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Effect of instructing system limitations on the intervening behavior of drivers in partial driving automation

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Abstract

Proper understanding of automation limitations is vital in order for drivers to deal with unexpected critical situations. The present study focuses on explanation-based knowledge of the limitations given to novice drivers who have no knowledge and experience of using driving automation systems. The knowledge is discussed considering (1) the possibility of the automation failing to issue an alert when the driving automation cannot handle the situation and (2) the manner of describing the limitations from either a functional or scenic point of view. An experiment conducted under 2 × 2 conditions of explanation-based knowledge (n = 24 participants per condition, average age of the participant = 55.9 ± 16.2 years) is implemented in a driving simulator. Data on transition time from automated control to manual control are collected. The results reveal that drivers could intervene more safely if the knowledge is described from a scenic point of view (average ratio of safe intervention = 95%, average reaction time = 2.0 s), as compared to a functional description (88%, 2.3 s). Explicit/scenic knowledge was found to be more beneficial in responding to alerts in such situations involving system limitations as well as in dealing with critical system failures. Further investigation of glance behavior and interviews revealed that novice drivers with explicit/functional knowledge are prone to be over-reliant on the automation’s capability. Therefore, the present study clarified that providing a driver with knowledge about system limitations/failures explicitly while giving is instructive for perceiving and responding to system limitations as well as unexpected hazards due to system failures.

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Acknowledgements

The present study was conducted as a part of the SIP-adus Project entitled “Strategic Innovation Promotion Program (SIP) Automated Driving Systems/Large-Scale Field Operational Test/HMI”. The authors would also like to thank N. Kashiwazaki, Y. Noguchi, R. Taguchi, Y. Ishitsuka, S. Funoki, K. Toyoda, T. W. Liu, S. Nishina, and R. Umeno for their help in data collection and analyses.

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Authors and Affiliations

  1. Faculty of Engineering, Information and Systems, University of Tsukuba, 1-1-1 Tennoudai, Tsukuba, Ibaraki, 305-8573, Japan

    H. P. Zhou & M. Itoh

  2. Automotive Human Factors Research Center, National Institute of Advanced Industrial Science and Technology, 1-1-1 Higashi Tsukuba, Ibaraki, 305-8566, Japan

    S. Kitazaki

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  1. H. P. Zhou
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  2. M. Itoh
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Appendices

Appendix 1: Descriptions of events, the HMI, and instructions in the eight scenarios

Scenario

Does system issue an alert in the HMI

Descriptions about system limitations

No.

Event

Functional way

Scenic way

A

Range of visibility is less than 40 m because of heavy fog

Yes

System does not work when traffic lines are not sensed

Visual field becomes worse due to deep fog

A′

Pavement marking cannot be detected

Yes

*Not be unexplained in the instruction

A″

Heavy snow is falling

Yes

*Not be unexplained in the instruction

B

Lane closed with pylons because of falling objects

Failed

System cannot recognize static objects on the road

Highway lane is closed due to objects on the road

B′

Lane closed with pylons because of construction

Failed

*Not be unexplained in the instruction

B″

Lane closed without pylons because of a stopped car

Failed

*Not be unexplained in the instruction

C

Car approaches an expressway junction

Yes

System cannot change lanes automatically

Car approaches an expressway junction

C′

Lane reduction occurs

Yes

*Not be unexplained in the instruction

Appendix 2: Descriptions of data collection under the four conditions

Procedure

Group

G1: Explicit/functional

G2: Explicit/scenic

G3: Implicit/functional

G4: Implicit/scenic

1. Common instruction

Purpose of data collection

Agreement on informed consent sheet

Manual operation of driving simulator

Exercise on manual operation

Use of automated driving system

Exercise on automated driving

2. Conditioned instruction

Explicit instructions about the possibility that the system will fail to provide an alert

Implicit instructions about the possibility that the system will fail to provide an alert

Functional description of system limitations

Scenic description of system limitations

Functional description of system limitations

Scenic description of system limitations

3. Data collection

12 trials (nine trials in which RtI events occur and three trials in which no RtI events occur)

Note that half of participants were instructed to undergo the 12 trials in Order Aa, whereas the other participants were instructed to undergo the 12 trials in Order Bb

4. Interview

  1. aOrder A: Scene: A (heavy fog) → D (dummy trial) → C′ (lane reduction) → D′ (dummy trial) → B (lane closed) → A′ (lines blurred) → B′ (lane closed) → C (junction) → D″ (dummy trial) → B (lane closed) → A″ (Heavy snow)
  2. bOrder B: Scene: C′ (lane reduction) → B (lane closed) → D (dummy trial) → A (heavy fog) → A′ (lines blurred) → D′ (dummy trial) → A″ (heavy snow)

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Zhou, H.P., Itoh, M. & Kitazaki, S. Effect of instructing system limitations on the intervening behavior of drivers in partial driving automation. Cogn Tech Work 22, 321–334 (2020). https://doi.org/10.1007/s10111-019-00568-1

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