Maximizing Airport Land Values: A Concept and Daily Person Trips in New Jersey: A Synthesis

1. Alain L. Kornhauser Professor,Operations Research & Financial Engineering Director, Transportation Research Program Princeton University Presented at ATRA Technix Conference, Univ. of Maryland, CATT January 21, 2012 Maximizing Airport Land Values: A ConceptandDaily Person Trips in New Jersey:A Synthesis

2. Alain L. Kornhauser Professor,Operations Research & Financial Engineering Director, Transportation Research Program Princeton University Presented at ATRA Technix Conference, Univ. of Maryland, CATT January 21, 2012 Maximizing Airport Land Values: A Concept

3. The Obvious: Airports are • important city and regional elements • not origins nor destinations • haven’t been good neighbors • have environmental and safety issues • noise, emissions, operational reliability • Consequently, airports • are required to have/own substantial land buffers • tend to be sited substantially far from customer’s ultimate origins and destinations • This makes then only intra- and inter- modal transfer points

4. Becoming a Good Neighbor • Environmental and safety issues are being addressed • Substantial noise and emissions reduction • Safety and operations substantially improved • Consequently: • Cities can move towards airports and airports can move towards cities leading to concepts such as; • Airport cities and Aerotropolis(John Kasarda, UNC) • What about better utilization of the airport lands themselves?

5. Fundamentals of Airport Economics • Airports are landlords to individual business • Airlines • Landing fees • Passenger & freight terminals • Maintenance facilities • Concessions • Traveler services • Arrival & Transfer (inside security) • Arrival & Departure (inside terminal, outside security) • Access • Individual Parking • Rental car companies • Taxi, Limos and shuttle bus companies • Support services • Hotel for in-transit passengers and airline crews

6. Improving Existing Airport Economics • Get more out of Airlines (little upside potential) • Landing fees • Passenger & freight terminals • Maintenance facilities • Improve Concessions • Major investment in enhanced Traveler services • Inside security: (travel is a captive customer) • APMs enable faster transfer between terminals, providing more time for traveler to be a captive customer. • Arrival & Departure (inside terminal, outside security) • Little opportunity here. • Access • Individual Parking: (generates less than $2/ft2/mo = €15/m2/mo very low rent opportunity) • Rental car companies; (even with low rent, moved off airport) • Taxi, Limos and shuttle bus companies; (little upside potential) • Support services • Hotel for airline crews and in-transit passengers (not much upside)

7. New Sources of Income • Focus on making the Airport a destination • Create destination-quality land uses on the excess land • Make those land uses readily accessible from the terminal without getting a car. • I’ll need a critical mass of entertainment, business activities all tightly coupled with a flexible transport system. • Many locations needing door-to-door connectivity • More travelers • More landing fees, terminals, • Spend more on the property

8. Las Vegas (LAS), 2011

9. 7/1/50

10. 5/1/65

11. 6/12/75

12. Las Vegas (LAS), 2008 R=1.5 km

13. Las Vegas (LAS), 2011

14. A Little Wider View

15. Alain L. Kornhauser Professor,Operations Research & Financial Engineering Director, Transportation Research Program Princeton University Presented at Technix Conference, Univ. of Maryland, CATT January 21, 2012 Daily Person Trips in New Jersey:A Synthesis

16. Alain L. Kornhauser Professor,Operations Research & Financial Engineering Director, Transportation Research Program Princeton University Presented at Technix Conference, Univ. of Maryland, CATT January 21, 2012 Daily Person Trips in New Jersey:A Synthesis

17. 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

18. I’ve Tried… • 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.

19. 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.

21. Synthesize from publically available data: • “every” NJ Traveler on a typical day NJ_Residentfile • 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

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

23. 2010 Population census @Block Level • 8,791,894 individuals distributed 118,654 Blocks.

24. Bergen County @ Block Level

25. Publically available data: • Distributions of Demographic Characteristics • Age • Gender • Household size • Name (Last, First)

26. Beginnings of NJ_Residentfile County Task 1 2010 Census # People, Lat, Lon, For each person Vital Stats RandomDraw: Age, M/F, WorkerType,

27. Home County Using Census Journey-to-Work (J2W) Tabulations to assign Employer County Task 2 C2C Journey2Work Work County WorkCounty Destination RandomDraw: Journey2Work http://www.census.gov/population/www/cen2000/commuting/files/2KRESCO_NJ.xls http://www.census.gov/population/www/cen2000/commuting/files/2KWRKCO_NJ.xls

28. Using Employer Data to assign a Workplace Characteristics Employment-Weighted Random Draw

29. Using School Data to Assign School Characteristics

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

31. 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

32. Creating the NJ_PersonTrip file • “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 • Start with • NJ_ResidentTrip file • NJ_Employment file • Readily assign trips between Home and Work/School • Trip Activity -> Stop Sequence • Home, Work, School characteristics synthesized in NJ_Resident file

33. Assigning “Other” Locations 1. Select Other County Using: Attractiveness-Weighted Random Draw Attractiveness (i)= (Patrons (I)/AllPatrons)/{D(i,j)2 + D(j,k)2}; Where i is destination county; j is current county; k is home county 2. Select “Other” Business using: Patronage-Weighted Random Draw within selected county

34. Assigning Trip Departure Times Task 8 Trip Type; SIC Distribution of Arrival/Departure Times Time Generator: RandomDraw: Time Distribution Trip Departure time (SeconsFromMidnight) • For: H->W; H->School; W->Other • Work backwards from Desired Arrival Time using • Distance and normally distributed Speed distribution, and • Non-symmetric early late probabilities • Else, Use Stop Duration with non-symmetric early late probabilities based on SIC Cod

35. NJ_PersonTrip file • 9,054,849 records • One for each person in NJ_Resident file • Specifying 30,564,528 Daily Person Trips • Each characterized by a precise • Origination, Destination and Departure Time