58
Human Factors, Countermeasures & Design Principles @
Volvo Group Trucks
Emma Johansson
‘The Epic Split’
Outline
• Definitions
• Human Error
• Countermeasures
– Understanding driver inattention
– Design safe human-machine interfaces
– Create behaviour based safety solutions
– Design driving support systems
Definitions
• Human Factors
– ’dicipline of optimizing Human
Performance in the workplace’.
– Interaction between people and
environment, procedures,
machines, and people.
• HMI
– Human Machine Interaction/
Interface.
Human Error
• If nothing physically is broke in an
accident, typically human error is
what is searched for.
Human Error
• Human error could be
seen as a symptom, not
a cause, of a system
which needs to be re-
designed
Leveson, 2011; Dekker, 2007
Human Error
• There is no such thing as a root or
primary cause: accidents are the
result of multiple factors - each
necessary and only jointly
sufficient
Leveson, 2011; Dekker, 2007
Examples from 100-car study, Dingus (2006)
...multiple factors
... only
jointly
sufficient
Example from Habibovic (2013)
Human Abilities • Important to acknowledge that human behaviour
is variable. Humans can be be both bad and
extremely good at:
– decision making and path planning in complex
traffic situations
– make prediction/anticipation of upcoming events
and behaviour of other road users
– Able to adapt and respond to novel and
unexpected scenarios
“The imbalance between things that go right and
things that go wrong"
Resilience: "The intrinsic ability of a system
to adjust its functioning prior to, during, or
following changes and disturbances, so
that it can sustain required operations
under both expected and unexpected
conditions." (Paries, 2010)
Countermeasures
Understanding driver inattention
Understanding
driver
inattention
Inattention: when the driver’s allocation of
resources to activities does not match the
demands of activities requred for the control
of safety margins. (Engström, 2013)
Understanding
driver
inattention
Understanding
driver
inattention
Significantly risky
Understanding
driver
inattention
Significant protective effect
Victor (2016) Dingus (2014)
Understanding driver inattention
• Example from observations and interviews with professional truck drivers in long haul operation
(Iseland, in prep)
– Reasons for engaging in secondary tasks according to drivers
• Boredom
• Social life, staying in contact with family and friends
• Not stress (obs – long haul drivers in the group interviewed in this particular study)
– Often a coping strategy to stay alert, prevent them from becoming drowsy or let their
mind “wander off”.
– Boredom often due to monotonous drive, long hours, well-designed trucks, support systems,
automatic gearbox etc.
Design safe human-machine interface
Design safe human-machine interface while driving with automation level 0-3
• HMI solutions that minimise visual
interaction (voice, head-up
displays, haptic controls etc.)
• Interaction management –
intelligent prioritisation and
scheduling of information from
external apps
• Standardised solution for nomadic
device integration
• Automatic ”drive mode” adaptation
of apps
Design safe human-machine interface while driving with automation level 0-3
• HMI solutions that minimise visual
interaction (voice, head-up
displays, haptic controls etc.)
• Interaction management –
intelligent prioritisation and
scheduling of information from
external apps
• Standardised solution for nomadic
device integration
• Automatic ”drive mode” adaptation
of apps
Design safe human-machine interface
European Statement of Principles
• Overall Design, Installation, Information presentation, interaction with displays and controls,
System behaviour, Information about the system. Examples:
– Visual displays should be positioned as close as practicable to the driver's normal line
of sight
– Visually displayed information presented at any one time by the system should be
designed such that the driver is able to assimilate the relevant information with a few
glances which are brief enough not to adversely affect driving.
– Internationally and/or nationally agreed standards relating to legibility, audibility, icons,
symbols, words, acronyms and/or abbreviations should be used.
– Information with higher safety relevance should be given higher priority.
– The driver should always be able to keep at least one hand on the steering wheel
while interacting with the system.
– The system should not require long and uninterruptible sequences of manual-visual
interfaces. If the sequence is short, it may be uninterruptible.
– Etc...
Designing safe human-machine interface
• Safe integration of nomadic devices, apps etc.
Create behaviour based safety solutions
Create
behaviour
based safety
solutions
Wege & Victor, 2013
Behavioral-based safety (BBS)
generally refers to
‘methods and techniques for obtaining sustained changes in
behavior, with the purpose to increase work safety and reduce
safety-related costs. In the context of driving, this may include driver
training, coaching and self-learning and BBS can be viewed as one
component in more generic safety management programs for
commercial fleets’.
Other references to studies involving or presenting overviews of BBS services: Pradhan, A., Lin, B., wege, C., Babel, F. (2017). Piccinini, G. F. B., Engström, J., Bärgman, J., & Wang, X. (2016). Hickman J, Hanowski R. (2011). Hickman J, Hanowski R. (2010). Hickman, J.S., R.R. Knipling, R.J. Hanowski, Hickman et al. (2007).
Design driving support systems
Systems – examples of what Volvo
Trucks offers its customers today
• Stay attentive
• Maintain safe speed & distance
• Drive within the lane
• Avoid overtaking in critical situations
• Mitigate and reduce severity of rear-end
accidents
(See more details in Laurent’s presentation)
Systems – examples of what Volvo
Buses offers its customers today
Systems – examples of the
future
Design driving support systems The overall goal
In addition to:
• Fuel savings
• Improved
uptime
Design driving support systems examples of Human Factors challenges
Design driving support systems Human Error (again)
• With a simplified view on human
error the solution has often been
to marginalise the driver/
operator by putting in more
automation or trying to remove
the human being more or less
completely.
Leveson, 2011; Dekker, 2007
Design driving support systems
• So far, there is no fail proof software. To replace the
human behind the wheel being with a machine
(designed by another human) only works if the task
environment is very static and predictable and a
priori controllable…
• Ensure intended effects of the functions are reached
by taking both technology and driver’s intent and
actions into account as well as technical and human
limitations.
• Implies the idea of complementary intentions,
abilities, actions of human and automation that are
used together to achieve one common goal.
historia de los burros
• Automated
steering
interventions
can reduce
collisions.
• Some drivers
however
counteracted
the automated
steering
intervention.
Examples of non-complementary actions: Investigating the effectiveness of automatic steering intervention (ex. from interactIVe)
When developing systems we should:
• define the actual function from a driver’s
perspective
• explain how, when and where information,
warnings, interventions and support should be
activated
• cover the I/O components and the interaction
with the driver through
– visual,
– auditory and
– haptic output/input (e.g. as information and
warnings) including active vehicle steering,
braking, acceleration through actuators
From AdaptIVe project,
adapted from Flemish (2008)
Design driving
support systems - different HF challenges depending on
levels of automation (SAE)
• Driver is in charge!
• System is in charge!
Design driving
support systems - different HF challenges depending on
levels of automation (SAE)
Overcome the
problem with
multiple, individual
systems. Integrate,
group etc.
Adapted from Ohn-Bar &
Trivedi, 2016
Research Questions &
Design Guidelines
Human Factors
non-functional
recommendation
References
Examples
Human Factors
Challenge
Application
scenario Highway (SP6),
Urban (SP5), Close-Distance
(SP4)
Addressed SAE Level
Related 4A
sub-category
Unique ID Name of the recommendation derived from its related topic
Human Factors
functional
recommendatio
n
Example design
guideline
ID Name
FR1A_TDT “Takeover of driving task"
Related SAE Levels:
SAE0 SAE1 SAE2 SAE3 SAE4
x x x
Related to 4A subcategories: AGENT STATE
Automation State Vehicle State Environment state Driver State
x
Related to the following applications
Highway Urban Close-Distance
x x x
Human Factors challenge
The automation does not check if the driver has taken over the driving task.
Human Factors recommendation
The automation should be able to detect that the driver has taken over the driving task.
Already existing approaches and examples
FR1A_TDT.E1: Consider a Hands-on check to ensure driver is ready to take over
FR1A_TDT.E2: Consider a Foot-on check to ensure driver is ready to take over
FR1A_TDT.E3: Check driver’s inputs (e.g. button press) if he/she is ready to take over
FR1A_TDT.E4: Check driver’s attentional state if he/she is ready to take over
References
Flemisch & Schieben (2009); HAVEit D33.2 P. 27; Meyer & Beiker (2015); Vogelpohl et al. (2016)
Tools and Methodologies
• Lab vs. field
• Subjective vs. Objective data
• Controlled vs. Quasi experimental
• Tools (eye tracking, vehicle signals, ...)
References • Alphonse Chapanis, A. (1991). To Communicate the Human Factors Message, You Have to Know What the
Message Is and How to Communicate It. Human Factors Society Bulletin , Volume 34, Number 11, November 1991,
pp 1-4
• Leveson, N. G. (2011). Engineering a Safer World: Systems Thinking Applied to Safety. MIT Press, 2011. ISBN 978-
0-262-01662-9.
• Dekker, S. (2007). Just Culture: Balancing Safety and Accountability, Ashgate Publishing, Ltd. • Dekker, S. (2006).
The Field Guide to Understanding Human Error. Ashgate Publishing, Aldershot, U.K.
• Wege, C., & Victor, T. (2013). The DO-IT BEST Feedback Model - Distracted Driver Behaviour Management and
Prevention Before, While And After Driving. Proceedings of the Third International Conference on Driver Distraction
and Inattention. Göteborg, Sweden. Full text also accepted for publication In M Regan, J Lee, & T Victor (Eds).
Driver Distraction and Inattention. Advances in Research and Countermeasures Volume II. Ashgate Publishing
Limited. 2014.
• Olson, R.L., Hanowski, R.J., Hickman, J.S., Bocanegra, J. (2009) Driver Distraction in Commercial Vehicle
Operations. DTMC75-07-D-00006.
• Dingus, T. A. (2014). Estimates of Prevalence and Risk Associated with Inattention and Distraction Based Upon In
Situ Naturalistic Data. Annals of Advances in Automotive Medicine, 58, 60–68.
References • Victor, T., Dozza, M., Bärgman, J., Boda, C-N., Engström, J, Flannagan, C., Lee, J. D., Markkula, G. (2016).
Analysis of Naturalistic Driving Study Data: Safer Glances, Driver Inattention, and Crash Risk
• Engström, J., Monk, C. A., Hanowski, R. J., Horrey, W. J., Lee, J. D., McGehee, D. V., Regan, M., Stevens, A.,
Traube, E., Tuukkanen, M., Victor, T., Yang, C. Y. D. (2013). A conceptual framework and taxonomy for
understanding and categorizing driver inattention. Brussels, Belgium: European Commission.
http://ec.europa.eu/newsroom/dae/document.cfm?doc_id=2671
• Dingus, T. A., Klauer, S.G., Neale, V. L., Petersen, A., Lee, S. E., Sudweeks, J., Perez, M. A., Hankey, J., Ramsey,
D., Gupta, S., Bucher, C., Doerzaph, Z. R., Jermeland, J., and Knipling, R.R. (2006). The 100-Car Naturalistic
Driving Study Phase II – Results of the 100-Car Field Experiment
https://www.nhtsa.gov/sites/nhtsa.dot.gov/files/100carmain.pdf
• Treat, J. R., Tumbas, N. S., McDonald, S. T., Shinar, D., Hume, R. D., Mayer, R. E., Stansifer, R. L., & Catellan, N.
J. (1979). Tri-Level Study of the Causes of Traffic Accidents: Final Report Volume I: Causal Factor Tabulations and
Assessments (DOT HS-805 085). Institute for Research in Public Safety, Indiana University.
• Treat, J.R. et al (1979). ‘Tri-level study of the causes of traffic accidents: final report. Executive summary’, ‘Tri-
level study of the causes of traffic accidents. Volume II: Special Analyses’.
References • Habibovic, A., Tivesten, E., Uchida, N., Bärgman, J., & Ljung Aust, M. (2013). Driver behavior in car-to-pedestrian
incidents: An application of the Driving Reliability and Error Analysis Method (DREAM). Accident Analysis &
Prevention, 50, 554–565. doi: 10.1016/j.aap.2012.05.034
• Paries, J., Wreathall, J., Hollnagel, E., Woods, D. D (2010). Resilience Engineering in Practice (2010)
• Dingus, T. A. (2014). Estimates of Prevalence and Risk Associated with Inattention and Distraction Based Upon In
Situ Naturalistic Data. Annals of Advances in Automotive Medicine, 58, 60–68.
• Iseland, T., Johansson, E., Dåderman (in prep.) A study of long haul truck drivers’ work tasks and motivational
factors behind secondary tasks.
• Volvo Trucks launches integrated system for services and infotainment - Volvo Trucks press release (2017)
http://www.volvotrucks.com/en-en/news-stories/press-release.html?pubid=21744
• J3016_201609 Taxonomy and Definitions for Terms Related to Driving Automation Systems for On-Road Motor
Vehicles https://saemobilus.sae.org/content/j3016_201609
• http://www.volvogroup.com/en-en/about-us/traffic-safety.html
• https://www.youtube.com/watch?v=8tqVX4HPHUU&feature=youtu.be
References • European Statement of Principles (ESoP) on Human Machine Interface for In-Vehicle Information and
Communication Systems (1998). http://cordis.europa.eu/pub/telematics/docs/tap_transport/hmi.pdf
• Updated ESoP (2006). http://eur-lex.europa.eu/LexUriServ/LexUriServ.do?uri=OJ:L:2007:032:0200:0241:EN:PDF
• Flemisch, F., Kelsch, J., Löper, C., Schieben, A., Schindler, J. (2008). Automation spectrum, inner / outer
compatibility and other potentially useful human factors concepts for assistance and
automation.https://www.academia.edu/4238375/Automation_spectrum_inner_outer_compatibility_and_other_pote
ntially_useful_human_factors_concepts_for_assistance_and_automation and in HumanFactors for assistance and
automation (pp. 1 - 16). Maastricht, the Netherlands: Shaker Publishing.
• Kelsch, J., Dziennus, M., Schieben, A., Schömig, N., Wiedemann, K., Merat, N., Louw, T., Madigan, R.,
Kountouriotis, G., Ljung Aust, M., Söderman, M., Johansson, E. (2017). AdaptIVe Deliverable D3.3 Final functional
Human Factors recommendations
• AdaptIVe project https://www.adaptive-ip.eu/
• interactIVe project: http://www.interactive-ip.eu/
• HAVEit project: http://www.haveit-eu.org/
References
• Ohn-Bar, E., Trivedi, M. M. (2016). Looking at Humans in the Age of Self-Driving and Highly Automated Vehicles.
IEEE Transactions on Intelligent Vehicles (T-IV).
• “Study Says Video-Based Safety System Could Cut Fatalities 20%”.
http://www.truckinginfo.com/channel/drivers/news/story/2014/05/study-says-video-based-safety-system-could-cut-
fatalities-20.aspx
• Lytx: https://www.lytx.com/en-us/
• Pradhan, A., Lin, B., Wege, C., Babel, F. (2017) (Ulm University – Germany) Effects of Behavior-Based Driver
Feedback Systems on Commercial Long Haul Operator Safety. Presented at the Driving Assessment Conference
2017.
• Piccinini, G. F. B., Engström, J., Bärgman, J., & Wang, X. (2016). Factors contributing to commercial vehicle rear-
end conflicts in China: A study using on-board event data recorders. Submitted for publication
• Hickman J, Hanowski R. (2010) Evaluating the safety benefits of a low-cost driving behavior management system
in commercial vehicle operations. Federal Motor Carrier Safety Administration report.
References
• Hickman J, Hanowski R. (2011). Use of a video monitoring approach to reduce at-risk driving behaviors.
Transportation Research Part F, 2011,14: p.189–198
• Hickman, J.S., R.R. Knipling, R.J. Hanowski, D.M. Wiegand, R.E. Inderbitzen, and G. Bergoffen (2007) CTBSSP
Synthesis Report 11: Impact of Behavior-Based Safety Techniques on Commercial Motor Vehicle Drivers,
Transportation Research Board of the National Academies, Washington, D.C., 2007.CTBSSP Hickman et al.
(2007)
• ‘Increasing safety through awareness and training’ http://www.volvogroup.com/en-en/about-us/traffic-safety.html
• ‘Volvo European Accident Research and Safety Report’ http://www.volvogroup.com/en-en/about-us/traffic-
safety.html
• ’Volvo Group Safety Vision’ http://www.volvogroup.com/content/dam/volvo/volvo-group/markets/global/en-
en/about-us/traffic-safety/volvo-safety-vision-poster-2016.pdf
• Wege, C., Larsson, P, Rydström, A. (2014). Safe Connectivity Recommendations. SICS project report.
