Universal Design, Technology, and Transportation Systems

1. Universal Design, Technology, and Transportation Systems Aaron Steinfeld Robotics Institute, Carnegie Mellon University Rehabilitation Engineering Research Center on Accessible Public Transportation (RERC-APT) Co-Director Quality of Life Technologies Engineering Research Center (QoLT ERC) Lead, Safe Driving QoLT Systems Accessing the Future 2009

2. Cast of Many

3. Accessible Transportation is Critical • Employment, independence, & social engagement • More than half a million people with disabilities cannot leave their homes because of transportation difficulties [1] • One-third of people with disabilities have inadequate access to transportation [2] • 46% of people with disabilities, compared to 23% of people without disabilities, reported feeling isolated from their communities [3] • Lack of transportation (29%) was only second to a lack of appropriate jobs being available (53%), as the most frequently cited reason for being discouraged from looking for work [4] • 1-month delay in nursing home admissions could save $1.12 B annually (US) [5] [1] Bureau of Transportation Statistics, U.S. Department of Transportation [2] N.O.D. Harris Survey of Americans with Disabilities [3] N.O.D. Harris Survey of Community Participation [4] Loprest & Maag, 2001 [5] Johnson, Davis, & Bosanquet, 2000

4. Apply IT advances in methods and technology to transportationFocus on need & capability, not diagnosis

5. Core Principles for Affecting Change • Technology, as appropriate for end users • Leverage existing advances in Intelligent Transportation Systems (ITS) • End user input early and often • Universal Design • Primary: Any older or disabled user • Secondary: Any user who could benefit from the technology • Successful examples: • Real-time arrival data from automated vehicle location (AVL) • VPG MV-1

6. Transit Status Quo • Funding, relationships, & complexity • Size and complexity of transit systems • Consistent funding challenges • Difficult to foster collaborative consumer participation • Paratransit is very expensive • More integration of accessibility into mainline components needed

7. Transit: Travel Chain Use IT at the system level: best practices, accountability, etc

8. Citizen Science(Paolos, 2008) • Rich media evidence for large-scale impact • End user data collection • Personal value/interest • Opt-in • Stationary works well • Citizen weather stations • Mobile now possible • Air pollution • Access barriers www.neighborhood-networks.net www.zexe.net/GENEVE/map.php

9. Collaboration is Attainable • ParkScan.org • Users provide pros & cons • In 2007 alone: • 425 registered users • 1,531 observations • 68% of contributed issues were addressed by the City • City is an active participant

10. Transit

11. Making it Useful • Part I: Citizen science website • Part II: Mobile, tailored, real-time information access • Universal design features • Open Services (e.g., BART) • Database Backend • Machine Learning • Human-Computer Interaction

12. Personal Vehicles Status Quo • Reactive, infrequent, & incomplete • Driving assessment: Doctor screening via interviews and surveys, simulation/simulated driving assessments • May not detect changes rapidly, occur infrequently • By and large, discount importance of vehicle and environment familiarity • Only ~400 Driver rehabilitation specialists (CDRS) in the US • Vehicle changes are not cheap or easy to implement • Hand controls (with training) start at $2k • Conversion vans for wheelchairs start at $20k and rise quickly

13. Intervene above an extreme threshold (intervene before crash) Compress the distribution instead (reduce tailgating habits) Driving: Increasing Safety Safe Unsafe Frequency Risk Knipling, et al 2004

14. Behavior & Decisions are Personal • Attempting to alter driver-specific outcomes through IT • Research shows there are many different driving styles • E.g., following behaviors: hunter, flow conformist, etc • Familiarity with own vehicle • Controls • Vehicle dynamics • Vehicle size • Familiarity with where typically drive • Intersection handling • Visual distractions • Road type comfort/compensation • Limited cognitive demand for navigation

15. Safe Driving Projects • DriveCap: Low-cost aftermarket system that can measure capability on common denominator driving tasks in a wide range of vehicles • DriveCap Advisor: Extend DriveCap to provide acceptable driver advice • DriveCap Navigator: In-vehicle navigation that learns and supports robust application of rules related to driver capability and vehicle limits • Vehicle Transformation: Basic research that enables safer driving through key design and vehicle control improvements • Vehicle Enhancement: Basic development that enables safer driving through semi-autonomous vehicle control • Policy, payment, acceptance, and related issues throughout

16. Use technology from autonomous vehicle research Augment & supplement capabilities of CDRS Appropriate: “Trusted advisor” Universal Design: Focus on driver capability, not diagnosis Driver Capability Assessment Autonomous vehicles (1990’s - present)

17. What Does the Data Look Like? Aggressiveness Time Gap to Leading Vehicle (sec) Turn Rate Increases in tailgating and taking both wide and sharp turns faster

18. Privacy: Context by Recipient Data collected QoLT P&S team

19. Thank You Funding provided by the U.S. Dept. of Education, National Institute on Disability and Rehabilitation Research, grant number H133E080019. Project Website:http://www.rercapt.org Part of this work is based on work supported by the National Science Foundation under Grant No. EEEC-540865. Project Website:http://www.qolt.org Robotics Institute School of Computer Science Carnegie Mellon University Email: steinfeld@cmu.edu