Situation awareness increases when drivers have more time to take over the wheel in a Level 3 automated car: A simulator study

Vlakveld, W P; Nes, Nicole van; Bruin, Jonathan de; Vissers, Luuk; Kroft, Merle van der

doi:10.1016/j.trf.2018.07.025

Cited by 66 publications

(26 citation statements)

References 24 publications

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“…The setup is predominantly an eyes-off-the-road setup that negatively affects situational awareness. Authors in [36] argue that situational awareness increases with an increase in takeover time, meaning that the more the user has eyes on the situation, the better the performance. The closest research towards awareness is on AR displays.…”

Section: Present Studymentioning

confidence: 99%

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

Muguro

Laksono

Sasatake

et al. 2021

MTI

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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.

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Section: Present Studymentioning

confidence: 99%

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

Muguro

Laksono

Sasatake

et al. 2021

MTI

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“…The impact of peripheral visual information in alleviating motion sickness when engaging in nondriving tasks in fully automated driving (Karjanto et al, 2018) Driver response when experiencing a safety critical take-over request (Blommer et al, 2017;Merat et al, 2014b;Shen & Neyens, 2017;Vogelpohl et al, 2018;Zeeb et al, 2015); Necessary time for drivers to achieve situation awareness (Agrawal et al, 2017;Vlakveld et al, 2018); How situation awareness in transfer of control is affected by driver fatigue, stress, (Neubauer et al, 2012); by workload (de Winter et al, 2014); by mental task demands (Heikoop et al, 2018); by alert cue specificity (Forster et al, 2017;Wright et al, 2017); and by driver experience (Wright et al, 2016b); Resuming control from the automation (Bueno et al, 2016;Clark & Jing Feng 2017;Gold et al, 2015;Merat & Lee, 2012;Merat et al, 2014;Merat et al, 2014b;Naujoks et al, 2018;Navarro et al, 2016;Petermeijer et al, 2017;Payre et al, 2017;Radlmayr et al, 2014;Zeeb et al, 2017;Zhang et al, 2018); Post-transition driving performance (Berthelon & Gineyt, 2014;Miller et al, 2015;Mok et al, 2015;Naujoks et al, 2015;Naujoks, Purucker, et al 2017;Radlmayr et al, 2018;Strand et al, 2014;…”

Section: Introductionmentioning

confidence: 99%

Driving with and without automation on the motorway – an observational study

Várhelyi

Kaufmann

Johnsson

et al. 2020

Journal of Intelligent Transportation Systems

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User-related assessment of a level 3 automated driving system, providing functions such as lane-and distance-keeping, stop & go driving, lane change and overtaking, was carried out on a motorway in Germany with the aim to assess user-related issues of automated driving, i.e., behavior when driving with automation on motorways, user experiences, reactions and acceptance. Twenty-one persons drove twice along the test route once with the system switched off and once with the system active. Driving data were logged and driving behavior was observed by two observers in the car and the drivers answered questionnaires. The results revealed that the drivers used the system as it was intended to be used and that the system affected driving positively in several ways, resulting in better speed adaptation, less speed variation, better distance keeping, better lane choice, better indicator usage and fewer dangerous lane changes. No differences with regard to subjective workload were shown. The system was perceived as being both useful and satisfactory. However, it was found that the system did not react to other drivers' intention to make a lane change, especially in situations where they were attempting to merge onto the motorway. Further development is needed to improve the system's ability to recognize other vehicles' intention to enter the vehicle's own lane. Also, the phenomenon of the driver "feeling guilty" because of the system's reckless behavior by not allowing other drivers to merge onto the motorway or hindering other cars behind due to lengthy overtaking should be investigated further.

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“…Several researchers identified awareness in driving as key to safe driving [34][35][36]. At the onset of level 3 automation in ADS, concerted efforts will be needed to maintain the driver's visual search path to the driving environment.…”

Section: Present Studymentioning

confidence: 99%

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

Muguro¹,

Laksono²,

Sasatake³

et al. 2021

Preprint

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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. The paper’s objective is to monitor driver engagement with a game and identify any impacts the task has on hazard recognition. 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. From the results, there was less than 1 second difference between the means of gaming task (mean = 2.55s, std = 0.1002s) to no-task (mean = 2.55s, std = 0.1002s). 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. The paper proposes alternative monitoring that has utility, i.e., entertaining the user. Further experiments AR-Game focusing on real-world car environment will be performed to confirm the performance following the recommendations derived from the current test.

show abstract

Situation awareness increases when drivers have more time to take over the wheel in a Level 3 automated car: A simulator study

Cited by 66 publications

References 24 publications

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

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

Driving with and without automation on the motorway – an observational study

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

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