Bicycle sharing programs provide modern cities with an alternative mode of transportation to residents and visitors alike. As such, it is important to analyze the behavior of these programs and assess their reliability. This work presents an approach to perform a behavioral analysis and to assess the reliability of bicycle sharing programs, taking New York City's Citibike program as a case study. The approach take two errors into account: (i) the error of having excess bicycles and the user not being able to return a bicycle, and (ii) the error of not having bicycles available at for a user to take. The probability of occurrence of each error is calculated according to the behavior of each station and a certain time. This work could help decision makers plan for rebalancing and docking expansions for bicycle sharing systems.
NYC Subway :
The annual ridership for New York City’s Subway system is of more than 1.7 billion during the past year (7th in world rank). Statistics have shown an increase of ridership over the last years but a decrease in the number of trains that are on time. This work enables an understanding of NYCs subway system, creating a behavioral characterization per station and route. This understanding can help forecast the the inflows and outflows of people per periods of time and per station. This work also plans to gain understanding of repairs and micro events that can affect public transportation systems.
Services in a smart city are assessed to see if they contribute to the improvement of quality of live within a city. The evaluations are done on a technical level, but do they match the perception of the people? Do people really think they live in a smarter city and that these services make their lives better? This work explores this concept.