Institute for Transport StudiesFACULTY OF ENVIRONMENT

Advances in Human Factors of Vehicle Automation

Tyron Louw

University of Leeds

UK

www.its.leeds.ac.uk

ITS, Leeds

Louw, T., Merat, N. & Jamson, H. (submitted). Engaging With Automation: To be Or Not To Be In The Loop. Driving Assessment 2015: 8th International Driving Symposium on Human Factors in Driver Assessment, Training, and Vehicle Design .

Merat, N., Jamson, a. H., Lai, F. F. C. H., Daly, M., & Carsten, O. M. J. (2014). Transition to manual: Driver behaviour when resuming control from a highly automated vehicle. Transportation Research Part F: Traffic Psychology and Behaviour, 26(March 2012), 1–9.

Jamson, a. H., Merat, N., Carsten, O., & Lai, F. C. H. (2013). Behavioural changes in drivers experiencing highly-automated vehicle control in varying traffic conditions. Transportation Research Part C: Emerging Technologies, 30, 116–125. Merat, N., & Jamson, a. H. (2008). How do drivers behave in a highly automated car? In PROCEEDINGS of the Fifth International Driving Symposium on Human Factors in Driver Assessment, Training and Vehicle Design HOW (pp. 514–521).

Carsten, O., Lai, F. C. H., Barnard, Y., Jamson, a. H., & Merat, N. (2012). Control Task Substitution in Semiautomated Driving: Does It Matter What Aspects Are Automated? Human Factors: The Journal of the Human Factors and Ergonomics Society, 54(5), 747–761.

Merat, N., Jamson, a. H., Lai, F. C. H., & Carsten, O. (2012). Highly Automated Driving, Secondary Task Performance, and Driver State. Human Factors: The Journal of the Human Factors and Ergonomics Society, 54(5), 762–771. Merat, N., Jamson, a. H., Lai, F. F. C. H., Daly, M., & Carsten, O. M. J. (2014).

Jamson, a. H., Merat, N., Carsten, O., & Lai, F. C. H. (2011). Fully-Automated Driving: The Road to Future Vehicles. In Driving Assessment 2011: 6th International Driving Symposium on Human Factors in Driver Assessment, Training, and Vehicle Design .

Toffetti, A., Wilschut, E. S., Martens, M. H., Schieben, A., Rambaldini, A., Merat, N., & Flemisch, F. (2009). CityMobil Human Factor Issues Regarding Highly Automated Vehicles on eLane. Transportation Research Record: Journal of the Transportation Research Board, 2110(2110), 1–8.

Merat, N., & Jamson, a. H. (2008). How do drivers behave in a highly automated car? In PROCEEDINGS of the Fifth International Driving Symposium on Human Factors in Driver Assessment, Training and Vehicle Design HOW (pp. 514–521).

www.its.leeds.ac.uk

Merat et al. (2014)

“Transition to manual: Driver behaviour when resuming control from a highly automated vehicle”

Aim: Investigate drivers’ ability to resume control from a highly automated vehicle in two conditions:

i. When automation was switched off and manual control was required at a system-based, regular interval

ii. When transition to manual was based on the length of time drivers were looking away from the road ahead

www.its.leeds.ac.uk

Merat et al. (2014)

Measures used:• Time it took drivers to successfully resume

control from the automated system• Steering behaviour – SDLP, High Frequency

component of steering • Eye tracking data: visual attention to the

surrounding environment (PRC) & pattern of drivers’ eye fixation – FaceLab.

www.its.leeds.ac.uk

Merat et al. (2014)

Time: p < .05Drives: p = .001

Compared to the Fixed Drive, drivers’ visual attention to the road centre was generally more diverse during the first minute of manual control after the Variable Drive

10–15 s lag time between disengagement of the automation and resumption of control by the driver

Figure 1. Percent road centre values during the first minute after control is transferred back to the drivers for the fixed and Variable drives (Error bars represent standard errors).

Results

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Merat et al. (2014)

When required to resume control drivers take ~30-45 seconds to stabilise behaviour

Time: p < .0001

Figure 2. High frequency component of steering during the first minute after control is transferred back to the drivers for the Fixed And Variable drives (Error bars represent standard errors).

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Merat et al. (2014)

If drivers are out of the loop due to control of the vehicle in Level 3 automation, their ability to regain control of the vehicle is better if they are expecting automation to be switched off

BUT

Regular disengagement of automation is not a practical method for keeping drivers in the loop

So

Raises the question how do we inform drivers of their obligation to resume control of driving from an automated system?

www.its.leeds.ac.uk

Louw, Merat & Jamson (submitted)

“Engaging With Highly Automated Driving: To Be Or Not To Be In The Loop?”

Aim: Investigate effect of engagement in a reading task during vehicle automation on drivers’ ability to resume manual control and successfully avoid an impending collision.

To understand how… 1. driver state before a transition and2. driver workload during a transition

… influences driver performance

www.its.leeds.ac.uk

Louw, Merat & Jamson (submitted)

Figure 3. Schematic representation of the driving scenario

Driving Scenario

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Louw, Merat & Jamson (submitted)

Figure 4. Driving simulator set-up. Central display unit (inset) indicated automation status.

3x3 Within-subjects Design

Drive (Manual, Engaged Automation, Distracted Automation)

Further out of the loop

Load (No Rule, Congruous rule, Incongruous Rule)

Control Level Tactical Level Driving tasks (Michon, 1985)

Figure 5. Representation of the congruous and incongruous rule conditions

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Louw, Merat & Jamson (submitted)

p=.001 p=.058P<.001

Measures• Maximum lateral and longitudinal acceleration• Time to first steering input• Time to complete lane change (avoidance manouvre)• Distribution of collision reaction inputs (steering, braking, steering & braking)

Results

Figure 6. Maximum lateral acceleration for Drive

Figure 7. Time to first steer for Drive Figure 8. Time to change lane for Drive

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Louw, Merat & Jamson, 2015

No collisions across all trials

• No rule: 89% of cases drivers chose to follow the lead vehicle to avoid a collision.

• Congruent rule: 100% of cases drivers managed to adhere to the rule • Incongruent rule: 99% of cases drivers managed to adhere to the rule

No Effect of LOAD

Table 2. Brake and Steer combinations for Drive

www.its.leeds.ac.uk

Louw, Merat & Jamson (submitted)

Conclusions

• Drivers experiencing automation were slower to identify the potential collision scenario

BUT

• Once identified the collision was evaded more erratically and at a faster pace than when drivers were in manual control of the vehicle

• Distracted automation: Quicker but more volatile responses

• 6.5s enough for simple control and tactical driving tasks after short periods of automation

www.its.leeds.ac.uk

Future Research

• Transitions into more complex, strategic-level driving tasks

• Effects of long durations under automation – 5/10/15mins

• Effective hand-off strategies

Institute for Transport StudiesFACULTY OF ENVIRONMENT

Thank you for your attention!

Tyron Louw

Institute for Transport Studies

University of Leeds

t.l.louw@leeds.ac.uk