Persuasive technology: The silver bullet for cooperative and automated traffic?

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Challenge the future

Persuasive technology: the silver bullet

for cooperative and automated traffic?

Prof Dr Ir Bart van Arem

Road transport is vital to our society

• 80% of all passenger transport

• 60% of inland freight transport

• Transport and logistics 7% of

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200,000 people premature deaths per year in EU because of air-quality Transport generates about 25-30% of

Green House Gases 650 fatal accidents per year in NL

(EU 40,000) Societal costs €9 bilion

3 % of GDP 10 million km minute delay

societal costs € 3 billion per year

1 % of GDP

EU Market for ITS equipment and services estimated over € 20 billion per year

Automation

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5

Cooperation

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7

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A better world with cooperative

systems?

TNO expects: 50% less congestion 25% less road fatalities 20% less pollution 10% less CO2

Bart van Arem, Ben Jansen & Martijn van Noort (2008), Slimmer en beter – de voordelen van intelligent verkeer, TNO rapport 2008-D-R0996/A, Delft, the Netherlands

The platooning dilemma

15 km/l 15 km/l

18 km/l 16 km/l

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Cooperative Eco ACC

Each follower minimizes own cost

Followers jointly minimize total cost

W-LAN IEEE 802.11p

The congestion assistant

Active accelerator pedal

• Start at approach of congestion

• Counter pressure on accelerator pedal

• Smoothly adapting speed to speed of congestion tail

Stop & Go

• Takes over keeping speed and headway

• Switches on below 50 km/h, switches off above 70 km/h

M

odelling experiments 4-> 3 lane transition

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Routing dilemma

_{Route A}

Vehicle travel time 15

Total travel time 100

Route B

Vehicle travel time 20

Total travel time 90

Will a driver sacrifice 5 minutes of its own travel

time to save 10 minutes of other drivers?

Social navigation

Personal

cost

System

cost

Social

cost

=

+

Altruism

level

*

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Control versus information

Extreme scenario: full freedom of choice

Extreme scenario: no freedom of choice

2015 2020

Possible scenario A: “Indiviual traveller moving within a

societal context”

Possible scenario B: “Optimal traffic system in which

a traveller can move”

Trend breaches Informing, control and guidance go hand-in-hand Individual and market goals Collective and societal goals

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Degrees of automation

Driver only Human driver executes driving task

Driver assistance System takes over longitudinal or lateral control Partial automation System takes over longitudinal and lateral control.

Driver monitors system and can resume control at any time.

High automation System takes over longitudinal and lateral control. In case of take-over request, driver must resume control within a time interval.

Full automation System takes over longitudinal and lateral control completely and permanently

Automation and autonomy are different issues….

Acceptance

• Drivers state that they prefer warnings over control

• Control could be acceptable in special conditions such as

congestion driving

• Acceptance of (different levels of) automation increases after

(positive) experience

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Behavioural adaptation

• New systems, new behaviour

• Intended impacts • Rebound impacts

• Risk homeosthasis

• Loss of driving skills

• From vehicle driving to supervisory

control

Blue: balanced demands/capabilities Red: optimal information Green: information overload

Model experiment traffic at on-ramp

0 50 100 150 0 1000 2000 Density Flo w x=1000 0 50 100 150 0 1000 2000 Density Flo w x=1500 0 50 100 150 0 1000 2000 Density Flo w x=2000 0 50 100 150 0 1000 2000 Density Flo w x=2500 0 50 100 150 0 1000 2000 Density Fl o w x=3000 0 50 100 150 0 1000 2000 Density Fl o w x=3500

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Transitions

• Between different levels of control in partial automation

• Entering and leaving the high automation level

• Integration of traffic (sub) networks with different levels

Challenges for persuasive technology

• Cooperative and automated traffic are emerging

• Cooperation:

• Ubiquitous information can reinforce selfish behaviour • Persuasive technology can help establish cooperative self

organization

• Automation:

• Acceptance

• Behavioural adaptation