Implications of self driving cars

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1 Challenge the future

University of Capetown, 11thdecember 2014 University of Capetown, 11thdecember 2014 Challenge the future 2

University of Capetown, 11th_{december 2014}

The Netherlands

World rank South Africa Area 41.543 km2 135 1.221.037 km2 Population 16.730.623 63 48.601.098 GDP per inhabitant € 34.822 17 $12.100 (large differences) x30 x3 South Africa Capital Pretoria 4 Challenge the future

Infrastructure of the Netherlands

Waterway density Liechtenstein 0,18 Netherlands 0,15 Belgium 0,07 Bangladesh 0,06 Vietnam 0,05 Roadway density Belgium 5,03 Netherlands 3,29 Japan 3,20 Hungary 2,12 Jamaica 2,01 Railway Density Czech Republic, Switzerland, Germany 0,12

Belgium 0,11

Hungary 0,09

Cuba, Austria 0,08

Netherlands, Slovakia, Japan,

United Kingdom 0,07

South Africa 0,44 (0,05 paved) South Africa 0.02

Transport in the Netherlands

Motorways with daily volume over 180.000 vehicles Netherlands 15 United Kingdom 2 Germany 2 0% 5% 10% 15% 20% 25% 30%

Bicycle share in all trips

The TU Delft Transport Institute

To improve societal

visibility To further improve scientific quality Internal and external collaboration Create focus and mass

7 faculties

60 staff members

Education 200 MSc py, 20 PhD py

Multidisciplinary projects

Valorization

Communication

Traffic Management

Transport Policy

Freight Transport & Logistics

Spatial Planning and Mobility

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University of Capetown, 11thdecember 2014

What are

self-driving cars?

Self driving cars can improve traffic efficiency and safety Netherlands to facilitate large

scale testing of self driving vehicles Dutch minister of Infrastructure

and Environment Mrs Melanie Schultz

Partial automation

High automation

Full automation

Available,

Mercedes S class

Limited scope

Decades away

unless on

dedicated

infrastructure or

driving very slowly

Massive worldwide

R&D

What is automated driving?

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University of Capetown, 11thdecember 2014 University of Capetown, 11thdecember 2014 Challenge the future14

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Technologies Adaptive

Cruise Control

Radar

• Longe range 70 GHz 100-150m

• Short range 24 GHz 20 m

Video camera

• now: monocular

• Stereovision

Dedicated Short Range Communication

• IEEE 802.11p (wifi) 200-300 m

Cooperative

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Huge investments in technology

Sensing

Communication

Positioning

Data fusion

Situation awareness

Trajectory predication

Cooperative control

Traffic management

Driver monitoring

Performance

Complexity

Security

Privacy

Liability

Failure modes

Weather conditions

Energy

Cost

Fundamental changes in driving

behaviour

Workload,

driving performance,

attention,

situation awareness

risk compensation,

Driver Vehicle Interface,

acceptance,

mode transition,

purchase and use

Driver in control

Vehicle in control

Driver supervision

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University of Capetown, 11thdecember 2014 University of Capetown, 11thdecember 2014 Challenge the future20

Potential impacts on traffic

Prevent traffic jams by better stability Solve traffic jams by

increased outflow

Better distribution of traffic over network

Less congestion delay Better energy efficiency No accidents (?) Decreased throughput by larger headways Decreased stability by lack of anticipation Increased risk of congestion

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Car driving more attractive!

Partial automation

High automation

Full automation

Better comfort, Less accidents Less congestion

Travel time can partially be used for other purpose

Travel time can fully be used for other purposes

More car trips?

Decreasing

congestion makes

latent demand

manifest

Car trips become

more attractive

4-8 % VMT increase (Gucwa, 2014)

Changes in activity

patterns?

100% capacity

increase

Car trips valued as

high quality rail

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