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UWE Autonomous Vehicle Research and Implications for Future Mobility Management SUSCOM Meeting Dartington Conference Room, 19 May 2016 Graham Parkhurst [email protected] Professor of Sustainable Mobility Centre for Transport & Society Department of Geography and Environmental Management
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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
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Consortium
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Large business
SME
Local government
Catapult
Charity
Academia
With support from
Home
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EnsurethatfutureCAVprovisionmeetsspecificmobilityneeds
improvingqualityoflife
Enableolderadultstocon=nuetobeac=vecontributorstothe
economyandsociety
MakeaccesstoCAVsarealitybydesigningHMIsaddressingageing-relatedimpairments
DevelopclearguidelinesandframeworksformobilityserviceprovidersandCAVmanufactures
Imagesource:www.riverside.org.uk
Customer Needs & Experience: Empowering People
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User Models and Metrics
Adaptable HMI Interface
User Needs Framework and Library of Tests
Customer Needs & Experience: Innovation Through Application
Stern (2014) CUBI Model
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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/
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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
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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
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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
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“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/
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“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/
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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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