Will Fisher & Michael Chang

Transcription

1 Essex County Will Fisher & Michael Chang Introduction Essex County, first established in 1683, is home to New Jersey s largest and most economically important city, Newark (population 280,000). On the east side of Essex county lies the city of Newark and half of Newark International Airport while the western portion of the county consists of suburbs of both Newark and New York, decreasing in density as you go farther west. Essex County, like Newark, is a socioeconomic melting pot. Newark is home to large multinational companies, such as Anheuser-Busch and Prudential, and some of the county s worst poverty, with a median household income just shy of $27, A mere 10 miles outside of Newark lies the municipality of Essex Fells, a town with a median household income of $148, Essex County is also home to the Port Newark-Elizabeth Terminal, the third largest port in the country. 3 The following table presents key statistics about Essex County. 4 We assume that the housing units figure is so high because of the number of non-home owners in Newark living in apartments. Quick Facts Essex County New Jersey Population, 2008 estimate 793,633 8,682,661 Housing units in multi-unit structures, % 36.1% 1 New_Jersey 2 Ibid

2 Median household income, 2007 $53,319 $67,142 Private nonfarm establishments, , ,350 Private nonfarm employment, ,225 3,661,679 Land area, 2000 (square miles) 126 7,417 Persons per square mile, ,300 1,134 Transportation Essex County is home to one of New Jersey's three light rail lines. The Newark Light Rail system, which runs from north Newark (Grove St.) to Newark Penn Station downtown. Essex county is well-served by NJ Transit's heavy rail service in large part because Newark Penn Station and Newark Broad Street Station are both key points that many NY-bound trains must pass through. All told, 5 NJ Transit lines run through these stations, combined. Amtrak NEC service runs through (and stops at) Newark Penn Station. Finally, Newark Penn Station is also a terminal for PATH service. 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 Essex County (333,600), 5 divided by the number of businesses (8,236) and randomized each row s employee count around that number (41) with a range of [2, 80] 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. 5

3 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 Essex County (13.1) and used this ratio as a scaling factor to find the number of attending students. 6 We also included transportation points in our data file, mainly stations for heavy rail (NJ Transit, PATH). We got the GPS coordinates from Google Maps and the ridership data from the respective websites. 7 Finally, we augmented the recreation data from a mere 5 sites to almost 50 using ReferenceUSA and found attendance data for the following types of recreational sites: amusement parks, 8 museums, 9 and malls. 10 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 we constructed had a lattice-type configuration in downtown Newark. We decided to scrap this design because it was overly complicated and hard to follow. This initial network is shown in the figure below. In particular, it was difficult to see how lengthy the paths had to be in order to reach destinations. Instead, the final network employs a combination of a grid pattern and loop structures 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

4 Final Network What we have done for Essex is utilize a grid-based system. In the downtown, we have denser grids with reversing directions and plenty of interchanges. In other words, we tried as best we could to mimic the actual street grid in Newark. But Essex County is covered in suburbs. It includes medium-density suburbs with

5 smaller houses and little unused backyard space to more affluent areas with greater spacing between houses and more privacy. The majority of Essex County suburbs fall into the medium-density category. For this, we did our best to stay on the arterial roads (again, maintaining a grid by making sure that adjacent arterials go in opposite directions) and where the arterials are too far apart to require residents to walk through the subdivision to the arterial road, we put stations father in. Inserting stations into subdivision is generally a pain because the subdivisions are often designed with (ridiculously) curvy, non-grid-like roads for aesthetic reasons. Therefore, many shape points are needed to map the design well. The following diagram shows an example of inserting a station into a subdivision. The "cut through" station is a station inserted for the sole purpose of serving the residents in the wide housing development between the arterial roads. Our network also covers key points of interest including Newark International Airport (left), Newark Penn Station (right), Rutgers University (lower left), and recreational facilities (lower right). We feel it is important to design the network to accommodate popular venues in particular. We do not include the NJ Transit EWR station because we feel that this rail station should not be a destination from our PRT system. If PRT users are looking for heavy rail, they can take the PRT to Newark Penn Station.

6 We decided against modeling our system to accommodate the Newark Light Rail system. Despite the fact that our specification says to make our PRT system complimentary to the light rail, we did the opposite. It is hard to justify designing a good PRT network around a service that is almost exactly the same. Light rail offers an automated for of mass transit serving a handful of popular points along one route. On the other hand, our PRT network will be faster (since it is not mass transit) and will have many more destinations, including all of the locations served by the Newark Light Rail. It will be ground level and automated. Not only would it be extremely difficult to model our network to be complimentary to light rail services, what would be the point? It is hard to imagine how light rail and PRT can be equal parts of a multimodal trip.

7 In addition to providing good service around residential zones, we also make a concerted effort to include stations near industrial areas with little residential zoning. This includes storage and shipping facilities, warehouses, etc. This sector is centered in industrial zoning areas and we make sure to include these facilities so that the employees can get to and from work. See the below picture for an example of such a place. 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 Essex County and a few bus Park & Ride locations. 11 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 costly. In addition, we have placed some track along railways since they are straight and often the property of the public sector. 11

8 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 Essex County, this ratio is about approximately.85 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. 12 In a handful of places, one station is attached to network with a bidirectional guideway. We feel this is justified because the station platform can be positioned a la the drawing below. In this drawing, the blue lines represent the guideway, the green is the network and the red is the station platform (note the unique placement). We use this technique in place where it would make little sense to wrap around the station with tracks on either side. For an example in our network, see the figure on the right. 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. One example of this is Newark International Airport. 12 We use the term "connected" in the formal graph theory sense of the word.

9 System Evolution The PRT system is most likely to start growth in the most dense, urban areas. For Essex County, this means Newark. Given the vast number of people that live and work in Newark, 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. Essex County had 20 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 Essex 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. 14 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

10 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" 15 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 10,000 trip ends. On the other hand, up to 120 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 739 stations and 436 miles of guideway serving a population of 600,000. We serve a total of 8,644,000 trips out of a possible 9,642,000 for a total provided service level of 92.5%. This corresponds to 3,473,000 trips, which equates to 4.4 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 ~150,000. Looking at these stations, we see that they are all in the heart of Newark with some points up by Fairfield, NJ. We're not sure why so much activity is being reported from Fairfield but this seems a little odd, we admit. The top station is the PRT station at the Newark NJ Transit & PATH station. The high numbers are actually due to high business patronage counts, not high transportation counts. This number is certainly artificially high because it counts patronage that does not use the PRT system. For example, in the Newark station there are many different food vendors. For our data, we multiply the business size by a certain patron factor. Therefore, our data shows that 150,000 business transactions will be made in the ¼ mile area around the Newark station (or within the station). This may be true Newark has a dense downtown with large numbers of commuters. But these transactions probably won't be made by PRT. Many of them will be made by foot. For example, PATH travellers picking up a bagel at the Newark station will be counted as two uses of the PRT system when at most, there is only one. And so the results overestimate the number of PRT users in certain areas of 15

11 high density where people are most likely to be on foot (which occurs more often in Essex County than other counties in NJ). In addiiton, 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. In addition, there may be some overcounting of the transportation trips. Since Newark station serves PATH and NJ Transit, the population that transfers between the two should not be counted. Ideally, we would reduce our PATH data numbers in Newark by 50%, implying that half of the people boarding or alighting from PATH switch to NJ Transit. Regardless, this would have little overall effect on our numbers since the patronage counts far exceed the transportation trip ends. In addition, we do not have a Newark airport rail station. Though a data point exists for that rail station, we did not put a PRT station there as to avoid double counting. The recreation data seems fine as it predicts 38,000 recreation trip ends per day. This is less than 5% 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 4. Although some of our housing data may seem high, we were not alarmed. Some of the home counts per station top 30,000. Since these values are multiplied by 4, this implies that 7,500 people live in a circle of half mile diameter. This corresponds to a density of 38,000 per square mile (with a little math), which is completely within reason given that Union City in Hudson County has over 50,000 per square mile. On the other hand, the work numbers may be too low. We only forecast 905,000 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 Essex 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 $1.7 billion dollars in profit per year. The construction costs are $12,000 per person, which is not particularly high given that the average cost of owning a car in the US is $7, Basic Costs, Revenue; Essex County Capital Costs Annual Recurring Costs Annual Revenue P&L Stations Guideway Vehicles Total Cost of Capital Maintenance Operating Total Fare naming rights Total (M$) (M$) (M$) (M$) (M$) (M$) (M$) (M$) (M$) (M$) $1,478 $2,180 $5,732 $9,390 $751 $188 $521 $1,460 $3,126 $27 $3,153 $1,

12 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 (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.