uwe autonomous vehicle research and implications for ... 19 05 16... · uwe autonomous vehicle...

UWE Autonomous Vehicle Research and Implications for Future Mobility Management SUSCOM Meeting Dartington Conference Room, 19 May 2016 Graham Parkhurst graham.parkhurst@uwe.ac.uk Professor of Sustainable Mobility Centre for Transport & Society Department of Geography and Environmental Management

Overview

•  Brief introduction of Venturer + Overview of Flourish

•  A bit more detail on Social/Behavioural Research within Venturer

•  Implications for Mobility Management

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Driverless Cars on UK Roads

Consortium

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Large business

SME

Local government

Catapult

Charity

Academia

With support from

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EnsurethatfutureCAVprovisionmeetsspecificmobilityneeds

improvingqualityoflife

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economyandsociety

MakeaccesstoCAVsarealitybydesigningHMIsaddressingageing-relatedimpairments

DevelopclearguidelinesandframeworksformobilityserviceprovidersandCAVmanufactures

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Customer Needs & Experience: Empowering People

User Models and Metrics

Adaptable HMI Interface

User Needs Framework and Library of Tests

Customer Needs & Experience: Innovation Through Application

Stern (2014) CUBI Model

Venturer social and behavioural research:

1.  expectations/acceptance of the AV concept and market opportunities

2.  Handover from AV to human driver in the urban context

3.  Interactions on urban roads between AVs and other road users

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Expectations/Acceptance of AVs •  Literature review •  Stakeholder interviews •  Online survey and debates •  ‘Pod’ perception experiments

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Acceptance: summary findings •  Awareness high

– Schoettle and Sivak (2014) 2/3rds in US/UK/AU •  Opinion survey findings inconsistent and

variable – Vary by country, driver status, gender, personality –  Influenced by question framing –  ‘Driver experience’, control, security strongest

negatives – Safety and full automation strongest positives

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Expectations: summary findings •  Howard & Dai (2014) ‘multi-tasking’ and not

having to park as positives •  Schoettle & Sivak (2014) 41% expected to

‘watch the road’ (8.3% would read) •  Casley (2013) fuel efficiency, shorter journey

times, environmental credentials more important than productive use of travel time

•  Wide range of estimates of willingness to pay – One outlier study indicated a $30k premium, but

several others only around $1-3k more 10/

Handover •  Literature Review •  Simulator Experiments •  AV Experiments

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Merat et al. (2014): at 70mph, 35-40 secs to

achieve stabilised lateral control of vehicle even if

planned

STISIM Simulator

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Williams Evoque simulator

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BAE Systems Bowler Wildcat

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Interactions on the public highway

•  Literature Review •  Focus groups •  Experiments into passenger and non-user

acceptance of AV decisions

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5.3 Interactions on the public highway: AV+ HDV @ Junction

•  Are there important differences between AV and human driver behaviour at T-junctions and roundabouts that have implications for safety/roads design/driver training? – AV interaction with human-driven vehicle in

different scenarios: simulator then campus roads

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5.3 Interactions on the public highway: Other combinations (scenarios under development)

•  E.g. acceptance of AV passing distance of cyclists by AV passengers and cyclists?

•  E.g. AV gap acceptance waiting to pass stationary vehicle e.g. bus of AV passengers?

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Highway code to become an operating manual?

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AVs – natural users of shared space or technologically challenged?

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Is this a dream scenario?

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Publicised benefits

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The Pathway to Driverless Cars: A detailed review of regulations for automated vehicle technologies

But AVs will have a long transition

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Level 5 might just be starting by 2030 according to KPMG!

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Non-Connected Connected Highly automated Fully automated

“Incremental Substitution” Scenario

•  ‘Pods’ in limited niches e.g. city centres –  new transport mode/option

•  Gradual development and exploitation of road-going car technology –  current ownership and use model continues

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Possible outcomes •  car ownership and traffic increase

–  L4/L5 AV empty running?

•  public transport use, car occupancy fall •  Increased mobility for those with restrictions on

driving capabilities (if able to afford an AV) –  But social exclusion of those without car access?

•  Worse urban living conditions –  More vehicles parked –  Limited decongestion/emissions benefits of AVs offset

•  Public health threat of reduced active travel? •  Pressure for regulation of other road users? 25/

“Collective Efficiency” Scenario

•  Higher L3 capital cost favours collective ownership of vehicles

•  L4 link vehicles further favour collectivity –  ‘driver experience’ no longer a factor in ownership –  Immediate availability achieved through summoning rather

than own car –  Removal of owner-driver vs guest-passenger distinction

encourages collective use •  Fleets (commercial, public, third-sector) offer a range

of automated mobility services –  Differentiated by price and service attributes

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Possible outcomes •  Efficient ridership + collective ownership minimise vkm

–  Absolute fall in traffic possible –  Emissions benefits maximised by smoother, lighter traffic

•  Parking at origins/destinations largely eliminated –  Accessibility of city centres favoured –  Residential streets decluttered

•  Social inclusion enhanced by more flexible ‘public’ transport e.g. in low density areas –  Accessibility and perhaps mobility increased

•  Concerns about levels of active travel remain –  But walking and cycling for part of journeys more possible

with collective ownership 27/

Implications for mobility managers •  Parking

–  In the long run demand might fall –  In the short run may increase – Pod systems enable relocation of parking? – Automated parking more space efficient

•  Car use: Much depends on adoption scenario •  Public transport use

– Labour costs (60%) largely eliminated? – Early adopter niche? – Many more smaller vehicles to manage on sites?

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Implications (cont.) •  Walking and cycling

– Might lose users to AV public transport fleets? – Will AVs need more segregated, less shared

space? •  Implications for labour market

– Fewer driving jobs? – More AV technician jobs?

•  What new infrastructure required? – Who will pay for it?

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