Presented at the AITPM National Conference 2017

1. www.jacobs.com | worldwide
Getting Proactive rather than Reactive in AV infrastructure planning
John Richardson, Peter Hunkin and Scott Wilkinson
AITPM Conference August 2017

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2

3. Thesis:
Connected autonomous vehicles (CAV)
are coming and we need to start
planning the necessary infrastructure
to get ahead of the curve!!!
(or maybe just to try to catch up…)
3
Wilkinson, Hunkin and Richardson – Getting Proactive rather than Reactive in AV Planning

4. Top 263 companies racing towards autonomous cars
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Wilkinson, Hunkin and Richardson – Getting Proactive rather than Reactive in AV Planning
Source: https://www.wired.com/2017/05/mapped-top-263-companies-racing-toward-autonomous-cars/

5. But this is mostly about vehicles NOT infrastructure…
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Wilkinson, Hunkin and Richardson – Getting Proactive rather than Reactive in AV Planning

6. What are CAVs?
• Autonomous Vehicle (AV)
– Vehicle capable of sensing its environment and navigating without
human input – (source: Wiki)
• Connected Autonomous Vehicles (CAV)
– Self driving cars that monitor the network and fully control the car
without any driver involvement
• Partially Autonomous Vehicles (PAV)
– Driver assistance systems such as lane guidance systems,
braking systems etc
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Wilkinson, Hunkin and Richardson – Getting Proactive rather than Reactive in AV Planning

7. Levels of automation
http://advi.org.au/australia/levels-of-automation/ 7
Wilkinson, Hunkin and Richardson – Getting Proactive rather than Reactive in AV Planning

8. But what will a world with CAVs look like?
• Many different views on potential outcomes:
– CAVs will reduce congestion – due to ‘AV carpooling’?
– CAVs will increase congestion – due to ‘empty running’?
– CAVs will change car ownership – ‘AV carpooling’?
– CAVs will take years to be effective – limited take-up?
– CAVs will be effective from day one – safety benefits?
– CAVs will only be effective on motorways – own lane?
• Different scenarios require different infrastructure
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Wilkinson, Hunkin and Richardson – Getting Proactive rather than Reactive in AV Planning

9. Which one will
eventuate?
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Wilkinson, Hunkin and Richardson – Getting Proactive rather than Reactive in AV Planning
BAU
SAME congestion
SAME environment
2R - Electric & CAV
SAME congestion
BETTER environment
3R - 2R + SHARING
BETTER congestion
BETTER environment

10. Planning for CAVs is ‘too hard’…
• If we don’t know what it will look like…
– How do we know which scenario will eventuate?
– Can we plan for different/alternate scenarios?
– How to practically use modelling tools to test scenarios?
• At present we are waiting for technology to
determine the ‘answer
• We should be engaged at the policy level to assist
with forward thinking and planning to meet needs
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Wilkinson, Hunkin and Richardson – Getting Proactive rather than Reactive in AV Planning

11. “But it could take decades…”
Not according to some…
• Inventivio1 says this is a common misconception:
– Past technologies took time to get to mass market
– Initially available only in premium cars (ABS, airbags)
– But this is because they give ‘little’ benefit for high cost
– AVs have multiple benefits and will be competitive market
– Benefits will be more cost effective for general market
– And if AV pooling is embraced it could accelerate quickly
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Wilkinson, Hunkin and Richardson – Getting Proactive rather than Reactive in AV Planning
1. http://www.inventivio.com/innovationbriefs/2016-09/Top-misconceptions-of-self-driving-cars.pdf

12. Can we be proactive rather than reactive?
• What if we can model CAV options to inform the
debate on effectiveness?
• What if we can develop models to test scenarios?
– Then we can assist and inform the debate?
– Then we can inform policy and decision makers?
– Then we can help to drive legislation through informed
analysis?
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Wilkinson, Hunkin and Richardson – Getting Proactive rather than Reactive in AV Planning

13. What do we focus on?
• Levels of CAV ownership that might occur
• Levels of CAV sharing that might occur
• Need for and impact of priority CAV lanes
• CBD parking needs and CAV circulation
• Timing of CAV implementation & take-up rates
• Impacts on peak period car demand & congestion
• Impacts on public transport demand & operation
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Wilkinson, Hunkin and Richardson – Getting Proactive rather than Reactive in AV Planning

14. CAV issues are all inter-related
CAV
Ownership
CAV
Sharing
Timing &
take-up
CAV
circulation
Priority
lanes
CAV
holding
areas
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Wilkinson, Hunkin and Richardson – Getting Proactive rather than Reactive in AV Planning

15. Opportunities and limitations of transport models
• Car ownership (CO) models in current ‘toolkits’
• Modify CO to reflect future CAV ownership
• Model CAVs as new transport mode?
• Need to develop CAV ‘service parameters’
• Some software developers investigating specialist
modules for CAVs
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Wilkinson, Hunkin and Richardson – Getting Proactive rather than Reactive in AV Planning

16. Modelling issues and benefits
• How to model CAV lane allocation?
– Similar to HOV / HOT lane modelling, sensitivity tests
• How to model CAV circulation?
– Models include this as function of trip purposes by time of day
• How to model remote CAV parking areas?
– Similar to models that choose park and ride locations
• How to model take-up rate?
– Need to run a series of sensitivity tests
• Need to manage empty CAV running
– Bad outcome needs policy measures to manage effectively
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Wilkinson, Hunkin and Richardson – Getting Proactive rather than Reactive in AV Planning

17. Many issues… many potential scenarios…
Three scenarios have been developed:
• Scenario 1: “Driverless cars rule the world”
• Scenario 2: “CAV sharing becomes popular”
• Scenario 3: "Hybrid ownership model“
Each considers issues such as CAV ownership, car
pooling, lane allocation on motorways, parking
needs, CAV circulation, peak period demands,
congestion impacts, public transport impacts
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Wilkinson, Hunkin and Richardson – Getting Proactive rather than Reactive in AV Planning

18. Outline of potential scenarios to model
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Wilkinson, Hunkin and Richardson – Getting Proactive rather than Reactive in AV Planning
Scenario Key assumptions Details to explore
1. Driverless cars rule
the world
Rapid take up of privately owned CAVs
CAV only lanes added to Motorways
Changes to traditional parking
High peak period travel demand
Mixing of CAVs and non-CAVs
Should this be expanded to arterial and other roads
The impacts of vehicles circulating vs centralised parking lots
Can additional road capacity support increased demand
2. CAV sharing model Car ownership falls – people happy to share a fleet privately owned
Less cars on the road
CAVs circulate waiting for next trip
Reduction in traditional public transport mode shares
The impacts of different cost models
Investigate changes to VKT, VHT, peak travel and distance per
person trip
Update algorithms to deal with circulating CAVs. What happens
during off-peak periods if CAVs are oversupplied
Identify which services will not be required and how CAVs and
public transport can best integrate
3. Hybrid ownership
model
Some people own and some embrace CAV pooling
CAV only lanes added to Motorways
Changes to traditional parking
Peak period demand same as now
Shared CAVs circulate waiting for next trip
Reduction in traditional public transport mode shares
As above but test impacts of different ratios of
owned:shared CAVs

19. Published model findings
• Infrastructure Victoria’s 30-year strategy (2016)
• Three broad technology options considered:
1. Autonomous cars
2. Driverless cars and ride sharing
3. Advanced traffic management
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Wilkinson, Hunkin and Richardson – Getting Proactive rather than Reactive in AV Planning
“the effect of road pricing and/or autonomous
vehicles dwarfs the effect of any one road or
public transport project option”

20. Published model findings – IV study 2016
• CAVs could significant increase:
– freeway capacity up to 60%
– freeway speeds up to 130km/h
– capacity on arterial roads up to 15%
– car trips will increase +1.1%
– people drive further VKT +11.5%
– and public transport usage declines -5% trips
• And produce a reduction in CO2 emissions -1.6%
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Wilkinson, Hunkin and Richardson – Getting Proactive rather than Reactive in AV Planning

21. Published model findings – IV study 2016
• Small changes to parameters, such as giving
everyone access to a car, produced big changes:
– increased car trips by 9% and VKT by 16%
– roads approaching significant congestion levels
– In addition to more (and longer) trips on the network CO2
emissions increased by 3%
• Performance if zero-occupant trips prevalent?
• Where are all these extra vehicles going park?
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Wilkinson, Hunkin and Richardson – Getting Proactive rather than Reactive in AV Planning

22. Published model findings – IV study 2016
• IV study suggests that infrastructure and policy
decisions are likely to shape the future success of
transport networks if (perhaps when) CAVs become
a major form of transport
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Wilkinson, Hunkin and Richardson – Getting Proactive rather than Reactive in AV Planning

23. Conclusions - analysis priorities should include:
• Identify where/how CAVs will influence travel behaviour
• Identify potential ranges of behaviour effects due to CAVs
• Develop model tests to assess anticipated behavioural changes
• Determine CAV specific behaviours (i.e. zero-occupant travel)
• Test various CAV change packages to develop model framework
• Test various CAV scenarios (by future years) for timing effects
• Performance measures compare/prioritise infrastructure needs
• Data collection and research needs to improve available tools
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Wilkinson, Hunkin and Richardson – Getting Proactive rather than Reactive in AV Planning

24. Thesis is proven!!!
Connected autonomous vehicles (CAV)
are coming and we need to start
planning the necessary infrastructure
to get ahead of the curve!!!
(or maybe just to try to catch up…)
24
Wilkinson, Hunkin and Richardson – Getting Proactive rather than Reactive in AV Planning

25. www.jacobs.com | worldwide
11 May 2017
© Copyright Jacobs
Getting Proactive rather than Reactive in AV
infrastructure planning
John Richardson, Peter Hunkin and Scott Wilkinson
AITPM Conference August 2017