Designing Human-Machine Interface for Autonomous Vehicles

Debernard, Serge; Chauvin, Christine; Pokam, Raïssa; Langlois, Sabine

doi:10.1016/j.ifacol.2016.10.629

Cited by 52 publications

(21 citation statements)

References 13 publications

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“…It is recognised that while exploring the AV at its high level of automation, drivers feel like passengers and a decrease in situational awareness leads to a potential increase in accidents. Driver's situational awareness depends on the situation of the handover: the moment in the transition timeline and emergency level [86]. The relation between responsibility for accidents and the AV level of automation was also analysed, and the responsibility of the driver was dominant, except for the cases of the highest AV level of automation in low‐risk situations.…”

Section: Challenges and Opportunities For Developing And Implementimentioning

confidence: 99%

Autonomous road vehicles: recent issues and expectations

Skrickij

Šabanovič

Žuraulis

2020

IET Intelligent Transport Systems

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Section: Challenges and Opportunities For Developing And Implementimentioning

confidence: 99%

Autonomous road vehicles: recent issues and expectations

Skrickij

Šabanovič

Žuraulis

2020

IET Intelligent Transport Systems

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“…The design of autonomous vehicles must keep the operators in the loop by providing augmented visualization cues to maintain SA. There is a fundamental requirement on the design principle to keep the "operator" informed about the system's intentions and current operating modes (Debernard, Chauvin, Pokam, Langlois, 2016). The Proximity Compatibility Principle and salient design have been applied not only in aviation (Ding & Proctor, 2017;Li et al, 2019), but also unmanned vehicles (Calhoun, Ruff, Behymer, & Frost, 2018), automation technology (Yamani & McCarley, 2018), electronic medical records (Zahabi, Kaber, & Swangnetr, 2015), digital alarm systems in nuclear power plants (Liu, Hwang, Hsieh, Liang, & Chuang, 2016).…”

Section: Generalized Application Of Augmented Visualization Designmentioning

confidence: 99%

Augmented visualization cues on primary flight display facilitating pilot's monitoring performance

Horn²,

Sun

et al. 2020

International Journal of Human-Computer Studies

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There have been many aviation accidents and incidents related to mode confusion on the flight deck. The aim of this research is to evaluate human-computer interactions on a newly designed augmented visualization Primary Flight Display (PFD) compared with the traditional design of PFD. Based on statistical analysis of 20 participants interaction with the system, there are significant differences on pilots' pupil dilation, fixation duration, fixation counts and mental demand between the traditional PFD design and augmented PFD. The results demonstrated that augmented visualisation PFD, which uses a green border around the "raw data" of airspeed, altitude or heading indications to highlight activated mode changes, can significantly enhance pilots' situation awareness and decrease perceived workload. Pilots can identify the status of flight modes more easily, rapidly and accurately compared to the traditional PFD, thus shortening the response time on cognitive information processing. This could also be the reason why fixation durations on augmented PFDs were significantly shorter than traditional PFDs. The augmented visualization in the flight deck improves pilots' situation awareness as indicated by increased fixation counts related to attention distribution. Simply highlighting the parameters on the PFD with a green border in association with relevant flight mode changes will greatly reduce pilots' perceived workload and increase situation awareness. Flight deck design must focus on methods to provide pilots with enhanced situation awareness, thus decreasing cognitive processing requirements by providing intuitive understanding in time limited situations.

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“…The ultimate goal of the research is to eliminate the human errors and uncertainty from automation, and hence, from the viewpoints of drivers, they have mainly focused on user interfaces, acceptance and trust, inattention and distraction, and adaptation to vehicle automation. For instance, many studies of human factors have developed the human-machine interface [12][13][14]31,32]. They include the determination of feedback methods when automated vehicles should notify the warnings and useful messages to the drivers and passengers, such as auditory, tactile, or visual presentation, and timing to transfer information.…”

Section: Environments For Intelligent Transportation Systemsmentioning

confidence: 99%

Component-Based Interactive Framework for Intelligent Transportation Cyber-Physical Systems

Jeong

Baek

Son

2020

Sensors

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While emerging technology for self-driving automation in vehicles progresses rapidly, the transition to an era of roads full of fully connected and automated vehicles (CAVs) may take longer than expected. Until then, it is inevitable that CAVs should coexist and interact with drivers of non-autonomous vehicles (NAVs) in urban roads. During this period of transition, it is critical to provide road safety with the mixed vehicular traffic and uncertainty caused by human drivers. To investigate the issues caused by the coexistence and interaction with humans, we propose to build a component-based and interactive intelligent transportation cyber-physical systems (ITCPS) framework. Our design of the interactive ITCPS framework aims to provide a standardized structure for users by defining core components. The framework is specified by behavior models and interfaces for the desired ITCPS components and is implemented as a form of human and hardware-in-the-loop system. We developed an intersection crossing assistance service and an automatic emergency braking service as an example of practical applications using the framework. To evaluate the framework, we tested its performance to show how effectively it operates while supporting real-time processing. The results indicate that it satisfies the timing requirements of vehicle-to-vehicle (V2V) communication and the limited processing time required for performing the functions of behavior models, even though the traffic volume reaches the road capacity. A case study using statistical analysis is conducted to assess the practical value of the developed experimental environment. The results of the case study validate the reliability among the specified variables for the experiments involving human drivers. It has shown that V2V communication support has positive effects on road safety, including intersection safety, braking events, and perception-reaction time (PRT) of the drivers. Furthermore, V2V communication support and PRT are identified as the important indicators affecting road safety at an un-signalized intersection. The proposed interactive framework is expected to contribute in constructing a comprehensive environment for the urban ITCPS and providing experimental support for the analysis of human behavior in the coexistence environment.

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Designing Human-Machine Interface for Autonomous Vehicles

Cited by 52 publications

References 13 publications

Autonomous road vehicles: recent issues and expectations

Autonomous road vehicles: recent issues and expectations

Augmented visualization cues on primary flight display facilitating pilot's monitoring performance

Component-Based Interactive Framework for Intelligent Transportation Cyber-Physical Systems

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