Final Project Written Report

We began our analysis of Camden’s first file. To get a better understanding of the density of the county, we identified one of the top pixels in the file with the most daily trips departing from it. Not surprisingly, the pixel was of the Lindenwold train station, which serves Atlantic City Rail Line (NJ Transit) as well as PATCO. Here is an overhead view of the entire pixel, area = ¼ square mile. The pixel indices are given:

The above graph shows the cumulative number of departures of aTaxis per hour, so this really represents the busyness of arriving trains at the station dropping off patrons. Lindenwold is very much a residential town and not a work destination town, so it makes sense that there is a constant stream of people getting off from 7am to 3pm, and then, when the workday is over, there is a massive spike as workers return to their homes in Lindenwold between 4pm and 10pm.

Daily AVO: 1.12

This above graph is important because it gives a good depiction of how many people are in an aTaxi each hour on average. This will give us good insight into what sizes of vehicles we will need to be in the area during time ranges. From midnight until 4pm, there is no need to have taxis any larger than 1-2 people (so small sedans or coupes, for example), because no AVO exceeds 1.06. Then, once evening rush hour hits, those taxis can be dispersed elsewhere around the county, and the larger, van-like transportation vehicles, with capacities closer to 5-6 people should descend upon Lindenwold station.

A very interesting comparison can be seen between this graph and the graph on the previous page (aTaxi departures per hour). The two have very similar trends throughout the entire day. This shows a relationship between the amount of people in a taxi and the amount of taxis leaving the train station. The more taxis leaving Lindenwold means the more people per taxi in this scenario.

The above two graphs show how passenger miles and aTaxi miles share the same general distribution, however there will be several instances on the passenger miles chart that exceed those on the taxi graph. This is common behavior among all plots of the same nature because of rides that carry more than 1 passenger; the taxi miles stay the same, whereas the passenger miles are multiplied by total passengers. The above graphs are a scatterplot of every single trip during the day from that particular pixel, so keep in mind that the lower parts of the graph (with fewer miles) are more closely packed, and thus there is a high number of trips traveling fewer miles, which are tough to distinguish based on the pixels’ density.