Modelling individual vehicleand driver behaviours

Stephen Cragg

Associate – SIAS Limited

Overview

Methodological approach

Key achievements

Current and future challenges

Methodological approach

Key achievements

Current and future challenges

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)

Influences on travel

Where am I?

Where am I going? (should I go?)

How often? (or not at all?)

How will I get there? (what’s available?)

When can / should I go?

What route to take?

Life, the Universe and Everything

TrafficModels

Transport Models TrafficModels

Driver & VehicleBehaviour

A model

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Behaviour model

Logic based

If

Then

this situation occurs

do thisbased on my vehicle and my driving style

Driver behaviour

Condensed into just three decisions

•What lane?~Mandatory and Discretionary

•What speed?

•What gap?

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

What lane?

Discretionary suggesters

•Keep left

•Vehicle behind me

•Slow vehicle in front of me

•Congestion

•Avoidance (incident, bus)

•On-slip / ramp

What lane?

BUSLe

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SlowCar

Be

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FastCar

Lane weightings applied

•Seniority can be applied

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)

What speed?

Finally a set of vehicle specific modifiers

•Drag and inertia

•Gradient~Modifies acceleration~Modifies target speed (for GVs only)

What gap?

A Gap when driving is generally time-based

•Junctions

•Headway

•Minimum gap~This is the closest distance I’ll get to the vehicle in front of me.

Behaviour model

Logic based

If

Then

this situation occurs

do thisbased on my vehicle and my driving style

Driver characteristics

Aggression

•This determines how I behave

Awareness

•This determines how I respond to others

Default is Normal Distribution

•Apply a spread0

5

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Default Distribution

Fre

qu

ency

Distribution modification

Not all distributions are normal

•Apply a skew

0

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Skew Distribution

Fre

qu

ency

Vehicle characteristics

Top speed

•Physical rather than legal

Bounds of acceleration / braking

Dimensions

•Length, width, height and mass

Overview

Methodological approach

Key achievements

Current and future challenges

Industry Acceptance

First Commercial Application in 1995

•First in the world (to the best of our knowledge)

Many similar products now on the market

Improved understanding

Not all answers are good – That’s Good!

Confidence in design

Our work is accessible to non-modellers

New answers

Metrics change

•Journey Time can now be supplemented with Journey Time Reliability

•Predictions of environmental impacts– all improved

•Effect of incidents / roadworks

New answers

The world is changing

•Managed highways

•Selective vehicle priority

•Driver education

•Ageing Population

Overview

Methodological approach

Key achievements

Current and future challenges

Challenges

DATA, DATA, DATA

•Difficult to capture individual behaviour

•Difficult = Expensive!

SPEED

•Richer data

•Multiple runs

Challenges

Language

•Micro and Small are NOT synonyms

Education

•Different mindset

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?