PROJECT DESCRIPTION
& GOALS
The Trip Demand Synthesis Process and the
aTaxi + Rail Transit Mobility Concepts
By
Julia Phillips
Hill Wyrough
The Need for Change
• New Jersey has 3rd longest commute time in nation1
• Average NJ commuter in traffic over 52 hrs/yr
• Average cost of NJ traffic is $8.3 billion – equivalent to
$1,465 per licensed NJ driver
• Total of $345 million in fuel wasted in congestion per
annum
1
US Census Bureau 2005
NJIT 2007 – Alternative Performance measures for Evaluating Congestion
3 Ibid.
4 Ibid.
2
Potential within aTransportation
• Reduce congestion through ridesharing and greater
utilization of existing NJT railway infrastructure
• Reduce fuel consumption and spending, minimize
environmental impact
• Improve highway safety by removing human error
• Create a mode of transportation superior in efficiency,
comfort, and availability to existing modes
aTaxi System
• Autonomous Transit as a subgroup of Personal Rapid
Transit
• No new infrastructure
• Both spatially and temporally specific
• Preexisting technology
• Ability to meet existing demand currently met by
automobile industry as well as demand of those presently
lacking access to personal transportation
Goal of ORF467 aTaxi Project
• To assess the potential for ridesharing in New Jersey as
comprehensively as possible
• Increase accuracy of data extrapolated by trip generator
through continued collection of real data
• Bulid upon Fall 2012’s findings regarding improved
efficiency with relaxation of constraints to:
• Destination pixel size (CD – common destination)
• Wait times (DD – departure delays)
Fall 2013 Advancements
• Substantially improved employment and patronage data
by:
• Correcting data for major employers
• Using patronage data and total sales numbers to more accurately
produce employee data
• Time of day data
• Factored in NJ Railway Transit
• Multimodal trips
• Intrastate rail trips
Trip Generation
• Step 1: Identify population (Age/Gender/Class of Worker)
• Generate number of residents per location
• Uniform sampling of ages by range
• Assign “traveler types”
• Produce income data
# people,
Lat, Long
Trip Generation
• Step 2: Assign place of work
• Assign a county > industry > employer per traveler of “work” type
Trip Generation
• Step 3: Assign schools
• Check person’s age/education level/enrollment
• Assign to Private (~15%) and Public (~84%) schools
• Dormitory students attend closest University
Trip Generation
• Step 4: Assign activity patterns
• Each resident follows a specific type of tour
• Tours can consist of between 0 and 7 arcs between Home, Work, School,
Other
• 17 Patterns
• Type determined by specific demographic data
• Averages out to 3.5-4.5 daily trips per person
Tour Types
Assumptions
• Residents located at centroid of census blocks
• Uniform distribution within age intervals
• All tours begin and end at home
Pixelation of New Jersey
• Convert New Jersey into a grid system of 0.50mi x 0.50mi
pixels
• Convert longitude and latitude as follows:
Pixelation of New Jersey
NJ State Gride
Zoomed-In Grid of Mercer
Pixelation of New Jersey
• Locate an aTaxi stand at the center of each pixel in NJ
• Any trip to within the pixel can be reasonably assumed to be served
by nearest aTaxi stand
• All trips within New Jersey can then be converted to trips from
aTaxi stand to aTaxi stand
Deep South Jersey oTrips
Deep South Jersey oTrips
South Jersey oTrips
South Jersey oTrips
Jersey Shore oTrips
Jersey Shore oTrips
Route 18 Corridor oTrips
Route 18 Corridor oTrips
Route 206 Corridor oTrips
Route 206 Corridor oTrips
North Western New Jersey oTrips
North Western New Jersey oTrips
North New Jersey oTrips
North New Jersey oTrips
North East New Jersey oTrips
North East New Jersey oTrips
Out of State oTrips
Out of State oTrips
Trip Type Distributions for NJ
Distribution of oaTaxiTrips: Hunterdon
Distribution of oaTaxiTrips: Atlantic
Distribution of oaTaxiTrips: Salem
Distribution of oaTaxiTrips: Sussex
Distribution of oaTaxiTrips: Warren
Distribution of oaTaxiTrips: Bergen
Distribution of oaTaxiTrips: Cape May
Distribution of oaTaxiTrips: Cumberland
Distribution of oaTaxiTrips: Essex
Distribution of oaTaxiTrips: Mercer
Distribution of oaTaxiTrips: Hudson
Mode Split Model
• 3 modes
• Walking/Bicycling
• NJ Transit railway
• aTaxis
• Walking/Bicycling
• Intrazonal
• oPixel adjacent to dPixel
• Train
• All trips to/from NYC or Philadelphia
• Trips originating or ending near train stations
• Can be combined with aTaxi and/or walking
Mode Split Model
NJ Transit Rail Lines
Congested Roadways
NJDOT Statewide Capital Investment Strategy FY2008
Geographic Distribution of oTrainTrips
Geographic Distribution of ShortTrips
Geographic Distribution of oaTaxiTrips
Breakdown of Trip Types