PROJECT DESCRIPTION& GOALSThe Trip Demand Synthesis Process and the aTaxi + Rail Transit Mobility ConceptsBy

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 20052 NJIT 2007 – Alternative Performance measures for Evaluating Congestion3 Ibid.4 Ibid.

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