Modelling individual vehicle and driver behaviours

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Modelling individual vehicleand driver behaviours

• Stephen Cragg
• Associate SIAS Limited

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Overview

• Methodological approach
• Key achievements
• Current and future challenges

Methodological approach Key achievements Current
and future challenges
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Influences on personal travel

• Fixed
• Age, sex, health
• Limited Choice
• Employment, income, household composition,
  household location
• Active Choice
• Lifestyle (e.g. car, motorbike, cycle ownership)

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Influences on travel

• Where am I?
• Where am I going? (should I go?)
• How often? (or not at all?)
• How will I get there? (whats available?)
• When can / should I go?
• What route to take?

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Life, the Universe and Everything
Traffic Models
Traffic Models
Transport Models
Driver Vehicle Behaviour
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A model
NOT in S-Paramics!
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Behaviour model

• Logic based

If
this situation occurs
Then
do this
based on my vehicle and my driving style
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Driver behaviour

• Condensed into just three decisions
• What lane?
• Mandatory and Discretionary
• What speed?
• What gap?

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What lane?

• Mandatory rangers(i.e. need to be a lane or
  range of lanes for a manoeuvre)
• When do I find out what lane(s) I should be in?
• Signposting
• If not in right lane(s), then urgency to get in
  lane increases as I get closer to hazard

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What lane?

• Discretionary suggesters
• Keep left
• Vehicle behind me
• Slow vehicle in front of me
• Congestion
• Avoidance (incident, bus)
• On-slip / ramp

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What lane?

• Lane weightings applied
• Seniority can be applied

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What speed?

• Acceleration suggesters lowest value chosen
• Target speed
• Geometric
• Following
• Want lane change
• Let in
• Undertaking
• Friction
• Overtake (opposite carriageway)

• End speed
• Stop
• Yellow box
• Bus stop (for buses)

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What speed?

• Finally a set of vehicle specific modifiers
• Drag and inertia
• Gradient
• Modifies acceleration
• Modifies target speed (for GVs only)

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What gap?

• A Gap when driving is generally time-based
• Junctions
• Headway
• Minimum gap
• This is the closest distance Ill get to the
  vehicle in front of me.

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Behaviour model

• Logic based

If
this situation occurs
Then
do this
based on my vehicle and my driving style
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Driver characteristics

• Aggression
• This determines how I behave
• Awareness
• This determines how I respond to others
• Default is Normal Distribution
• Apply a spread

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Distribution modification

• Not all distributions are normal
• Apply a skew

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Vehicle characteristics

• Top speed
• Physical rather than legal
• Bounds of acceleration / braking
• Dimensions
• Length, width, height and mass

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Overview

• Methodological approach
• Key achievements
• Current and future challenges

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Industry Acceptance

• First Commercial Application in 1995
• First in the world (to the best of our knowledge)
• Many similar products now on the market

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Improved understanding

• Not all answers are good Thats Good!
• Confidence in design
• Our work is accessible to non-modellers

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New answers

• Metrics change
• Journey Time can now be supplemented with Journey
  Time Reliability
• Predictions of environmental impacts all
  improved
• Effect of incidents / roadworks

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New answers

• The world is changing
• Managed highways
• Selective vehicle priority
• Driver education
• Ageing Population

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Overview

• Methodological approach
• Key achievements
• Current and future challenges

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Challenges

• DATA, DATA, DATA
• Difficult to capture individual behaviour
• Difficult Expensive!
• SPEED
• Richer data
• Multiple runs

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Challenges

• Language
• Micro and Small are NOT synonyms
• Education
• Different mindset

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Challenges

• Combining traffic microsimulation with other
  driver choices. For example
• When to travel?
• How to travel (e.g. should I cycle or drive)?
• Where to travel?

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