Automated Vehicles: The technology that will change our mobility experience Ryan Lanyon Program Manager, Transportation Services City Toronto ACT Canada Sustainable Mobility Summit December 3, 2014

American futurist, innovator, author, and co-founder of the Global Business Network (GBN) “There will come a time when driving a car is like riding the horse. Some people will still like to do it, but most of us won’t.” – Peter Schwartz

Themes The Vehicle The Changing Trip Experience Impacts on Mobility Choices Considerations for Municipalities TDM Efforts

Levels of Automation 0. No Automation Function-specific Automation e.g. automatic transmission, cruise control Combined Function Automation e.g. automatic parking, adaptive cruise control with lane centering Limited Self-Driving Automation e.g. the driver is available, but can cede control Full Self-Driving Automation e.g. there is no human driver, nor is a passenger required Level 2 – also collision avoidance Source: US Department of Transportation, National Highway Traffic Safety Administration

Driver as a Passenger - Video is part of Volvo’s “Drive Me Project” to have 100 AVs test driving on 50km of roadway in Gothenburg, Sweden by 2017 Video modified from: https://www.youtube.com/watch?v=rMx-iGFys6s

Time Nature of work and workplace continues to evolve Will ‘telework’ now include work done in the car? Will this open the door to greater acceptance for work done on transit?

Inside the Car Note in video – adjustment of seat to switch from automated to manual driving INTERIOR Driver faces other passengers Wouldn’t it be nice to have a table? More leg room Decouple the dash - iPad EXTERIOR Wider? Higher? Placement of doors?

An Extension of the Home? How difficult will it become to convince people to leave their cars at home?

The Promise of Safety One of the biggest barriers to active transportation is perceived danger from automobiles [NEED TORONTO STATS ABOUT DRIVER BEHAVIOUR] AVs could create safer environments for pedestrians and cyclists E.g. minimum passing distance

Levels of Automation 0. No Automation Function-specific Automation e.g. cruise control Combined Function Automation e.g. adaptive cruise control with lane centering Limited Self-Driving Automation e.g. the driver is available, but can cede control Full Self-Driving Automation e.g. there is no human driver, nor is a passenger required Disruptive Source: US Department of Transportation, National Highway Traffic Safety Administration

Total Automation “Automation could be the catalyst that brings together personal mobility and public transportation,” - Sven Beiker, of the Center for Automotive Research at Stanford (CARS). Source: http://www.govtech.com/transportation/GT-Taking-Driverless-Cars-to-the-Next-Level.html Disruptions Transit, taxis, auto ownership, school buses New markets – those who could not drive Displacement of old technology and patterns Full automation leads to a fork in the road Will the future model for mobility continue to be automobile ownership, or will it migrate to transportation as a service? Or both?

Total Automation Two directions Impact on transit Continued/increased auto-ownership Customized cars for different needs Further extension of your personality Decreased auto-ownership Multiple commuting trips, shared use Automated vehicles as taxis Impact on transit Compact urban environment – virtually none Suburban low-density environment – complete overhaul

Auto Ownership Model Cost of parking at work > cost of return trip to home Car + Driver If we substitute AVs for our current fleet, then we will likely experience an increase in trips - rational decision to look at the cost of parking at work vs. marginal cost of a return trip to free parking at home Without ride-sharing, there will be no environmental benefit – more VKT Driverless Car passenger no passenger no passenger passenger

Trends in Mobility Patterns Repopulating the core Reduced interest in auto ownership Increased diversity in modal choice Increased use of sustainable modes Greater acceptance of technology Mobile technology and mobility options No more “one-size-fits-all” model Popularity of ride-sharing services like Lyft, Uber

Reduced Auto Ownership ? The real change with AVs will come with a change in auto ownership Move to ‘Transportation as a service’ model http://www.theverge.com/2014/5/28/5758734/uber-will-eventually-replace-all-its-drivers-with-self-driving-cars

Reduced Auto Ownership Elimination of sunken investment Potential models Subscription with unlimited use Membership fee with per-trip pricing based on volume Per-trip pricing Time-based pricing? Customization of the experience Vehicle Seat adjustment, environment, entertainment - We know the biggest determinant in mode choice is auto ownership we’ve seen evolving pricing models through internet-based services such as high-speed access and entertainment content Near-field communication will store and transit user preferences to the vehicle, as it adjusts to your preferred conditions

A Service for All

AVs: Other Applications Commercial operations – freight Municipal operations – transit, service vehicles (plows, waste disposal, street sweeping), emergency vehicles, automated enforcement

Challenges Social Acceptance Regulatory Acceptance Public Transit – Leave the driving to someone else Automated and Connected Vehicles – Leave the driving to something else Early adoption: Commercial and freight vehicles? Regulatory Acceptance Liability Appropriate decision-making and driving behaviour? Speed limit vs. average travel speed Will people be comfortable leaving the driving to a computer, potentially susceptible to outside override and control? UK Department for Transport to start testing social acceptability of driverless cars – among other road users like motorcyclists, cyclists, peds, horse riders

Considerations for Municipalities Engineering Traffic systems Geometry: redesign of streets; dedicated lanes? Maintenance – where are the lanes? Planning and parking requirements Interior drop-offs? Enforcement Emergency vehicles Connectivity? Policies – will we shape the application of the technology? Will we respond and adapt? What will be the role of the private sector? How much automation will depend on V2V technology instead of V2I? Dedicated lanes predicted in California in 10 years – mapping detail needed could be cause

Considerations in TDM The ‘spare time’ advantage will be reduced How to encourage carpooling in a framework where transportation is sold as a service? Importance of pricing to reduce transportation demand Per trip? Per unit of distance? Per unit of time? Peak period premiums? Class of service? E.g. SOV or carpool

Transition Period

Acknowledgments CAVCOE and Conference Board of Canada Transportation Research Board (TRB) National Association of City Transportation Officials (NACTO) Antoine Belaieff, Metrolinx Stephen Buckley & Joey Reeder, City of Toronto

Thank You Ryan Lanyon Program Manager, Transportation Services City of Toronto 416-392-3570 rlanyon@toronto.ca @ryan_lanyon