Behavioral Implications of Transformative Disruptions in Transportation. Chandra R. Bhat, The University of Texas at Austin

Transcription

1 Behavioral Implications of Transformative Disruptions in Transportation Ram M. Pendyala, PhD Professor, Transportation Systems Director, TOMNET University Transportation Center School of Sustainable Engineering and the Built Environment Mobility Analytics Research Group (MARG) 2017 AZITE IMSA Spring Conference February 28 March 2, 2017; Phoenix, AZ Collaborators Chandra R. Bhat, The University of Texas at Austin Patricia Lavieri, Felipe Dias, Sebastian Astroza Tagle, Jungwoo Shin Venu Garikapati, National Renewable Energy Laboratory Daehyun You, Maricopa Association of Governments Patricia L. Mokhtarian, Georgia Institute of Technology 2 1

2 Road to the Future Mobility futures with numerous options Technology adoption in the marketplace Beyond a vehicle ownership, use, and evolution problem Survey based behavioral research studies Incorporating lifestyle considerations Key findings and results Potential Future States Source: Deloitte University Press,

3 Trip Costs in Alternative Future States Source: Deloitte University Press, Network (Capacity) Effects Reduced incidents, smaller spacing greater capacity realization 3

4 Road to the Future Mobility futures with numerous options Technology adoption in the marketplace Beyond a vehicle ownership, use, and evolution problem Survey based behavioral research studies Incorporating lifestyle considerations Key findings and results Is Pace of Technology Adoption Speeding Up? Source: pace of technology adoption is speeding up/ 8 4

5 Never Achieve 100% Market Penetration Source: Pew Research Center, Rate of Adoption Dependent on Vehicle Turnover Source: IIASA Global Energy Assessment,

6 Adoption/Ownership/Purchase of New Technologies Dependent On? 11 How Will People Embrace Technology Source: Schoettle and Sivak, UMTRI,

7 How Will People Embrace Technology Source: Schoettle and Sivak, UMTRI, How Will People Embrace Technology Source: Schoettle and Sivak, UMTRI,

8 Rapid Growth of Mobility-on-Demand Over the past ~15 years, services like Zipcar attracted about 1 million users in North America and 1.7 million users globally Within ~5 years, Uber has attracted at least 8 million users globally As of Jan 2015, 160,000 people drive for Uber worldwide As of Dec 2014, Uber served 1 million rides/day (140 million rides in 2014) 55% of US population has access to Uber (as of August 2014) 50,000 drivers added to Uber monthly (as of Dec 2014) In summer 2015, Uber served 1 million rides/day in China and 200,000 rides/day in India Uber gave 2.5 million rides in first year of operation in Austin, TX 15 But, is regulation ahead? NYC Council Proposes Bill Restricting Number of Uber, Other For-Hire Cars (6/24/15, WCBS) De Blasio Administration Dropping Plan for Uber Cap, for now (7/22/15; New York Times) Source: FutureAdvisor,

9 Road to the Future Mobility futures with numerous options Technology adoption in the marketplace Beyond a vehicle ownership, use, and evolution problem Survey based behavioral research studies Incorporating lifestyle considerations Key enhancements to transport models Vehicle Ownership and Use Modeling Problem Model vehicle ownership and fleet composition considering... Technology options/bundles and costs On-demand mobility services and costs Willingness to share? Identify relevant vehicle types and modal alternatives for choice set Technology continues to evolve, and hence challenging to identify alternatives and their attributes Integration of vehicle fleet composition, usage, and evolution model system to capture technology penetration time frames Will personal vehicle ownership become a relic of the past? 18 9

10 Moving Beyond Vehicle Ownership How Will Emerging Technologies Impact VMT? Pros May replace a drive-alone trip with Uber + transit, or other combo (solves transit s first- and last-mile problem) May eliminate a personallyowned car (separately good), reducing unnecessary trips Neutral May replace a kiss-and-ride or PNR trip Or replace some other drivealone trip Cons May displace a transit trip (not only increasing VMT, but undermining transit) May replace one carpool trip with multiple single-rider AV trips Makes travel easier, cheaper may generate new trips Time saved (e.g., for parents using Shuddle for their children) may be used to generate new trips On-demand vehicles generate VMT by cruising, deadheading 19 Road to the Future Mobility futures with numerous options Technology adoption in the marketplace Beyond a vehicle ownership, use, and evolution problem Survey based behavioral research studies Incorporating lifestyle considerations Key enhancements to transport models 10

11 A Consumer Adoption Modeling Framework Emerging Vehicular Technologies New technologies that make the vehicle smarter Intelligent navigation and safety systems, fuel options, communications devices, and multimedia platforms Definition of a smart vehicle Connected Infotainment system Autonomous 11

12 Survey Research Stated preference survey research to understand consumer preferences for emerging vehicular technology Conjoint Analysis helps identify desirable features for a new product and appropriate price level Extensively employed in marketing science and transportation research Stated Preference Survey Stated Choice of Vehicle and Technology Options Please choose the alternatives that you would purchase (multiple choices are allowed). Based on your current annual usage of vehicles, please allocate the usage among your selected alternatives. Attributes Vehicle 1 Vehicle 2 Vehicle 3 Vehicle 4 1. Fuel Type Electric Gasoline Hybrid Diesel 2. Fuel Cost (Won/km) Vehicle 3. Purchase Price (10,000 won) Attributes 4. Maintenance cost (10,000 won/year) Accessibility of Fueling Station (%) 80% 100% 100% 80% 1 Willingness to purchase 2 Allocate the car usage per year km km km km 12

13 Stated Preference Survey Choice of Vehicle and Technology Options Please choose the most preferred alternative (single choice). Smart Option Attributes 1 The most preferred alternative Attributes Vehicle 1 Vehicle 2 Vehicle 3 Vehicle 4 1. Option Price (10,000 won) Connectivity Possible Possible Not Possible Not Possible 3. Voice Command Possible Not Possible Not Possible Not Possible 4. Autonomous Driving Control Speed Control Speed Control Speed Control Speed + Lane Keeping 5. Wireless Internet Provided Not Provided Provided Not Provided 6. Application Not Provided Provided Not Provided Not Provided Survey Sample Survey completed during March-May 2012 by a sample of 675 respondents in six metropolitan cities of South Korea Seoul, Busan, Daegu, Incheon, Gwangiu, and Daejeon Adopted quota sampling method (considering age and gender) After extensive data cleaning, validation checks, and filtering, final data set included 633 respondents 13

14 Modeling Methodology Vehicle choice is a multiple discrete choice problem because multiple alternatives may be chosen Also consider additional utility derived from usage (continuous aspect) of the chosen alternatives Account for the presence of correlated unobserved factors across utilities of different choice alternatives Choice of smart vehicle option is a single discrete choice problem Relax the restrictive IIA assumption associated with traditional multinomial logit model Account for heterogeneity in consumer preferences Vehicle Type Choice Model Baseline Preferences and Satiation Parameters 14

15 Consumer Preferences for Advanced Vehicular Technologies 29 Willingness-to-Pay for Smart Vehicle Options Attribute Parameter Parameter Marginal Willingness Mean Std Dev to Pay (MWTP) Option price Connectivity USD 1,420 Voice command USD 532 Lane keeping USD Wireless internet USD 1,508 Smart Applications USD

16 Road to the Future Mobility futures with numerous options Technology adoption in the marketplace Beyond a vehicle ownership, use, and evolution problem Survey based behavioral research studies Incorporating lifestyle considerations Key enhancements to transport models Ownership and Sharing of Autonomous Vehicle Technologies Autonomous vehicle (AV) era is rapidly approaching Growing interest in modeling consumer preferences for adoption and use of autonomous vehicles Puget Sound Regional travel survey data for analyzing potential adoption of self-driving vehicles Future AV use likely impacted by history of vehicle ownership and usage, socio-economic attributes, and mobility options Lavieri, P.S., V.M. Garikapati, C.R. Bhat, R.M. Pendyala, S. Astroza, and F.F. Dias (2016/2017) Modeling Individual Preferences for Ownership and Sharing of Autonomous Vehicle Technologies. Department of Civil, Architectural, and Environmental Engineering, The University of Texas at Austin, Austin, TX

17 Modeling Framework Green Lifestyle Technology Savviness Travel Behavior & Choices Use of Car-sharing Use of Ride-sourcing Vehicle Ownership and Use Home/Work Location Future Travel Demand Autonomous Vehicle Usage 1) Share 2) Own 3) Both 4) None Socio-economic and demographic characteristics 33 Ownership and Sharing of Autonomous Vehicle Technologies Two lifestyle factors, namely, green lifestyle (GL), and technology savviness (TS) included in the models 34 17

18 Impacts of Technology Use on Activity-Travel Choices Technology has become ubiquitous part of human existence Smartphones and apps facilitate more flexible and dynamic scheduling of activities Analyzed impacts of smartphone ownership and use on activity travel choices Use of multiple modes of transport Tour complexity Recreational tours Tour accompaniment Astroza, S., V.M. Garikapati, C.R. Bhat, R.M. Pendyala, P. Lavieri, and F.F. Dias (2016/2017) Analysis of the Impact of Technology Use on Multi-Modality and Activity-Travel Characteristics. Department of Civil, Architectural, and Environmental Engineering, The University of Texas at Austin, Austin, TX. 35 Modeling Framework Smartphone Ownership Sociodemographics Multimodality Trip Chaining Lifestyle Factors Intensity of Use of Websites Green Lifestyle Tech Savviness Intensity of Use of Smartphone Apps Recreatn Tours Tour Accomp 18

19 Impact of Technology Use on Activity-travel Choices 37 Road to the Future Mobility futures with numerous options Technology adoption in the marketplace Beyond a vehicle ownership, use, and evolution problem Survey based behavioral research studies Incorporating lifestyle considerations Key enhancements to transport models 19

20 Key Transport Model Enhancements Vehicle type choice model Identify vehicle used for specific tour/trip Vehicle tracking algorithm Trace path and availability of each vehicle in time-space continuum Agent-based mesoscopic and microscopic simulation models to track vehicles and travelers through time and space Account for empty VMT Disruptive technologies could be game-changer for activity generation significant induced demand Similar to impact of aviation on long distance travel demand Key Transport Model Enhancements Choice set definition Vehicle alternatives and their attributes Modal options and their attributes Features, attributes, and options affect market penetration rates Enhanced on-demand taxi travel model to account for emerging mobility services Current taxi trip models are extremely rudimentary Consider all disruptive options/forces/technologies together in a holistic manner TNCs experiencing rapid growth and significant utilization Far greater than CV/AV technologies! 20

21 Some Modeling Issues Recent attempts at modeling AV impacts Increase lane capacity Reduce coefficient on travel time variable Reduce auto operating cost Include SOV as a mode option for zero-car households No parking constraints/costs Fun exercises to test sensitivity of models to changes in model parameters, assumptions, and coefficients But need greatly enhanced model paradigms to address complex primary, secondary, and tertiary impacts Not modeling land use impacts (longer term location choices) In the End, Traveler Still Makes Choices Infrastructure use largely driven by user (departure time choice, origin-destination travel patterns, trip chaining) Fundamental tenets of activity-travel demand modeling not necessarily invalid due to emerging technologies Need to understand Choice options and attributes on the supply side Lifestyle factors and behavioral response process on the demand side Integrate consideration of secondary and tertiary impacts (e.g., empty VMT) 21

22 Thank You! 43 22