Requirements for AMD Modeling A Behavioral Perspective

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1 Requirements for AMD Modeling A Behavioral Perspective Venu Garikapati National Renewable Energy Laboratory May 18, 2017 Princeton SmartDrivingCars Summit

2 What is an Automated Mobility District (AMD) An AMD is a campus-sized implementation of the connected/automated vehicle technology to realize the full benefits of a fully electric automated mobility service within a confined region on district. AMD

3 Characteristics of an AMD Fully automated and driverless cars Service constrained to a dense area Mix of on-demand and fixed route services Multi-modal access within/at the perimeter What are early use-case implementations for AMDs?

4 Boundary Application Contexts Residential Communities University Campuses Business Campuses Military Bases Others AMD Impact Perspectives Larger Metropolitan Area Boundary AMD Inter-area Intra Boundary Intra- Districts Impacts Mobility & energy of AMD fleet Land use changes Inter-Regional Impacts Modal choice Route choice Activity choice Boundary Issues / Effects Mode transfer / parking Boundary services TNCs, car sharing / rental

5 Application Context: University Submodel Developed for Mid-regional Council of Governments in Albuquerque, New Mexico ~900,000 individuals from 337,771 households University of New Mexico and Central New Mexico Community College 42,000 students and 18,000 faculty staff Separate submodel developed to account for travel patterns of university population Submodel has its own trip generation, location choice, and mode choice components (informed by a university travel survey) Interacts with the regional travel demand model

6 University Submodel: Highlights 1 Model components classified by Affiliation (student, faculty, staff); Living arrangement (on/off campus) 2 3 Separate treatment of intra-campus and non-intra-campus travel A parking infrastructure measure is built into the mode choice model to reflect the impact of parking on mode shares University Parking Attraction Factor Capacity per Capita Generalized Cost of Parking on Campus

7 Understanding the Adoption of AVs Are We Here Yet?

8 Understanding the Ownership and Sharing of Autonomous Vehicle (AV) Technologies Growing interest in modeling consumer preferences for adoption and use of autonomous vehicles Identifying AV adoption rates and ownership models critical in modeling AMDs Future AV use likely impacted by history of vehicle ownership and usage, socio-economic attributes, and mobility options Impacts of AVs on VMT and energy consumption?

9 Understanding the Ownership and Sharing of Autonomous Vehicle Technologies Two lifestyle factors, namely, green lifestyle (GL), and technology savviness (TS) included in the models developed

10 Modeling Requirements for AMDs Trip Frequency Impact of AMDs on travel patterns of individuals (increase/decrease) Location Choice Mode Choice Separate treatment for intra- and inter-district travel Accurately depicting the boundary transfers Impact on vehicle ownership Incorporation of an on-demand shuttle service mode At a Minimum! Traffic Assignment Accurately simulating automated vehicles Capturing interaction among different modes Evaluating and monitoring mobility and energy/emission

11 Network Modeling Requirements for AMDs Legend Extremely Important Important Not Important Model Type Road network Transit Pedestrians Parking Signals Other needs Traditional 4 step model ? CAVs-private ? TNC(Uber/Lyft) ? SAVs/aTaxi ? PRT ? The ideal model ? Other AMD options?????

12 Existing Tools to Model AMDs Tool Emerging Mobility Simulation Capabilities Trip-Based demand Activity- Based demand Multi-Modal Capability Resolution Open source VISSIM CAV, MaaS Yes Yes Yes Microscopic No SUMO CAV, Automated Shuttle Yes Yes Yes Microscopic Yes; C++ POLARIS CAV, MaaS No Yes Yes Mesoscopic Yes; C++, Python MATSim SAV, ataxi No Yes Yes Microscopic Yes; Java QRS II NA Yes No Yes Macroscopic No MassMotion NA NA NA No, only pedestrian AIMSUN NA Yes No Yes Microscopic Microscopic/ mesoscopic TRANSIMS NA No Yes Yes Microscopic Yes; C++ No No

13 Where we are AMD Modeling Where we want to be Existing tools primarily emphasize on The road network, with minimal to no consideration for ped/bike/transit Privately owned vehicles, but do not model shared economies Limited capabilities to model AMDs Models built from traditional travel surveys Any others Need modeling tools that Consider the interaction between different modal alternatives Capture private as well as shared economies in vehicles Model the impact of AMDs on travel behavior Are built from field deployments of emerging transportation tech Can quantify the energy and emission benefits Any others

14 Bridj Is Dead, But Microtransit Isn't Someone will find a way to make these hybrid ridehailing/bus services work. --The Atlantic May 3, 2017

15 Thanks!

16 University Parking Attraction Factor (UPAF) Parking attraction factor is derived for UNM/CNM UPAF Capacity per Capita Generalized Cost of Parking on Campus The generalized parking cost is a composite factor that considers Average cost of parking in a lot (per day) Distance of the lot from the central UNM zone (UNM main campus zone) Capacity of the lot

17 Modeling Framework Present Choices Future Intention Based on Current Interest Green Lifestyle Tech Savviness Use of Car-sharing Use of Ride-sourcing Vehicle Ownership Household Location Interest in AV: 1) Sharing 2) Owning 3) Both 4) None Socio-demographics

18 User Preferences for Car-sharing and Ride-sourcing Services With the advent of Transportation Network Companies (TNCs), ownership of vehicles might become relic of past Pay by the minute or pay by trip Possible benefits include reduced need for parking infrastructure Potential impacts on daily-activity and long distance travel patterns? Similar in theory to mobility benefits from AMDs

19 User Preferences for Car-sharing and Ride-sourcing Services Greater proclivity to use ride-sourcing and car-sharing services Young (18-34 years) Well-educated (bachelor's degree or higher) Employed (Full/Part-time) Individuals who are single and own a smartphone Less proclivity to use ride-sourcing and car-sharing services Older age (55 years or above) Presence of children in the household Households who currently own multiple vehicles Individuals who do not own a smart phone

20 Directions for Future Research Models and frameworks informed from a full scale implementation of AMDs Need to answer questions/assumptions pertaining to AMDs Adoption rates Impacts on travel behavior and energy consumption Operational attributes (frequency, fleet, and ridership) Standard set of metrics that serve as a benchmark to design and deploy AMDs Study hub and spoke development of a network of AMDs

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