1. State of the Art & Near Term Future of Smart Driving Cars by Alain L. Kornhauser, Ph.D. Professor, Operations Research & Financial Engineering Director, Program in Transportation Faculty Chair, PAVE (Princeton Autonomous Vehicle Engineering) Princeton University Presented at NJ DoT Trenton, NJ June 18, 2013

2. Where Have We Been?

3. The Automobile’s 1 st 125 Years (1886-2011) Benz patent 1886 1 st Automobile Benz patent 1886 1 st Automobile Benz Circa 2011 Delivered: Enormous Personal Freedom & Mobility But…Safe Operation Requires Continuous Vigilance

4. We Love the Freedom & Mobility But…Continuous Vigilance is an unrealistic requirement for drivers

5. Txtng while driving is out of control…

6. TravelTainment Industry Wants Everyone’sAttention

7. In In 717 out of 723 accidents ((99%) http://orfe.princeton.edu/~alaink/SmartDrivingCars/NHTSA_Hendricks2001_UnsafeDrivingActs.pdf “In 717 out of 723 crashes (99%), a driver behavioral error caused or contributed to the crash”

8. Early Estimate of Motor Vehicle Traffic Fatalities in 2012

9. Response is Laudable Kirkland, WA But… Not Likely to be Effective

10. What About Automation?

11. Preliminary Statement of Policy Concerning Automated Vehicles Extending its vehicle safety standards from Crash Mitigation to Crash Avoidance with Aim at Full Self-Driving Automation Level 0 – No-Automation. The driver is in complete and sole control of the primary vehicle controls (brake, steering, throttle, and motive power) at all times, and is solely responsible for monitoring the roadway and for safe operation of all vehicle controls. Vehicles that have certain driver support/convenience systems but do not have control authority over steering, braking, or throttle would still be considered “level 0” vehicles. Examples include systems that provide only warnings Level 1 – Function-specific Automation: Automation at this level involves one or more specific control functions; if multiple functions are automated, they operate independently from each other. The driver has overall control, and is solely responsible for safe operation, the driver. The vehicle’s automated system may assist or augment the driver in operating one of the primary controls – either steering or braking/throttle controls (but not both). Level 2 - Combined Function Automation: Automation of at least two primary control functions designed to work in unison to relieve the driver of control of those functions. Vehicles at this level of automation can utilize shared authority when the driver cedes active primary control in certain limited driving situations. The driver is still responsible for monitoring the roadway and safe operation and is expected to be available for control at all times and on short notice. Level 3 - Limited Self-Driving Automation: Vehicles at this level of automation enable the driver to cede full control of all safety-critical functions under certain traffic or environmental conditions. Level 4 - Full Self-Driving Automation: The vehicle is designed to perform all safety-critical driving functions and monitor roadway conditions for an.

12. Preliminary Statement of Policy Concerning Automated Vehicles The Aim to Full Self-Driving is Laudable; But…, Ironically, it may be overly ambitious and potentially counter productive But…, Ironically, it may be overly ambitious and potentially counter productive Eternal Vigilance should not be the price of Freedom derived from the Automobile We Like to Drive and Can Be Vigilant But… Preferably only when we want to; Otherwise, Let us “TXT” By Focusing on Level 3 (Limited Self-Driving, aka SmartDrivingCar ) NHTSA Can Capture “All” Safety Benefits & Make the Car Even More Desirable By Focusing on Level 3 (Limited Self-Driving, aka SmartDrivingCar ) NHTSA Can Capture “All” Safety Benefits & Make the Car Even More Desirable The Jump to Level 4 (Full Self-Driving) Delivers Broad Societal Benefits Equal Mobility for All (young, old, handicapped, disadvantaged), Elimination of Congestion, Halving of Energy, Pollution These are NOT NHTSA’s Mission & Shouldn’t be Distracted by that Goal

13. Where Are We Now? R&D “Level 3 Semi Self-Driving Automation ”

14. http://www.youtube.com/watch?v=cdgQpa1pUUE Has drive ~ 500,000 miles with “Level 3: Limited Self-Driving Automation” But…Hardware too expensive and Reliance on 3D Google Maps is “non-elegant”

15. Where Are We Now? “Level 4 Full Self-Driving Automation ” Operational in Exclusive Environments

16. Now exist in essentially every Major AirportMajor Airport Now exist in essentially every Major AirportMajor Airport APM Automated People Movers APM Automated People Movers Milan Beijing Paris and a growing number of Driverless Metros

17. Personal Rapid Transit: Morgantown (1975 - ) Remains a critical mobility system & expansion being planned Today… > 25M Driverless VMT Zero serious accidents > 25M Driverless VMT Zero serious accidents

18. And Today… Masdar & Heathrow are operational Video > 1M Driverless VMT Zero accidents > 1M Driverless VMT Zero accidents

19. Autonomous Buses at La Rochelle (CyberCars/Cybus/INRIA) http://www.youtube.com/watch?v=72-PlSFwP5Y Autonomous Buses at La RochelleCybus http://www.youtube.com/watch?v=72-PlSFwP5Y – Simple virtual non-exclusive roadway Virtual vehicle-based longitudinal (collision avoidance) and lateral (lane keeping) systems This is actually “Level 4 Full Self-Driving Automation” Very Slow Speed (~ 10 mph); “Limited Pedestrian Environment”

20. – Driverless Trucks in Australian & Chilean Mines http://www.youtube.com/watch?v=s0RCSX95QmE

21. Where Are We Now? Operational Bus Transit “Level 0+ No Automation, Driver Assistance ”

22. Bus 2.0: Initial Demonstration of Transit-based Driver Assistance (Level 0+, no control, only warning ) Fleet of 10 Gillig low floor buses Morning and evening express services 22 mile (one-way) travel distance Reliable travel times in all weather and traffic conditions Fleet of 10 Gillig low floor buses Morning and evening express services 22 mile (one-way) travel distance Reliable travel times in all weather and traffic conditions

23. Bus 2.0: Transit-based Driver Assistance How Do They Do It?

24. It Just Works!

25. Where Are We Now? Available in ShowRooms for Consumers “Level 2- Combined Automation wit Constant Vig1lance ”

26. Intelligent Drive (active steering ) BAS-Plus Active Lane-Keeping Assist Active Lane-Keeping Assist (braking not steering  ) Volvo Truck Emergency braking

27. DOT HS 810 767 Pre-Crash Scenario Typology for Crash Avoidance Research More on Google: Levandowski Presentation

28. With Mercedes the Market Leader in “Level 2-” and an incremental price tag that can be absorbed by a Price Leading Insurance Company, then other automakers will be enticed to follow which should lead to: Viral adoption by the car buying public “Moore’s Law type of price/performance improvement Market-driven Transition to “Level 2” and “Level 3” at same or even lower price structure Adoption and enhancement rates that are comparable to that enjoyed by airbags (With likely a comparable hick-up)

29. What’s Near-term for Transit? With Mercedes the Market Leader in “Level 2-” and an incremental price tag that can be absorbed by a Price Leading Insurance Company, then other automakers will be enticed to follow which should lead to:

30. Fact: For over 40 years New Jersey has had the World’s Best “Bus Rapid Transit” System! It Consists of: Efficient Boarding/Alighting @ Port Authority Bus Terminal – 223 Departure Gates – Readily Accommodates 700 Buses/hr The World’s Best Bus Rapid Transit System

31. Fact: For over 40 years New Jersey has had the World’s Best “Bus Rapid Transit” System! It Consists of: Efficient Boarding/Alighting @ PA Bus Terminal Direct Access/Egress to Exclusive Lanes in the Lincoln Tunnel 3+ HOV Lanes on the NJ Turnpike that are, by default, essentially bus-only Many Strategically Located Park&Ride Lots The World’s Best Bus Rapid Transit System

32. Pieces are Connected by: “495-viaduct” Counter-flow Exclusive Bus Lane (XBL) (XBL) – Lane Segregation is by Removable Plastic Peg – Yet exceedingly Safe » 3 (?) accidents in 41 years, no fatalities. The World’s Best Bus Rapid Transit System

33. A Perfect Storm Opportunity PABT in desperate need of “rehabilitation” XBL at capacity “Helix” due for “rehabilitation” Desperately need: Increased late afternoon in- bound capacity for busses New bus procurement cycle begins in 2 years Test facility available @ Ft. Monmouth

34. add Intelligent Cruise Control with Lane Assist to the 3,000 buses… e.g. Daimler Benz Distronic Plus with Traffic Jam AssistDistronic PlusTraffic Jam Assist even at an incremental $75,000/bus this is just $200M Could achieve sustained 3.0 second headways – Increases practical throughput by 50% from 700 -> 1,000 buses/hr; 35,000 -> 50,000 pax/hr – Increased passenger capacity comparable to what would have been provided by $10B ARC rail tunnel Institutionally manageable: – All Express Buses are acquired according to NJT Specs. – Facilities (XBL, LT, PABT) are controlled by PANY&NJT Ideal test facility available: – Ft. Monmouth Improving The World’s Best Bus Rapid Transit System

35. Concept Not New: Concept Makes Even More Sense Now! Improving The World’s Best Bus Rapid Transit System

36. Near-term Opportunity for a Substantive Extension of Autonomous Transit Specific: General Mobility for Fort Monmouth Redevelopment – Currently: Decommissioned Ft. Monmouth is vacant. Ft. Monmouth Economic Revitalization Authority (FMERA) is redeveloping the 3 sq. mile “city”FMERAredeveloping Focus is on attracting high-tech industry The “Fort” needs a mobility system. FMEDA is receptive to incorporating an innovative mobility system Because it is being redeveloped as a “new town” it can accommodate itself to be an ideal site for testing more advanced driverless systems.

37. Where might We End Up?

38. Most every day… Almost 9 Million NJ residents 0.25 Million of out of state commuters Make 30+ Million trips Throughout the 8,700 sq miles of NJ Where/when do they start? Where do they go? Does anyone know??? – I certainly don’t Not to sufficient precision for credible analysis

39. I’ve harvested one of the largest troves of GPS tracks – Literally billions of individual trips, – Unfortunately, they are spread throughout the western world, throughout the last decade. – Consequently, I have only a very small ad hoc sample of what happens in NJ on a typical day. I’ve Tried…

41. Motivation – Publicly available data do not contain: – Spatial precision Where are people leaving from? Where are people going? – Temporal precision At what time are they travelling? ORF 467 Fall 201241 Trip Synthesizer Project Overview

42. Why do I want to know every trip? Academic Curiosity If offered an alternative, which ones would likely “buy it” and what are the implications. More specifically: – If an alternative transport system were available, which trips would be diverted to it and what operational requirements would those trip impose on the new system? In the end… – a transport system serves individual decision makers. It’s patronage is an ensemble of individuals, – I would prefer analyzing each individual trip patronage opportunity.

43. Synthesize from publically available data: “every” NJ Traveler on a typical day NJ_Resident file – Containing appropriate demographic and spatial characteristics that reflect trip making “every” trip that each Traveler is likely to make on a typical day. NJ_PersonTrip file – Containing appropriate spatial and temporal characteristics for each trip

44. Creating the NJ_Resident file for “every” NJ Traveler on a typical day NJ_Resident file Start with Publically available data:

45. 2010 Population census @Block Level – 8,791,894 individuals distributed 118,654 Blocks. CountyPopulationCensus BlocksMedian Pop/ BlockAverage Pop/Block ATL 274,549 5,9412646 BER 905,116 11,1715881 BUR 448,734 7,0974163 CAM 513,657 7,7074767 CAP 97,265 3,6101527 CUM 156,898 2,7333457 ESS 783,969 6,82077115 GLO 288,288 4,5674063 HUD 634,266 3,031176209 HUN 128,349 2,2773156 MER 366,513 4,6115179 MID 809,858 9,8455082 MON 630,380 10,0673963 MOR 492,276 6,5434575 OCE 576,567 10,4573155 PAS 501,226 4,96665101 SAL 66,083 1,6652640 SOM 323,444 3,8365184 SUS 149,265 2,9982850 UNI 536,499 6,1396187 WAR 108,692 2,5732342 Total 8,791,894 118,654 74.1

46. Publically available data: Distributions of Demographic Characteristics – Age – Gender – Household size – Name (Last, First) Ages (varying linearly over interval):input:output: [0,49]67.5% [50,64]18.0%17.9% [65,79]12.0%12.1% [80,100]2.5% Gender:Input:Output: female51.3% Household:Size:Probability:cdf:Expectation: couple20.300.3000.6 couple + 130.080.3800.24 couple + 240.060.4400.24 couple + 350.040.4800.2 couple + 460.040.5200.24 couple + grandparent:30.010.5250.015 single woman10.160.6850.16 single mom + 120.070.7550.14 single mom + 230.050.8050.15 single mom + 340.030.8350.12 single mom + 450.030.8650.15 single man10.120.9850.12 single dad + 120.010.9900.01 single dad + 230.0050.9950.015 single dad + 340.0051.0000.02 2.42

47. Final NJ_Resident file Home County Person Index Household Index Full Name Age Gender Worker Type Index Worker Type String Home lat, lon Work or School lat,lon Work County Work or School Index NAICS code Work or School start/end time ATL 274,549 BER 905,116 BUR 448,734 CAM 513,657 CAP 97,265 CUM 156,898 ESS 783,969 GLO 288,288 HUD 634,266 HUN 128,349 MER 366,513 MID 809,858 MON 630,380 MOR 492,276 OCE 576,567 PAS 501,226 SAL 66,083 SOM 323,444 SUS 149,265 UNI 536,499 WAR 108,692 NYC 86,418 PHL 18,586 BUC 99,865 SOU 13,772 NOR 5,046 WES 6,531 ROC 32,737 Total: 9,054,849

48. Assigning a Daily Activity (Trip) Tour to Each Person

49. NJ_PersonTrip file 9,054,849 records – One for each person in NJ_Resident file Specifying 32,862,668 Daily Person Trips – Each characterized by a precise Origination, Destination and Departure Time All Trips Home County TripsTripMilesAverageTM #Miles ATL 936,585 27,723,93129.6 BER 3,075,434 40,006,14513.0 BUC 250,006 9,725,08038.9 BUR 1,525,713 37,274,68224.4 CAM 1,746,906 27,523,67915.8 CAP 333,690 11,026,87433.0 CUM 532,897 18,766,98635.2 ESS 2,663,517 29,307,43911.0 GLO 980,302 23,790,79824.3 HUD 2,153,677 18,580,5858.6 HUN 437,598 13,044,44029.8 MER 1,248,183 22,410,29718.0 MID 2,753,142 47,579,55117.3 MON 2,144,477 50,862,65123.7 MOR 1,677,161 33,746,36020.1 NOR 12,534 900,43471.8 NYC 215,915 4,131,76419.1 OCE 1,964,014 63,174,46632.2 PAS 1,704,184 22,641,20113.3 PHL 46,468 1,367,40529.4 ROC 81,740 2,163,31126.5 SAL 225,725 8,239,59336.5 SOM 1,099,927 21,799,64719.8 SOU 34,493 2,468,01671.6 SUS 508,674 16,572,79232.6 UNI 1,824,093 21,860,03112.0 WAR 371,169 13,012,48935.1 WES 16,304 477,95029.3 Total 32,862,668 590,178,59719.3

50. Overview of Data Production 1.Generate population 2.Assign work places 3.Assign schools 4.Assign tours / activity patterns 5.Assign other trips 6.Assign arrival / departure times ORF 467 Fall 201250 Project Overview

52. “Pixelated” New Jersey 2 (“1/2 mile square; 0.25mi 2 ) “Pixelated” New Jersey 2 (“1/2 mile square; 0.25mi 2 ) aTaxi Concept During peak demand aTaxis operate between aTaxiStands Autonomous vehicles wait for walk-up customers Located in “center” of each pixel (max ¼ mile walk) Departure is Delayed to facilitate ride-sharing Focus of Analysis: what is the ride-share potential? Ridesharing delivers: Congestion relief Energy savings Reduced costs/passenger Environmental sustainability

53. Intra-pixel Trips Warren County Population: 108,692

55. New Jersey Summary Data ItemValue Area (mi 2 )8,061 # of Pixels Generating at Least One O_Trip21,643 Area of Pixels (mi 2 )5,411 % of Open Space32.9% # of Pixels Generating 95% of O_Trips9,519 # of Pixels Generating 50% of O_Trips1,310 # of Intra-Pixel Trips447,102 # of O_Walk Trips1,943,803 # of All O_Trips32,862,668 Avg. All O_TripLength (miles)19.6 # of O_aTaxi Trips30,471,763 Avg. O_aTaxiTripLength (miles)20.7 Median O_aTaxiTripLength (miles)12.5 95% O_aTaxiTripLength (miles)38.0

56. Thank You alaink@princeton.edu www.SmartDrivingCar.com Discussion!

57. http://www.youtube.com/watch?v=MZ 3s_cdk_yE&feature=player_embedded http://www.youtube.com/watch?v=MZ 3s_cdk_yE&feature=player_embedded http://www.youtube.com/watch?v=0D 0ZN2tPihQ&feature=player_embedded http://www.youtube.com/watch?v=0D 0ZN2tPihQ&feature=player_embedded http://orfe.princeton.edu/~alaink/Sma rtDrivingCars/Videos/VolvoPlatooningC oncept.wmv http://orfe.princeton.edu/~alaink/Sma rtDrivingCars/Videos/VolvoPlatooningC oncept.wmv http://www.youtube.com/watch?v=rid S396W2BY&feature=player_detailpage http://www.youtube.com/watch?v=rid S396W2BY&feature=player_detailpage Assorted Videos of Self-Driving Cars http://orfe.princeton.edu/~alaink/SmartDrivingCars/Videos/1 _FrozenLakeVID_onlySteeringWoIndividualWheelBraking.mp4 http://orfe.princeton.edu/~alaink/SmartDrivingCars/Videos/1 _FrozenLakeVID_onlySteeringWoIndividualWheelBraking.mp4 http://orfe.princeton.edu/~alaink/SmartDrivingCars/Videos/2 _FrozenLakeVID_onlySteeringWoIndividualWheelBraking.mp4 http://orfe.princeton.edu/~alaink/SmartDrivingCars/Videos/2 _FrozenLakeVID_onlySteeringWoIndividualWheelBraking.mp4 http://orfe.princeton.edu/~alaink/SmartDrivingCars/Videos/3 _FrozenLakeVID_onlySteeringWoIndividualWheelBraking.mp4 http://orfe.princeton.edu/~alaink/SmartDrivingCars/Videos/3 _FrozenLakeVID_onlySteeringWoIndividualWheelBraking.mp4 http://orfe.princeton.edu/~alaink/SmartDrivingCars/Videos/4 _FrozenLakeVID_onlySteeringWoIndividualWheelBraking.mp4 http://orfe.princeton.edu/~alaink/SmartDrivingCars/Videos/4 _FrozenLakeVID_onlySteeringWoIndividualWheelBraking.mp4