructions. A driving simulator experiment was conducted to imitate a connected environment and included an overtaking scenario on a two-lane highway under three distance gaps (short, middle and long) of oncoming vehicles and four HMI conditions including baseline (3*4). 39 participants (mean = 28.3 years, SD = 8.2 years) drove the simulator. Visual attention, driving maneuver, and subjective evaluation data were collected. The results indicated that the supporting information was valid in facilitating overtaking behavior compared without HMI, particularly under the middle distance gap scenario. Advice information was the most effective, required the least attention, exhibited the best performance, and was accepted by drivers. Detailed maneuver instructions were perceived as helpful, although no effect on acceptance was found. The findings of the study provide valuable insights into the development of user-friendly overtaking assistance systems.

Factors affecting drivers' off-road glance behavior while interacting with in-vehicle voice interfaces

In-vehicle voice-based interfaces have been massively embedded in modern vehicles as a countermeasure to visual-manual distractions. However, limited data are available regarding the actual visual demands imposed on the driver when interacting with such an interface. How those factors that are associated with the drivers themselves affect their visual behavior when interacting with an in-vehicle voice-based interface remains understudied. This study focused on investigating factors affecting drivers' off-road visual behavior while interacting with a voice-based interface. A secondary data analysis leveraging structural equation modeling was performed based on data collected from a large-scale field experiment wherein participants drove a vehicle on the highway and performed a series of tasks using an in-vehicle voice interface. The results indicate that while voice-based interfaces are designed to help reduce drivers' visual demands, drivers can still direct their eyes off the road for a prolonged period of time during the interaction and exhibit potentially risky visual behavior. In addition, individual-level factors can exert influence on drivers' off-road visual behavior in such a way that older drivers and drivers with higher trust in technologies are associated with more long eyes-off-road glances when interacting with a voice-based interface. To promote the general public's adoption of in-vehicle voice interfaces and support safe interactions, we recommend relevant research and system design consider drivers' trust in, perceptions, and previous usage of similar technologies, as well as their individual characteristics such as age.

Developing a two-stage auditory warning system for safe driving and eco-driving at signalized intersections: A driving simulation study

In-vehicle intersection warning systems represent a promising approach for informing drivers of potential danger to reduce crashes and improve intersection safety. However, there is limited research on drivers' eco-driving performances, such as fuel consumption and emission, when drivers adapt their behaviors to the systems. In this study, an innovative two-stage in-vehicle intersection warning system was proposed to reduce red-light running (RLR) violations. Forty-five drivers participated in a simulated driving experiment and their driving performances at the intersections were evaluated to examine the effectiveness of the warning system. The measures included stop/go decision, RLR rate, average speed and deceleration, brake transition time, brake level, fuel consumption, and emission of CO and NOx. The results indicated that the warning system had a positive effect on drivers' safe driving and eco-driving performances, such as reducing the RLR rate, advancing and smoothing the deceleration and reducing fuel consumption and emission. Moreover, the impact of warning on drivers' performances varied with the time to the onset of yellow light. The research has practical implications for the automobile industry to use vehicle-to-infrastructure technology in the design of in-vehicle warning systems to improve driver behaviors at intersections.

Exploring drivers' mental workload and visual demand while using an in-vehicle HMI for eco-safe driving

Eco-safe driving is a promising approach to improve road safety while reducing transport emissions. The application of an eco-safe driving system is feasible with the support of vehicle-to-vehicle/infrastructure technologies. To guarantee system usability and safety appropriateness, a key precondition is to ensure that driver mental workload and visual demands required for using the system are reasonable. This study explored how drivers' mental workload and visual demands were affected when driving with an eco-safe driving HMI (human-machine-interface). Four in-vehicle eco-safe HMI information conditions were evaluated, including baseline, advice only, feedback only, and advice & feedback. Two traffic scenarios (stop-sign intersection with traffic vs. stop-sign intersection without traffic) were simulated using an advanced driving simulator. Behavioural variables (e.g. brake force, acceleration), visual variables (e.g. blink metrics, pupil size) and subjective workload scores were collected from 36 licensed Australian drivers. The experiment results showed that the HMI prompted drivers to apply a smooth and stable brake force when they approached the intersection and a smooth acceleration when they left the intersection. Drivers' mental workload indicated by visual measurements were consistent with their subjective reported workload levels. Drivers had a higher mental workload when they received and processed additional eco-safe information in the advice & feedback condition. An increase in mental workload induced by the in-vehicle cognitive task initiated more blink activities while the increase in visual demand caused by a complex road situation led to blink inhibition. The study shows the HMI could significantly promote eco-safe driving behaivours without causing excessive mental and visual workload of drivers.

Eye tracking use in researching driver distraction: A scientometric and qualitative literature review approach

Many factors affect road safety, but research constantly shows that drivers are the major cause of critical situations that could potentially lead to a traffic accident in road traffic. Visual information is a crucial part of input information into the driving process; therefore, distractions of overt visual attention can potentially have a large impact on driving safety. Modern eye tracking technology enables researchers to gain precise insight into the direction and movement of a driver’s gaze during various distractions. As this is an evolving and currently very relevant field of road safety research, the present paper sets out to analyse the current state of the research field and the most relevant publications that use eye tracking for research of distractions to a driver’s visual attention. With the use of scientometrics and a qualitative review of the 139 identified publications that fit the inclusion criteria, the results revealed a currently expanding research field. The narrow research field is interdisciplinary in its core, as evidenced by the dispersion of publication sources and research variables. The main research gaps identified were performing research in real conditions, including a wider array of distractions, a larger number of participants, and increasing interdisciplinarity of the field with more author cooperation outside of their primary co-authorship networks.

Sustainable Business Models: A Review

During the past two decades of e-commerce growth, the concept of a business model has become increasingly popular. More recently, the research on this realm has grown rapidly, with diverse research activity covering a wide range of application areas. Considering the sustainable development goals, the innovative business models have brought a competitive advantage to improve the sustainability performance of organizations. The concept of the sustainable business model describes the rationale of how an organization creates, delivers, and captures value, in economic, social, cultural, or other contexts, in a sustainable way. The process of sustainable business model construction forms an innovative part of a business strategy. Different industries and businesses have utilized sustainable business models’ concept to satisfy their economic, environmental, and social goals simultaneously. However, the success, popularity, and progress of sustainable business models in different application domains are not clear. To explore this issue, this research provides a comprehensive review of sustainable business models literature in various application areas. Notable sustainable business models are identified and further classified in fourteen unique categories, and in every category, the progress -either failure or success- has been reviewed, and the research gaps are discussed. Taxonomy of the applications includes innovation, management and marketing, entrepreneurship, energy, fashion, healthcare, agri-food, supply chain management, circular economy, developing countries, engineering, construction and real estate, mobility and transportation, and hospitality. The key contribution of this study is that it provides an insight into the state of the art of sustainable business models in various application areas and future research directions. This paper concludes that popularity and the success rate of sustainable business models in all application domains have been increased along with the increasing use of advanced technologies.