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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 3 rd longest commute time in nation 1 Average NJ commuter in traffic over 52 hrs / yr
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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 2 NJIT 2007 – Alternative Performance measures for Evaluating Congestion 3 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
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
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