Bergen County

IntroductionBergen is the most populous county in New Jersey, boasting a population of 895,250.

With 234 square miles of inhabitable land, Bergen County has an average population density of 3826 people per square mile. It is part of the New York Metropolitan area and thus the transportation system serves as a vital system for people commuting to New York. Population is densest towards the lower portion of Bergen Bounty as shown below in Figure 1. From http://www.city-data.com/county/Bergen_County-NJ.html, we can see that Bergen County has a population that is rather evenly distributed in terms of age and sex, with a slight tendency towards younger age. However, its workforce is mainly office workers due to its proximity to NY. There are approximately 22000 students attending school and 14000 students attending college. The average income of tax payers was $90000.

Figure 1

Interestingly enough, 73% of the people in Bergen County currently use private vehicles with no carpooling to commute to work and only 17% use public transportation. For more information on public systems see http://orfe.princeton.edu/~alaink/Papers/ORF%20467F08PRTSystem.pdf. Bergen County has a wide diversity of various attractions and points of interest, ranging from schools to offices to heavy commercial areas.

Initial NetworkWe decided to place the initial networks in the two areas of denser population. Namely,

the lower left and lower right of the county. Since the practicality of a system is important to its use, we focused on creating enough stations in the local area to be usable.

The tracks usually followed existing roads and sometimes went over forests and water. One route conveniently leads to the densely populated region of Passaic County. Roads were not followed 100% of the time because the PRT seeks to create close locations not linked by roads closer in terms of travel time. Thus, it is convenient to have it transverse over water and forests.

Construction EvolutionIn the second stage, we will try to add networks and link the two bottom networks in

the west and east. This will also cover the paths leading to the airport and Giants stadium increasing revenue significantly. Thus, stage three will consist of saturating the bottom half of the county, as well as extending the top half. The fourth state will complete the process and expand the networks to profitable positions in the top half of the county. In addition, it is important to note that due to the block system used, as saturation increases, efficiency also increases as interconnectivity increases within the network since the cost of extending a connection between two blocks is subsidized by the building of a station on that connection.

Stage two coverage area

Stage three coverage area

Final Network

*Note pictures do not contain guide ways and shape points due to network issues leading to loss of data.

The final network spans the entire county and covers 80% of the trips in the county. In total there are 612 stations, 607 interchanges, and 526.04 miles of track. However, the miles of track should be closer to 600 miles of track because of the lack of shape points in the second model. With a $3 fare, this network is expected to make $2 billion net profit a year. However, this number is grossly inflated as the original Bergen County data was inflated. The total number of trip ends has been reduced by about 10 million from last year. This network

produces a higher profit than last year’s due to higher efficiency. The tools this year allowed for the users to see the coverage area and achieve a more efficient coverage of the county.

Below are some assumptions we took in determining our ridership and profit. We assumed that peak hour trips are 15% of total trips. In addition, the fleet size was 11% of peak hour trips. These assumptions are, however, rather generous considering land prices in Bergen County.

Networks Statistics; County Bergen

Stations

Interchanges

Miles of

Guideway

Length

Total Trip ends

served Total TripsPeak hour

TripsFleet size

Average trip

Length

Average Vehicle

Occupancy Fare

Vehicle Operating Costs

(#) (#) (miles) (per day) (per day) (per day) (#)(Miles)

(Trips/vehicle)

612 607 526.04 13,402,769

4,261,660

639,249 70317 5 2

$ 3.00 $ 0.20

In addition, it is to be noted that due to the low population density in the northern region, the city-gird-like design of the network could not be implemented. Instead, a series of vertical parallel lines were used to reach isolated, populous networks in the north. The parallel paths were connected with each other and the isolated networks in the northern region were also linked. However, the minimal path between stations there is still relatively far compared to the air-distance.

Below is a distribution of trip ends served by stations for the final network.

1 25 49 73 97 1211451691932172412652893133373613854094334574815055295530

20000

40000

60000

80000

100000

Trip ends served per stationBergen County

Highest to lowest

Trip

Edn

s ser

ved

per d

ay

*Note, this information was not provided for initial and developing networks as due to a technical error, the network data was lost. In addition pictures of the network with interchanges and links were also not available due to the same reason.

There are a few values that are exceptionally high in terms of station trip ends served because multiple stations could not be inserted due to unavailability of space. However, as one can see, it is still rather acceptable as the average station density is 21,000 trip ends per day. In addition, only a few stations contribute to the high average. Perhaps it is possible to make those selected stations larger.

1 33 65 97 1291611932252572893213533854174494815135455776090

0.001

0.002

0.003

0.004

0.005

0.006

0.007

0.008

Density Distribution of TripsSorted from Largest to Smallest

1 31 61 91 1211511812112412713013313613914214514815115415716010

0.2

0.4

0.6

0.8

1

1.2

Cumulative Density Distribution of Trips

Sorted from Largest to Smallest

Coverage Analysis

Below is a table of the various types of trips and the network’s service coverage of those trips. As seen, the coverage is fairly decent for all trips except for home trips. This is mainly due to the low density of residential areas. This makes it cost inefficient to set stations and cover those areas.

Trip Ends Served

home school work shop transp. entert. dinning Total

Total 2,193,260

453,044

1,657,101

8,109,491

86,440

2,378

901,055

13,288,150

County

Total Trip Ends

3,536,472

535,084

1,948,686

9,623,340

91,222

2,828

1,069,260

16,806,892

Trips served (per day) 4,153,256

Percentage 62% 85% 85% 84% 95% 84% 84% 79%

Financial Analysis

As shown below, our break-even price was $1.30 fare. This is mainly due to the high population density in Bergen County. Realistically, the break-even fare would be around $1.70 because the current model lacks shape points. Thus, the guide ways would be longer.

0.899999999999999

0.999999999999999 1.1 1.2 1.3 1.4 1.5 1.6 1.7 1.8 1.9 2 2.1 2.2 2.3 2.4 2.5 2.6 2.7 2.8 2.9 3

$(1,000.00)

$(500.00)

$-

$500.00

$1,000.00

$1,500.00

$2,000.00

$2,500.00

Fares and Profit

Graph of projected fares and profits.

The most costly elements in the capital costs are the vehicles. If we assumed that the network was constructed all at once, it would require, at a 3% interest rate, it would require less than 6 years to pay off. (See spreadsheet page 2 for calculation.)

Basic Costs, Revenue; County Bergen

Capital Costs Annual Recurring Costs Annual Revenue P&L

StationsGuideway

Vehicles Total

Cost of Capital

Maintenance Operating Total Fare

Station lease and

naming rights Total

(M$) (M$) (M$) (M$) (M$) (M$) (M$) (M$) (M$) (M$) $

1,224 $

2,630 $

7,032 $

10,886 $

871 $

218 $ 639 $

1,728 $ 3,835

$ 22

$ 3,858

$ 2,130

ConclusionBergen County is one of the more profitable counties in NJ. As seen also in previous years, it has

always been the most profitable county. The concentration of density in the southern region of the county allows for a favorable design of network that maximizes efficiency. In addition, since Bergen County is one of the most populous and riches counties, there is a lot of profit to be made. The large number of white collar workers provides a large workforce and a large number of commutes per day. This project has allowed me to not only learn more about network design, but also has allowed me to realize the importance of the PRT system. It was an enjoyable experience!

Notes

After getting the county file corrupted twice, I hope that future classes will back up their data in custom files as well as in the main station file. In addition, Bergen County’s data is still not very accurate. I hope that future classes will alter some patron trips to entertainment and recheck the school numbers.