Quick Facts Union County New Jersey

Transcription

1 Union County Will Fisher & Michael Chang Introduction Union County, first established in 1857, sits right south of Union County. Union County is home to the town of Elizabeth, which shares ownership with one of the East Coast's major shipping ports (Port Newark-Elizabeth Terminal). In addition to the port, Newark International Airport also lies, in part, in Union County. Union County is comprised of medium-density and low-density suburbs across 21 municipalities. It is relatively flat and low-lying. The following table presents key statistics about Union County. 1 Quick Facts Union County New Jersey Population, 2008 estimate 523,249 8,682,661 Median household income, 2007 $61,587 $67,142 Private nonfarm establishments, , ,350 Private nonfarm employment, ,234 3,661,679 Land area, 2000 (square miles) 103 7,417 Persons per square mile, ,070 1,134 For more information about our county, please see the write-ups for Union County from years past. Next, we describe the current transportation network because our PRT network will have to interface with these current mass transit options. Current Transportation Network Union County is well-served by NJ Transit's heavy rail. All told, 4 NJ Transit lines run through the stations of Union County. Amtrak runs on the NEC lines (red & blue). 1

2 Data We should note that our business data is somewhat fuzzy. We realized early on that our business data was complete in the sense that the number of businesses listed is correct but the number of employees per business is either fabricated or just wrong. Since we couldn t find a reliable database of businesses and the number of employees, we decided to take the existing set of businesses and scale the employees properly. We found the number of people employed in Union County (248,600), 2 divided by the number of businesses (6,164) and randomized each row s employee count around that number (40) with a range of [2, 78] with an equal distribution. For the patrons, we took the following piecewise function where e is the number of employees of the business and p is the calculated number of patrons: If (1 <= e <= 10): p = 80e, else if (10 < e <= 25): p = 60e, else: p = e. This models a scenario where businesses of less than 10 employees are essentially small retail shops with high volume, medium size businesses are a larger form of retail, and any business with at least 25 employees has no patrons beyond people that visit the company for some reason (e.g. consultants). We think this is a good, generic model for business activity and the numbers we find average out to about 2 business-destined trips per person per day. For the school data, we extrapolated from the employee counts to get the student enrollment numbers. We found the average student-to-teacher ratio for Union County (15.6) and used this ratio as a scaling factor to find the number of attending students. 3 We also included transportation points in our data file, mainly stations for NJ Transit's heavy rail service. We got the GPS coordinates from Google Maps and the ridership data from the respective websites. 4 Finally, we augmented the recreation Note: NJ Transit data was found on Wikipedia since that is the only source we find. Wikipedia references a document that is no longer accessible online. We still think the numbers are pretty reasonable.

3 data from a mere 5 sites to almost 50 using ReferenceUSA and found attendance data for the following types of recreational sites: amusement parks, 5 museums, 6 and malls. 7 Finally, after the presentation, we went back to the data and made sure to delete all the businesses that were located outside our county. Some of the data points were falling on locations outside our county and were contributing to low trips-served percentages. After deleting these points, we observed an increase of ~2% in trips served. Initial Network The initial network was actually mistakenly setup in Bayonne. At the time we thought that Bayonne was part of Union County but obviously had not checked this. A graph of the network can be seen below but it is of little use since the geography of Union County is much different. Final Network Our PRT network design for Union County contains 562 stations, 363 interchanges, and 13,251 placemarks. While designing this network, there were a couple obstacles. The western quarter of the county is separated from the bulk of the county by forests and Interstate 78. Moreover, the roads were not as structured as they were, say for Hudson; there were a lot of curvatures and S-shaped roads. Nevertheless, the approach to the design was relatively the same as both Hudson and Essex. We followed the arterial roads and made sure to emphasize quarter to half-mile distances between each station. The shape point became just as valuable as an interchange in this particular network. After establishing the arterial roads, we then diverged to populated suburbs and developments. Since interchanges are of no extra cost, we placed interchanges along the outskirts of the county in anticipation of future connections between counties

4 Full Network For future PRT designers, there is a particular ordering of stations and interchanges that we deem extremely helpful, concise, and optimal. Start by plotting stations all in the same direction longitudinally. Then, make the following longitudinal road have stations pointing in the opposite direction. Place interchanges wherever there are intersections between the two longitudinal roads in question. The latitudinal roads can go in any direction; for the mundane, one can alternate them from going left and then right. Now, the following pattern is what makes this network so eloquent. When two guide-ways are pointing in towards an intersection, the ordering of the leaving guide-way should be interchange then station. If two guide-ways are pointing OUT of an intersection, the ordering of the exiting guide-way should then be station then interchange. This method allows for an efficient T-like structure. Of course, one could implement the same design if he or she chose to make latitudinal roads be the base alternating roads and the direction of the longitudinal roads roamed freely.

5 Chang Fisher Network The purpose of this design is to minimize the tendency of making an extremely long circuitous route to get from one station to another. When interlaced with more lines and stations, one can cut across and zig-zag to get from place to place rather than a full circle. When designing this network, we made sure to be aware of other transportation systems already in place. We placed PRT stations by heavy and light rail stations. (You can even see the platform in the snapshot below.)

6 PRT Station in the Vicinity of a Train Station The placing of PRT systems nearby rail stations allows for an easier commute from home to a far-away workplace. Furthermore, we made sure to place stations near Park and Rides. In the long run, having a PRT system should greatly reduce the number of cars parked by a bus or rail station.

7 PRT Station in the Vicinity of a Park and Ride Last but not least, we made sure to place stations near sports arenas. A football stadium is a good indicator of a nearby university or high school, and a PRT station nearby a football stadium would automatically incorporate serving those attending their respective schools as well as make those Friday and Saturday night home games more easily accessible.

8 PRT Station in the Vicinity of a Football Stadium (School) Union County is one of the more dense counties in New Jersey, which allowed us to believe that any station nearby a residential area will easily exceed the 2,000 trips minimum. We also knew that there would be a few counties with less than 70% trips served data, so we had to take it upon ourselves to make sure we were near the 90% trip served criteria. Our network provides 87.6% service to those in Union County. The following characterizes the design features of our network: Our network links up with heavy rail stations, including all the NJ Transit train stations in Union County and a few bus Park & Ride locations. 8 Our PRT network lies on top of the existing street network and follows it closely with the liberal use of shape points (see below). By designing our network as such, there would be no trespassing involved in constructing the guideways (i.e. no need to use eminent domain). In other words, it would be easier to pitch the idea since the construction would be simpler and less 8

9 costly. In addition, we have placed some track along railways since they are straight and often the property of the public sector. Our design does not use interchanges where only shape points are needed. If there is only one track coming in and one going out, this calls for a shape point, not an interchange. We obey this principle. We have almost as many interchanges as we have stations. In Union County, this ratio is about approximately.65 interchanges per station. Since interchanges are free in our economic model, we use them liberally. The network almost exclusively uses one-way guideways. You will find very few network edges that have track in both directions. This is important because one, it simplifies design and construction and two, it lowers costs as long as the network is still connected. 9 System Analysis In looking at the station trip data, we noticed that a good number of stations serve zero trips. At first, this seemed odd to us, but on closer inspection it is clear why this is the case. In the below image, we see an example of a station where, ostensibly, we should be covering the locale's needs but because the census tracts are outside the station's quarter-mile circle, we end up with a trip-ends value of 0. In other instances, there are no official trip ends (since we didn't include the data) but service is still desired. 9 We use the term "connected" in the formal graph theory sense of the word.

10 System Evolution The PRT system is most likely to start growth in the more dense, urban areas. For Union County, this most likely means the Elizabeth/Linden/Newark region. Given the vast number of people that live and work around there, the cost per trip will be lower than anywhere else in the county. Ideally, however, the system would be fully funded and all the designed stations would be constructed. This has the advantage of offering a full countywide transportation system because what use is a mode of transport if it doesn't cover the desired destination? Benefits Among the obvious benefits are reduced traffic fatalities and reduced loss of time as a result of greatly-diminished traffic congestion. Union County had 14 pedestrian deaths in We can put economic values on the time savings and decreased fatality rate, but since they are not included in the spreadsheet model, we will leave this as is. If nothing else, these numbers would favor the construction of a PRT system since there are costs that will be saved by the residents of Union County. Neighborhood Changes We believe that the implementation of a successful PRT will result in higher property values in the affected areas and consequently, better recreational areas, better air quality, greater walkability and less crime. We claim that property values will go down because it has been shown that proximity to public transit increases home prices. 11 Assuming that cars are successfully replaced by our PRT system, it goes without saying that air quality will improve. Indeed, the overall environmental profile of our PRT system should be much better than that of an automobile-based system as long as the (power) grid is supplied by non-carbon sources or carbon

11 light fuels such as natural gas. As for the claims of reduced crime, we think that Jane Jacobs's notion of "eyes on the street" 12 will suffice to bring about reductions in crime. Jane Jacobs postulated that urban areas with more people walking around and fewer people in cars leads to safer areas. While traveling in a PRT pod is not conducive to this effect, walking to and from the station is key. Whereas cars can be parked at the home and used from end to end, PRT stations are located within walking distance of destinations. Thus, the extra walking required of our PRT system should be enough to produce the desired increase in walkability of the affected neighborhoods and in turn reduce crime in these areas. Network Details & Finances We plot the trip-ends per station below. In this plot, we see that a few stations serve an exceptionally high number of trip ends while most of them average around 8,000 trip ends. On the other hand, up to 150 of the stations serve at most a thousand trip ends. These stations are as such because we overprovisioned the network, putting stations where Google Maps showed there to be people or business but where we didn't have data points because of the granularity of the data. That is, the data points (falsely) aggregate spread-out distributions into single points. Our PRT network has 562 stations and 305 miles of guideway serving a population of 522,000. We serve a total of 5,944,000 trips out of a possible 6,785,000 for a total provided service level of 89.9%. This corresponds to 2,280,000 trips, which equates to 4.3 trips per person per day. We feel this number is a little high, possibly by 1 trip/person/day. The specification calls for 90% and we are happy with our network since it almost perfectly meets the required service needs without overextending. We got the service level percentage higher than before by removing extraneous data points, which we discuss in the data section. We also investigated the numbers from the top stations. For this county, the top few stations report patronage numbers of ~130,000. Looking at these stations, we see that they are located next to dense housing developments and malls. We feel that the combination of those two makes it possible to give us these high numbers. Even though the Kornhauser PRT system multiplies the number of passengers/residents by a small factor to arrive at the number of trip ends, we still feel this number is high, possibly by a factor of 2. Taking the Jersey Gardens mall as an example, it gets it about 25,000 people per day, 13 which corresponds to 50,000 trip ends per day. We simply may have just multiplied the employee counts of business by too great a factor to arrive at the patronage numbers. That is, the patronage counts are simply artificially high. The recreation data seems fine as it predicts 35,000 recreation trip ends per day. This is less than 7% of the population per day using the PRT to go to gyms and clubs and the like. We feel this is reasonable. In addition, the home numbers perfectly correspond to 4 times the true population which makes sense since the Kornhauser PRT system multiplies the census data by

12 On the other hand, the work numbers may be too low. We only forecast 665,000 work-based trip ends per day. Depending on the employment rate, this may be too low since at the very least, there should be two trip ends per day per person (going to and leaving work). The main issue is that our employment data, though thorough in the number of business covered, may be inaccurate in the number of people it claims work in Union County. We may have wanted to scale up these numbers to match total county employment statistics. For the financing of the project, refer to the below table. The net result is $1.1 billion dollars in profit per year. The construction costs are $12,200 per person, which is not particularly high given that the average cost of owning a car in the US is $7, Basic Costs, Revenue; Union County Capital Costs Annual Recurring Costs Annual Revenue P&L Stations Guideway Vehicles Total Cost Capital Maintenance Operating Total Fare Naming rights Total (M$) (M$) (M$) (M$) (M$) (M$) (M$) (M$) (M$) (M$) $1,124 $1,525 $3,763 $6,412 $513 $128 $342 $983 $2,053 $20 $2,073 $1,090 As for the break-even cost of the station, we do the following calculations: first, assume that each station costs $200,000 per year consisting of an amortized construction cost of $160,000 per year plus $40,000 in maintenance every year 14

13 (from Excel sheet). Now, if we assume that each trip contributes 50 cents in revenue to the station it uses at one endpoint, then a station needs (200,000/(365*.50) = 1100 trips per day to be competitive. Unfortunately, this would rule out many of our stations. That said, transportation systems often account for less profitable infrastructure by subsidizing it with the profits from more heavily trafficked infrastructure. The plot below has the trips per day data.