1. by Alain L. Kornhauser, PhD Professor, Operations Research & Financial Engineering Director, Program in Transportation Faculty Chair, PAVE (Princeton Autonomous Vehicle Engineering) Princeton University Board Chair, Advanced TRansit Association Presented at WSTA Annual Meeting Connecting Communities; Sharing Solutions Vancouver, WA August 24, 2015 Automation in Transit: Now & In the Near Future The Business Cases

2. Outline Basic Economics of Transit Servi ce Scope of Vehicle Automation Near-Term Transit Opportunity: Automated Collision Avoidance Near-Term Transit Opportunity: Automated Collision Avoidance Revolutionary Transit Opportunity: autonomousTaxis (aTaxis) Revolutionary Transit Opportunity: autonomousTaxis (aTaxis)

3. Basic Economics of Transit Service Transit Mode Costs ($$$)

4. Basic Economics of Transit Service Transit Mode VehicleWay Costs ($$$)

5. Basic Economics of Transit Service Transit Mode VehicleWay Costs ($$$) Capital Operating

6. Basic Economics of Transit Service Transit Mode VehicleWay Costs ($$$) Capital $$ Operating $$

7. Basic Economics of Transit Service Bus Transit VehicleWay Costs ($$$) Capital $$0 Operating $$0 Interesting about Bus Transit: It isn’t Burdened to pay for a Way!

8. Basic Economics of Transit Servi ce Scope of Vehicle Automation Outline

9. 02 3 41 NHTSA Levels of Automation (None) (Driverless) (Self-Driving) (Warning) (Auto Collision Avoidance) Scope of Vehicle Automation

10. 02 3 41 Speed Dimensions of Vehicle Automation NHTSA Levels of Automation (None) (Driverless) (Self-Driving) (Warning) (Auto Collision Avoidance)

11. 02 3 41 Speed Slow (~10 mph) Moderate (~30 mph) Dimensions of Vehicle Automation NHTSA Levels of Automation (None) (Driverless) (Self-Driving) (Warning) (Auto Collision Avoidance) High (~60 mph)

12. 02 3 41 Exclusivity of the Way Speed Exclusive (Yours! but Must Pay for Way) NHTSA Levels of Automation (None) (Driverless) (Self-Driving) (Warning) (Auto Collision Avoidance) Slow Moderate (~30 mph) High (~60 mph) Scope of Vehicle Automation

13. 02 3 41 Exclusivity of the Way Speed Restricted (“Guest/Freeloader” user) Exclusive (Yours! but Must Pay for Way) NHTSA Levels of Automation (None) (Driverless) (Self-Driving) (Warning) (Auto Collision Avoidance) Slow Moderate (~30 mph) High (~60 mph) Scope of Vehicle Automation

14. 02 3 41 Exclusivity of the Way Speed Mixed (Free Way) Scope of Vehicle Automation Restricted (“Guest/Freeloader” user) Exclusive (Yours! but Must Pay for Way) NHTSA Levels of Automation (None) (Driverless) (Self-Driving) (Warning) (Auto Collision Avoidance) Slow Moderate (~30 mph) High (~60 mph)

15. Google Self-Driving Google Self-Driving Today’s Automation Bus 2.0 MB Driverless Concept Google Self-Driving Google Self-Driving CityMobil2 Elevators Transit Bus After-market ACAS After-market ACAS Morgantown PRT Paris Metro, etc. Today’s Showroom Today’s Showroom

16. Basic Economics of Transit Servi ce Scope of Vehicle Automation Near-Term Transit Opportunity: Automated Collision Avoidance Near-Term Transit Opportunity: Automated Collision Avoidance Outline

17. Google Self-Driving Google Self-Driving Near-Term Transit Opportunity: Automated Collision Avoidance Bus 2.0 MB Driverless Concept Google Self-Driving Google Self-Driving CityMobil2 Elevators Transit Bus Today’s Showroom Today’s Showroom After-market ACAS After-market ACAS Morgantown PRT Paris Metro, etc. Evolve

18. Near-Term Transit Opportunity: Automated Collision Avoidance Near-Term Transit Opportunity: Automated Collision Avoidance The Business Case Part A Driving a Bus is NOT Simple and Very Stressful Requires Continuous Diligence 2 bus drivers in NYC arrested for striking a pedestrian while simply trying to do their job Driving is one of the most dangerous occupation

22. Near-Term Transit Opportunity: Automated Collision Avoidance Near-Term Transit Opportunity: Automated Collision Avoidance The Business Case Part A Driving a Bus is NOT Simple and Very Stressful Requires Continuous Diligence 2 bus drivers in NYC arrested for striking a pedestrian while simply trying to do their job Driving is one of the most dangerous occupation They need help and ACA systems are available to help! Transit Unions & OSHA need to be demanding deployment of ACAS on all buses!

23. Bus Collisions are Expensive! Near-Term Transit Opportunity: Automated Collision Avoidance Near-Term Transit Opportunity: Automated Collision Avoidance The Business Case Part B

24. 2013 Nationwide Bus Casualty and Liability Expense Source FTA NTD Casualty and Liability Amount Vehicle- related 119 Fatalities 15,351 Injuries $499,872,628. Total Buses Commuter Bus (CB), Motor Bus (MB), Bus Rapid Transit (RB), Demand Responsive (DR) 80,795 Sub-Total Casualty and Liability Amount Per Bus $6,187/Bus/Year Near-Term Transit Opportunity: Automated Collision Avoidance Near-Term Transit Opportunity: Automated Collision Avoidance The Business Case Part B

25. Near-Term Transit Opportunity: Automated Collision Avoidance Near-Term Transit Opportunity: Automated Collision Avoidance The Business Case Part B The Trend is NOT Good!

26. In the next five days the bus transit industry will spend $6.8 million in casualty and liability expenses Bus Collisions are Expensive! Near-Term Transit Opportunity: Automated Collision Avoidance Near-Term Transit Opportunity: Automated Collision Avoidance The Business Case Part B

27. Fundamental Business Model We are at a point where: Fundamental Business Model We are at a point where: Cost of Automated Collision Avoidance Technology < Present Value {Expected Liability Savings over life of bus} Bus Collisions are Expensive! Near-Term Transit Opportunity: Automated Collision Avoidance Near-Term Transit Opportunity: Automated Collision Avoidance The Business Case Part B

28. Bus Collisions are Expensive! Near-Term Transit Opportunity: Automated Collision Avoidance Near-Term Transit Opportunity: Automated Collision Avoidance The Business Case Part B

29. Bus Collisions are Expensive! Near-Term Transit Opportunity: Automated Collision Avoidance Near-Term Transit Opportunity: Automated Collision Avoidance The Business Case Part B

30. Plus: Lives Saved, Injuries Avoided, Disruptions Averted, and Arrests not Made All for Free!!! Bus Collisions are Expensive! Near-Term Transit Opportunity: Automated Collision Avoidance Near-Term Transit Opportunity: Automated Collision Avoidance The Business Case Part B

31. Starting with the Basics Basic Economics of Transit Servi ce Scope of Vehicle Automation Near-Term Transit Opportunity: Automated Collision Avoidance Near-Term Transit Opportunity: Automated Collision Avoidance Revolutionary Transit Opportunity: autonomousTaxis (aTaxis) Revolutionary Transit Opportunity: autonomousTaxis (aTaxis)

32. Google Self-Driving Google Self-Driving Revolutionary Transit Opportunity: autonomousTaxis (aTaxis) Bus 2.0 MB Driverless Concept Google Self-Driving Google Self-Driving CityMobil2 Elevators Transit Bus Today’s Showroom Today’s Showroom After-market ACAS After-market ACAS Morgantown PRT Paris Metro, etc. Evolve

33. Today: Transit “affords” to serve only 2% of the daily trips Revolutionary Transit Opportunity: autonomousTaxis (aTaxis) Revolutionary Transit Opportunity: autonomousTaxis (aTaxis) The Business Case

34. http://www.bts.gov/pub lications/highlights_of_t he_2001_national_hous ehold_travel_survey/ht ml/figure_06.html

35. Current State of Public Transport… Not Good!: – Serves about 2% of all motorized trips – Passenger Miles (2007)*: 2.640x10 12 Passenger Car; 1.927x10 12 SUV/Light Truck; 0.052x10 12 All Transit; 0.006x10 12 Amtrak – Does a little better in “peak hour” and NYC 5% commuter trips NYC Met area contributes about half of all transit trips – Financially it’s a “train wreck” http://www.bts.gov/publications/national_transportation_statistics/2010/pdf/entire.pdfhttp://www.bts.gov/publications/national_transportation_statistics/2010/pdf/entire.pdf, Table 1-37

36. Today: Transit “affords” to serve only 2% of the daily trips Revolutionary Transit Opportunity: autonomousTaxis (aTaxis) Revolutionary Transit Opportunity: autonomousTaxis (aTaxis) The 98% of trips that don’t use Transit are trips that take place from-to and at times Transit doesn’t serve Between those places at those times there simply isn’t enough concentration of trips to effectively pay for The Business Case

37. But what if the only thing that you had to pay for was the vehicle? RevolutionaryTransit Opportunity: autonomousTaxis (aTaxis) RevolutionaryTransit Opportunity: autonomousTaxis (aTaxis) The Business Case Then Transit looks just like the car; even better, Transit looks like an Elevator Transit Mode VehicleWay Costs ($$$) Capital $$0 Operating $~0$0 No one will want to take the “Stairs” Transit evolves to serve 80% of the trips!

38. RevolutionaryTransit Opportunity: autonomousTaxis (aTaxis) RevolutionaryTransit Opportunity: autonomousTaxis (aTaxis) Implications for New Jersey’s ~32M daily trips If “NJ Transit” acquired ~1.5M aTaxis: >80% trips served @ auto-like LoS 5X Increase in NJ Rail ridership Daily aTaxi AVO > 1.5 Peak-hour, peak direction AVO ~3.0 Road congestion disappears This changes EVERYTHING! Including Quality of Life & Land Use

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

40. Bus Collisions are Expensive! Near-Term Transit Opportunity: Automated Collision Avoidance Near-Term Transit Opportunity: Automated Collision Avoidance The Business Case Part B

42. Soterea Automate Collision Avoidance

43. Near Term Opportunities

44. “Change-the world” Opportunities

46. 02 3 41 Exclusivity of the Way Speed Slow moderate high Exclusive Mixed (Shared Infrastructure) Restricted Scope of Vehicle Automation aTaxi NHTSA Levels of Automation

47. The Business Case

48. Federal Transit Administration National Transit Database for 2013 Commuter Bus (CB), Motor Bus (MB), Bus Rapid Transit (RB), Demand Responsive (DR) 119 Fatalities 15,351 Injuries Casualty & Liability expenses paid = $499,872,628 Average of $6,187 per bus

50. Liability Savings pay Cash for the Technology, and… “half” of the following come for FREE!

51. Think About… +

52. + + Enormous Extended Reach

53. Think About… + Inexpensive Guideway + Inexpensive vehicles Great way to get started

54. Think About… + + Enormous Extended Reach

55. By walking to a station/aTaxiStand – At what point does a walk distance make the aTaxi trip unattractive relative to one’s personal car? – ¼ mile ( 5 minute) max Like using an Elevator! “NJ Transit aTaxis” Service Model Elevator

56. By walking to a station/aTaxiStand – A what point does a walk distance makes the aTaxi trip unattractive relative to one’s personal car? – ¼ mile ( 5 minute) max By using the rail system for some trips – Trips with at least one trip-end within a short walk to a train station. – Trips to/from NYC or PHL Spatial Aggregation

57. By walking to a station/aTaxiStand – A what point does a walk distance makes the aTaxi trip unattractive relative to one’s personal car? – ¼ mile ( 5 minute) max By using the rail system for some trips – Trips with at least one trip end within a short walk to a train station. – Trips to/from NYC or PHL By sharing rides with others that are basically going in my direction – No trip has more than 20% circuity added to its trip time. Spatial Aggregation

58. Pixelation of New Jersey NJ State Grid Zoomed-In Grid of Mercer

59. Stands are conveniently located about ½ mile appart Stands are conveniently located about ½ mile appart xPixel = floor{108.907 * (longitude + 75.6)} yPixel = floor{138.2 * (latitude – 38.9)) xPixel = floor{108.907 * (longitude + 75.6)} yPixel = floor{138.2 * (latitude – 38.9))

60. O O D P1P1 An aTaxiTrip

61. P1P1 O Common Destination (CD) CD=1p: Pixel -> Pixel (p->p) Ride-sharing Common Destination (CD) CD=1p: Pixel -> Pixel (p->p) Ride-sharing TripMiles = L TripMiles = 2L TripMiles = 3L

62. P1P1 O PersonMiles = 3L aTaxiMiles = L AVO = PersonMiles/aTaxiMiles = 3 PersonMiles = 3L aTaxiMiles = L AVO = PersonMiles/aTaxiMiles = 3

63. NJ Transit Train Station “Consumer-shed” NJ Transit Train Station “Consumer-shed”

64. D a PersonTrip from NYC (or PHL or any Pixel containing a Train station) a PersonTrip from NYC (or PHL or any Pixel containing a Train station) NYC O Princeton Train Station NJ Transit Rail Line to NYC, next Departure aTaxiTrip An aTaxiTrip {oYpixel, oXpixel, TrainArrivalTime, dYpixel, dXpixel, Exected: dTime} An aTaxiTrip {oYpixel, oXpixel, TrainArrivalTime, dYpixel, dXpixel, Exected: dTime}

65. P2P2 P1P1 O CD= 2p: Pixel ->2Pixels Ride-sharing

66. P1P1 P3P3 O P2P2 CD= 3p: Pixel ->3Pixels Ride-sharing; P 2 New

67. Elevator Analogy of an aTaxi Stand Temporal Aggregation Departure Delay: DD = 300 Seconds Elevator Analogy of an aTaxi Stand Temporal Aggregation Departure Delay: DD = 300 Seconds Kornhauser Obrien Johnson 40 sec Henderson Lin 1:34 Popkin 3:47

68. Samuels 4:50 Henderson Lin Young 0:34 Popkin 2:17 Elevator Analogy of an aTaxi Stand 60 seconds later Elevator Analogy of an aTaxi Stand 60 seconds later Christie Maddow 4:12

69. “Last Mile” Impact on NJ Transit Rail (Today: 281,576, +537% ! )

70. Typical Daily NJ-wide AVO CD: Common Destinations; DD: Departure Delay (in Seconds) Typical Daily NJ-wide AVO CD: Common Destinations; DD: Departure Delay (in Seconds)

71. Typical Daily NJ-wide AVO CD: Common Destinations; DD: Departure Delay (in Seconds) Typical Daily NJ-wide AVO CD: Common Destinations; DD: Departure Delay (in Seconds)

72. Typical Daily NJ-wide AVO CD: Common Destinations; DD: Departure Delay (in Seconds) Typical Daily NJ-wide AVO CD: Common Destinations; DD: Departure Delay (in Seconds)

73. Typical Daily NJ-wide AVO CD: Common Destinations; DD: Departure Delay (in Seconds) Typical Daily NJ-wide AVO CD: Common Destinations; DD: Departure Delay (in Seconds)

74. Typical Daily NJ-wide AVO CD: Common Destinations; DD: Departure Delay (in Seconds) Typical Daily NJ-wide AVO CD: Common Destinations; DD: Departure Delay (in Seconds)

75. Typical Daily NJ-wide AVO CD: Common Destinations; DD: Departure Delay (in Seconds) Typical Daily NJ-wide AVO CD: Common Destinations; DD: Departure Delay (in Seconds)

76. Mercer County Pixel {200,103} Princeton ItemValue Activity Locations 57 Employment1,336 Population1,062 School Enrollment 0 Work School Home (Block Centroid ) Pixel Centroid

77. 2-pax aTaxis 15-pax aTaxis 6-pax aTaxis

78. What about the whole country?

79. Public Schools in the US

80. Nation-Wide Businesses RankState Sales VolumeNo. Businesses 1California$1,8891,579,342 2Texas$2,115999,331 3Florida$1,702895,586 4New York$1,822837,773 5Pennsylvania$2,134550,678 9New Jersey$1,919428,596 45Washington DC$1,31749,488 47Rhode Island$1,81446,503 48North Dakota$1,97844,518 49Delaware$2,10841,296 50Vermont$1,55439,230 51Wyoming$1,67935,881 13.6 Million Businesses {Name, address, Sales, #employees}

81. US_PersonTrip file will have.. 308,745,538 records – One for each person in US_Resident file Specifying 1,009,332,835 Daily Person Trips – Each characterized by a precise {oLat, oLon, oTime, dLat, dLon, Est_dTime} Will Perform Nationwide aTaxi AVO analysis Results ????

86. Manhattan (New York County) Simulated population of 1,585,873 residents 8,085,055 trips originatewithin Manhattan 52,759,156 person-trip miles for Manhattan oTrips 3,010,666 unique travelers (1,424,793 non- resident travelers – Commuters) Mean Trip Length = 6.53 miles; Median Trip Length = 3.31 miles Interesting differences between commuter and resident population traveling through Manhattan

87. Trip Files are Available If You want to Play

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

89. NHTSA Levels of Automation 1 2 3 4 5 Exclusivity of the Way Speed Slow moderate high Exclusive Mixed Restricted Scope of Vehicle Automation