Fast Forwarding to a World of On-Demand Air Transportation

Similar documents
The following slideshow and talk were presented at the Uber Elevate Summit on April 25 th, The text included here is an approximate transcript

Mike Hirschberg, Executive Director AHS International The Vertical Flight Technical Society

Key Drivers for evtol Design Christopher Silva From VTOL to evtol Workshop May 24, 2018

Mike Hirschberg, Executive Director AHS International The Vertical Flight Technical Society Uber graphic, April 2017

NASA Revolutionary Vertical Lift Technology Project Research Susan A. Gorton, Project Manager Aircraft Noise and Emission Symposium February 27, 2018

The Skycar 400 High-speed, 4-passenger VTOL aircraft

Urban Air Mobility - Trends & Challenges. Dr. Jochen Kaiser Head of Visionary Aircraft Concepts

Modelling Shared Mobility in City Planning How Transport Planning Software Needs to Change ptvgroup.com

Propulsion Controls and Diagnostics Research at NASA GRC Status Report

Integrated Systems Architecture & Stability/Control Considerations in Early Vehicle Design

First Civilian Tiltrotor Takes Flight

High aspect ratio for high endurance. Mechanical simplicity. Low empty weight. STOVL or STOL capability. And for the propulsion system:

On-Demand Mobility. Aviation s Path to High Speed Regional Mobility

Electric VTOL Aircraft

Prototyping Collision Avoidance for suas

Jay Carter, Founder & CEO CAFE Electric Aircraft Symposium July 23 rd, 2017

Designing evtol for the Mission NDARC NASA Design and Analysis of Rotorcraft. Wayne Johnson From VTOL to evtol Workshop May 24, 2018

Inventory Routing for Bike Sharing Systems

Skip the Traffic: Fly Your Car A User s Perspective

A Vehicle Design and Optimization Model for On-Demand Aviation

Clean Sky 2. LifeCraft Demonstrationt (IADP RC 2 & ITDs) Consultation meetings Brussels th December 2012 OUTLINE

The role of rail in a transport system to limit the impact of global warming

FLYING CAR NANODEGREE SYLLABUS

AT-10 Electric/HF Hybrid VTOL UAS

To those immersed in the world of traditional helicopters,

Opportunistic Energy Sharing Between Power Grid and Electric Vehicles: A Game Theory-based Nonlinear Pricing Policy

Evolution of Rotary Wing Technology, Enhanced Capabilities for Humanitarian Operations

IPRO 317-VTOL Aircraft for the Masses

Air Buzz. 32nd Annual AHS International Student Design Competition

The Electric VTOL Revolution

Hybrid VTOL: Increased Energy Density for Increased Payload and Endurance

CarterCopters. Cleaner Greener. Safer. Your affordable environmentally-friendly VTOL technology Carter Aviation Technologies, LLC

3. What is the total fuel capacity with normal tanks? Usable? 4. What is the total fuel capacity with long range tanks? Usable?

National Routing Number Administration p-ani Activity and Projected Exhaust Report

I!"#$%&'"#(')$*+($+$,+-.(/"-$0-!&-00#$

Focused acceleration: a strategic approach to climate action in cities FEBEG ENERGY EVENT, BRUSSELS, JUNE 27, 2018

Development of an Unmanned Aircraft Mounted Software Defined Ground Penetrating Radar

w w w. o n e r a. f r

The Future of. Vertical Mobility

AN ADVANCED COUNTER-ROTATING DISK WING AIRCRAFT CONCEPT Program Update. Presented to NIAC By Carl Grant November 9th, 1999

ARCHIVED REPORT. For data and forecasts on current programs please visit or call

Skycar Flight Control System Overview By Bruce Calkins August 14, 2012

A complete hybrid VTOL autopilot solution. Start anywhere, fly everywhere.

Fédération Aéronautique Internationale

DEPARTMENT OF TRANSPORTATION FEDERAL AVIATION ADMINISTRATION TYPE CERTIFICATE DATA SHEET NO. A11EA

ParkNet: Drive-by Sensing of Road-side Parking Statistics

Disruptive Technology and Mobility Change

Kamakshi Duvvuru Uber Case Study & Feature Proposal. Research:

Design and Development of Hover bike

AIRLINE TRANSPORT PILOTS LICENSE ( FLIGHT PERFORMANCE AND PLANNING)

AUTONOMOUS TRANSPORT. Investment Opportunity Brief

RFC Dallas, Inc. AIRCRAFT QUESTIONNAIRE (9/25/2016) "A Safe Pilot Knows His Equipment"

AIRCRAFT FAMILIARIZATION. Some questions may not apply to the aircraft you are flying.

Future of Mobility: A view of the DfT s direction of travel

How the V-22 Osprey Works

AIRCRAFT INSPECTION REPORT. For CESSNA 172 RG

FAA Part 27 Rotorcraft Safety Continuum for Systems & Equipment

NASA LEAPTech and X-57 Prototyping

Leading the way to seamless mobility November th, 2017 Tampa, Florida

ELECTRIC BICYCLE A Green Alternative to Urban Commuting

Park Smart. Parking Solution for Smart Cities

Traffic Management through C-ITS and Automation: a perspective from the U.S.

MAV and UAV Research at Rochester Institute of Technology. Rochester Institute of Technology

LONG-TERM TRANSPORTATION ELECTRICITY USE CONSIDERING AUTONOMOUS VEHICLES: ESTIMATES & POLICY OBSERVATIONS

Pioneering electric aviation Lessons learned and vision of the future

IN-FLIGHT CHECK LIST B-17 Technical Session for Flight Engineers 11/18/2017 (with REVISION)

UTA Transportation Equity Study and Staff Analysis. Board Workshop January 6, 2018

Preface. Acknowledgments. List of Tables. Nomenclature: organizations. Nomenclature: acronyms. Nomenclature: main symbols. Nomenclature: Greek symbols

Employing Opportunistic Charging for Electric Taxicabs to Reduce Idle Time

Aero Engine Round Table, 30 May

MD - RA. Minister s Delegates - Recreational Aviation Représentants du Ministre - Aviation de Loisir Service d Inspection

CAVOK Aviation Training Ltd. Cessna C177

aviation week A New Approach To VTOL Page 36 Secure Collaboration On The Internet THE FIGHT OVER F-22 & SPACE TECHNOLOGY Page 53 Page 44

Lip wing Lift at zero speed

4 COSTS AND OPERATIONS

Innovations and Energy Implications from Connected/Automated Vehicles and New Mobility Technologies

Small UAV A French MoD perspective and planning

International Journal of Scientific & Engineering Research, Volume 4, Issue 7, July ISSN BY B.MADHAN KUMAR

Shu Ting Goh, Research Fellow, ECE, NUS S. A. (Reza) Zekavat, Professor, ECE, MTU (Visiting Prof. WPI)

ACAS X Next Generation Collision Avoidance

A FLYING EJECTION SEAT. By R. H. Hollrock* and J. J. Barzda* ABSTRACT

German Ultralight VTOL Innovations. By Ian Frain. Ultra Coaxial Development

An Innovative Approach

China Intelligent Connected Vehicle Technology Roadmap 1

ELECTRIC POWER TRAINS THE KEY ENABLER FOR CONTRA ROTATING PROPELLERS IN GENERAL AVIATION (& VICE VERSA)

An Overview of High Speed Rail. David Randall Peterman Congressional Research Service

TCDS NUMBER E00078NE U.S. DEPARTMENT OF TRANSPORTATION REVISION: 3 DATE: April 12, 2011

Forget self-driving cars. A CMU spinoff is helping to make self-piloted, flying taxis.

Route-Based Energy Management for PHEVs: A Simulation Framework for Large-Scale Evaluation

for Unmanned Aircraft

suas in CAP Delaware Wing HQ, Civil Air Patrol Development of small Unmanned Aerial Systems

TYPE CERTIFICATE DATA SHEET

Zero-Emission Long-Haul Trucking Technologies

Stop Sign Gap Assistance At Rural Expressway Intersections

ICAO/UN-Habitat Pilot Project on Synergy between Airports and Urban Development for Sustainable Development Experts Group Meeting

A New Type of Rotor + Airbag Hybrid Unmanned Aerial Vehicle

Weight & Balance. Let s Wait & Balance. Chapter Sixteen. Page P1. Excessive Weight and Structural Damage. Center of Gravity

Evaluating the impact of feedstock quality on delivered cost: Two case studies from the US Southeast region

Friday, 27 June Realizing a small UAV for medical transport in developing countries Master thesis: Ferdinand Peters. Dr.One

Climate change challenge

Transcription:

Fast Forwarding to a World of On-Demand Air Transportation Smart Urban Transportation Forum IMA University of Minnesota May 15, 2017 Jon Petersen Head of Data Science, Advanced Programs Uber Technologies

dynamic pricing spatio-temporal forecasting dispatch Rich problems revenue management driver positioning latent demand modeling uberpool stochastic routing anomaly detection ubereats map matching many more

Uber Elevate

Noise Speed Efficiency Emissions Safety (thus cost)

Over a dozen VTOL companies developing prototypes to deploy within the next three years Volocopter Lilium Zee.Aero Ehang Joby Aviation A^3/Airbus

Distributed Electric Propulsion + Fixed Wing Very quiet compared with combustion engines, Many rotors -> lower tip speed Inherently safer: Redundancy is tolerant of failures, partial autonomy 2X safer than driving Emissions: Electric has zero operational emissions 10x more efficient: 3-4x improvement from tiltrotor, 3x improvement in fixed wing

Vehicle Designs multicopter autogyro helicopter co-axial helicopter compound helicopter lift + cruise vectored thrust tilt duct tilt wing tilt rotor en-route cruise speed [mph] 50 100 100 150 150 150 150 150 150 150 lift/drag 1.5 3.5 4.25 5.5 9 10 10 10 12 14 disc-loading [lbs/ft 2 ] 3.75 3.75 4.5 7 4.5 15 40 40 15 15 efficient cruise FOM 0.60 0.75 0.75 0.75 0.75 0.60 0.50 0.60 0.65 0.65 efficient takeoff & landing empty weight/ gross weight 0.55 0.50 0.55 0.60 0.65 0.65 0.65 0.65 0.65 0.65 en-route energy [kwh/mile] 6.07 2.6 2.14 1.65 1.01 0.91 0.91 0.91 0.76 0.65

Flux Optimizer Beyond the Vehicle Where to build infrastructure? What are the network dynamics? What does a good network need?

Flux Optimizer Under the Hood 1. Estimate Demand 2. Generate Candidate Hubs 3. Hub Optimization 4. VTOL Route Optimization

Flux Optimizer Under the Hood 1. Estimate Demand 2. Generate Candidate Hubs 3. Hub Optimization k-means clustering on trip points 4. VTOL Route Optimization centroids define candidate hubs also supports hubs defined by the user

Flux Optimizer Under the Hood GOAL maximize time savings of all riders 1. Estimate Demand 2. Generate Candidate Hubs 3. Hub Optimization An itinerary (o,d,i,j) is valid if the time saved s(o,d,i,j) exceeds some threshold s*: 2 s(o, d, i, j) = x(o, d) {z } ground time s x(o, d) 4 (o, i)+ (L)+ (i, j)++ (U)+ (j, d) 5 {z } VTOL time 3 4. VTOL Route Optimization

Flux Optimizer Under the Hood GIVEN all eligible VTOL itineraries set of candidate hubs H user inputs 1. Estimate Demand Optimize subset of hubs H* to maximize coverage 2. Generate Candidate Hubs 3. Hub Optimization 4. VTOL Route Optimization

Flux Optimizer Under the Hood 1. Estimate Demand GIVEN optimal hub placements trips DECIDE sequence of flight legs assign riders to VTOLs when/where/how much to recharge when/where to deadhead when to depart (savings vs. load) 2. Generate Candidate Hubs 3. Hub Optimization 4. VTOL Route Optimization

Hub Optimization

DFW Hub Optimization

DFW Rolling Out Infrastructure 1, 2 Rider Coverage = 15.2% + 3, 4, 5 + 6, 7, 8, 9, 10 Rider Coverage = 42.2% Rider Coverage = 47.3%

Dubai Hub Optimization 2 Hubs 5 Hubs 10 Hubs 50 Hubs 23% 52% 69% 86% % Trip Coverage

Minneapolis/St. Paul Hub Optimization

VTOL Route Optimization

VTOL Routing Model Multicommodity Network Flow Model

VTOL Routing Model ground arcs (battery charging) Better modeling approach: identify path P that is a minimum cover valid for (v,p) then lift following arcs following the final arc in P

ASSUMPTIONS DALLAS, TX # OF HUB 5 AIRSPACE SEP.! 2 mi INPUT evtol COUNT [% CAPACITY] 20 25 30 35 40-100 SEAT COUNT 1 2 3 4 5 6 MINIMUM GROUND TIME [min] 2 3 4 5 6 OUTPUT evtol RANGE 20-120 mi EN-ROUTE SPEED [mph] 50 100 150 170 200 ASCEND 75 sec DECEND 45 sec RECHARGE MINUTES [20-90%] 15 20 25 30 TRIP VOLUME [1.0 = reference] 0.3 0.7 1.0 1.3 1.7 MIN SAVINGS THRESHOLD [%] 30 35 40 45 50 55 MIN VTOL RANGE [m] 10 20

ASSUMPTIONS DALLAS, TX # OF HUB 5 AIRSPACE SEP.! 2 mi INPUT evtol COUNT [% CAPACITY] 20 25 30 SEAT COUNT 1 2 3 4 5 MINIMUM GROUND TIME [min] 2 3 4 5 6 35 6 40-100 OUTPUT evtol RANGE 20-120 mi EN-ROUTE SPEED [mph] 50 100 150 170 200 ASCEND 75 sec DECEND 45 sec RECHARGE MINUTES [20-90%] 15 20 25 30 TRIP VOLUME [1.0 = reference] 0.3 0.7 1.0 1.3 1.7 MIN SAVINGS THRESHOLD [%] 30 35 40 45 50 55 MIN VTOL RANGE [m] 10 20

ASSUMPTIONS DALLAS, TX # OF HUB 5 AIRSPACE SEP.! 2 mi INPUT evtol COUNT [% CAPACITY] 20 25 SEAT COUNT 1 30 35 2 3 4 5 6 MINIMUM GROUND TIME [min] 2 3 4 5 6 40-100 Demand may be met using OUTPUT evtol RANGE 20-120 mi ~ 40% of vehicle capacity EN-ROUTE SPEED [mph] 50 100 150 170 200 ASCEND 75 sec RECHARGE MINUTES [20-90%] Load factor 15 20 25 30 DECEND ~ 1.55 per flight 45 sec TRIP VOLUME [1.0 = reference] 0.3 0.7 1.0 1.3 1.7 MIN SAVINGS THRESHOLD [%] 30 35 40 45 50 55 MIN VTOL RANGE [m] 10 20

ASSUMPTIONS DALLAS, TX # OF HUB 5 AIRSPACE SEP.! 2 mi INPUT evtol COUNT [% CAPACITY] 20 25 30 SEAT COUNT 1 2 3 4 5 MINIMUM GROUND TIME [min] 2 3 4 5 6 35 6 40-100 OUTPUT evtol RANGE 20-120 mi EN-ROUTE SPEED [mph] 50 100 150 170 200 ASCEND 75 sec DECEND 45 sec RECHARGE MINUTES [20-90%] 15 20 25 30 TRIP VOLUME [1.0 = reference] 0.3 0.7 1.0 1.3 1.7 MIN SAVINGS THRESHOLD [%] 30 35 40 45 50 55 MIN VTOL RANGE [m] 10 20

ASSUMPTIONS DALLAS, TX # OF HUB 5 AIRSPACE SEP.! 2 mi INPUT evtol COUNT [% CAPACITY] 20 25 30 SEAT COUNT 1 2 3 4 5 6 40-100 MINIMUMM GROUND TIME [min] 2 3 4 5 6 35 most sharing of VTOLs is attained with 3 seats routes with highest load factors Frisco DFW Downtown Dallas OU UT TPUT evtol RANGE 20-120 mi EN-ROUTE SPEED [mph] 50 100 150 170 200 ASCEND 75 sec DECEND 45 sec RECHARGE MINUTES [20-90%] 15 20 25 30 TRIP VOLUME [1.0 = reference] 0.3 0.7 1.0 1.3 1.7 MIN 10 VTOL RANGE [m] 20 MIN VTOL RANGE [m] 10 20

ASSUMPTIONS DALLAS, TX # OF HUB 5 AIRSPACE SEP.! 2 mi INPUT evtol COUNT [% CAPACITY] 20 25 30 SEAT COUNT 1 2 3 4 5 MINIMUM GROUND TIME [min] 2 3 4 5 6 35 6 40-100 OUTPUT evtol RANGE 20-120 mi EN-ROUTE SPEED [mph] 50 100 150 170 200 ASCEND 75 sec DECEND 45 sec RECHARGE MINUTES [20-90%] 15 20 25 30 TRIP VOLUME [1.0 = reference] 0.3 0.7 1.0 1.3 1.7 MIN SAVINGS THRESHOLD [%] 30 35 40 45 50 55 MIN VTOL RANGE [m] 10 20

e V TO L CO UNT [ % CA PA CI T Y ] 20 25 30 35 40-100 + North Denton # O F HUB S E AT CO UNT 5 1 2 34 5 6 AIRSPACE S E P. MI NI MUM G RO UND T I ME [m i n ] 5 min MGT! 2 mi evtol RA NGE 20-120 mi 3 min MGT 2 3 4 5 6 E N-RO UT E S P E E D [ mp h ] 50 100 150 170 200 ASCEN D 75 sec RE CHA RG E MI NUT E S [ 2 0-9 0 % ] 15 20 25 30 DEC END 45 sec T RI P V O L UME [ 1. 0 = re f e re n c e ] 0.3 0.7 1.0 1.3 1.7 MI N V TO L RA NG E [ m] 10 20 MI N V TO L RA NG E [ m] 10 20 OUTPUT - Las Colinas INPUT ASSUMPTIONS DAL LA S, T X

ASSUMPTIONS DALLAS, TX # OF HUB 5 AIRSPACE SEP.! 2 mi INPUT evtol COUNT [% CAPACITY] 20 25 30 SEAT COUNT 1 2 3 4 5 MINIMUM GROUND TIME [min] 2 3 4 5 6 35 6 40-100 OUTPUT evtol RANGE 20-120 mi EN-ROUTE SPEED [mph] 50 100 150 170 200 ASCEND 75 sec DECEND 45 sec RECHARGE MINUTES [20-90%] 15 20 25 30 TRIP VOLUME [1.0 = reference] 0.3 0.7 1.0 1.3 1.7 MIN SAVINGS THRESHOLD [%] 30 35 40 45 50 55 MIN VTOL RANGE [m] 10 20

1705 mph cruise AIRSPACE S E P.! 2 mi evtol RA NGE 20-120 mi e V TO L CO UNT [ % CA PA CI T Y ] 20 25 30 35 40-100 S E AT CO UNT 1 2 34 5 6 200 mph cruise MI NI MUM G RO UND T I ME [m i n ] 2 3 4 5 6 E N-RO UT E S P E E D [m p h ] 50 100 150 170 200 ASCEN D 75 sec RE CHA RG E MI NUT E S [ 2 0-9 0 % ] 15 20 25 30 DEC END 45 sec T RI P V O L UME [ 1. 0 = re f e re n c e ] 0.3 0.7 1.0 1.3 1.7 MI N V TO L RA NG E [ m] 10 20 MI N V TO L RA NG E [ m] 10 20 OUTPUT # O F HUB INPUT ASSUMPTIONS DAL LA S, T X

ASSUMPTIONS DALLAS, TX # OF HUB 5 AIRSPACE SEP.! 2 mi INPUT evtol COUNT [% CAPACITY] 20 25 30 SEAT COUNT 1 2 3 4 5 MINIMUM GROUND TIME [min] 2 3 4 5 6 35 6 40-100 OUTPUT evtol RANGE 20-120 mi EN-ROUTE SPEED [mph] 50 100 150 170 200 ASCEND 75 sec RECHARGE MINUTES [20-90%] 15 20 25 30 DECEND 45 sec TRIP VOLUME [1.0 = reference] 0.3 0.7 1.0 1.3 1.7 MIN SAVINGS THRESHOLD [%] 30 35 40 45 50 55 MIN VTOL RANGE [m] 10 20

ASSUMPTIONS DALLAS, TX # OF HUB 5 AIRSPACE ACE SEP.! 2 mi NPUT I evtol COUNT [% CAPACITY] 20 25 SEAT COUNT 1 2 3 4 5 6 MINIMUM GROUND TIME [min] 2 3 4 5 6 30 35 Charging only at mega vertiports 40-100 OUTPUT RIDERS SERVED - 4.0% TIME SAVED + 0.0% evtol RANGE 20-1200 mi ASCEND 75 sec DECENDD 45 sec EN-ROUTE SPEED [mph] 50 100 150 170 200 RECHARGE MINUTES [20-90%] 15 20 25 30 TRIP VOLUME [1.0 = reference] 0.3 0.7 1.0 1.3 1.7 MIN VTOL RANGE [m] 10 20 z BATTERY CHARGE AT LANDING -17% evtol UTILIZATION - 2.3% DEADHEADS PER evtol +0.5% MIN SAVINGS THRESHOLD [m] MIN VTOL RANGE [m] 10 20 LOAD FACTOR +1.5%

ASSUMPTIONS DALLAS, TX # OF HUB 5 AIRSPACE SEP.! 2 mi INPUT evtol COUNT [% CAPACITY] 20 25 30 SEAT COUNT 1 2 3 4 5 MINIMUM GROUND TIME [min] 2 3 4 5 6 35 6 40-100 OUTPUT evtol RANGE 20-120 mi EN-ROUTE SPEED [mph] 50 100 150 170 200 ASCEND 75 sec RECHARGE MINUTES [20-90%] 15 20 25 30 DECEND 45 sec TRIP VOLUME [1.0 = reference] 0.3 0.7 1.0 1.3 1.7 MIN SAVINGS THRESHOLD [%] 30 35 40 45 50 55 MIN VTOL RANGE [m] 10 20

ASSUMPTIONS DALLAS, TX # OF HUB 5 AIRSPACE SEP.! 2 mi INPUT evtol COUNT [% CAPACITY] 20 25 30 SEAT COUNT 1 2 3 4 5 MINIMUM GROUND TIME [min] 2 3 4 5 6 35 6 40-100 OUTPUT evtol RANGE 20-120 mi EN-ROUTE SPEED [mph] 50 100 150 170 200 ASCEND 75 sec RECHARGE MINUTES [20-90%] 15 20 25 30 DECEND 45 sec TRIP VOLUME [1.0 = reference] 0.3 0.7 1.0 1.3 1.7 MIN SAVINGS THRESHOLD [%] 30 35 40 45 50 55 MIN VTOL RANGE [m] 10 20

ASSUMPTIONS DUBAI, UAE # OF HUB 5 AIRSPACE SEP.! 2 mi INPUT evtol COUNT [% CAPACITY] 20 25 30 SEAT COUNT 1 2 3 4 5 MINIMUM GROUND TIME [min] 2 3 4 5 6 35 6 40-100 OUTPUT evtol RANGE 10-120 mi EN-ROUTE SPEED [mph] 50 100 150 170 200 ASCEND 75 sec RECHARGE MINUTES [20-90%] 15 20 25 30 DECEND 45 sec TRIP VOLUME [1.0 = reference] 0.3 0.7 1.0 1.3 1.7 MIN SAVINGS THRESHOLD [%] 30 35 40 45 50 55 MIN VTOL RANGE [m] 10 20

DUBAI, UAE # VTOLs Rider Capacity Minimum Ground Time Cruise Speed Trip Volume (Rider Savings) Min Rider Savings

What if pick-up times were longer? Simulate ETAs +10%, +25%, +50%

Ongoing & Future Work Incorporating stochasticity vehicle design (speed, battery consumption) VTOL travel times latent demand Air Traffic Management Flight planning for noise abatement Unmanned Aircraft Systems Traffic Management (UTM) Irregular Operations Marketplace Optimization: Pricing, Dispatch, Pooling

Thanks! Questions? more about Uber Elevate: www.uber.com/info/elevate/ Uber Elevate summit videos: www.uber.com/info/elevate/summit/ Questions, comments: petersen@uber.com