Genfare’s software innovations provide powerful back-end tools that enable transit agencies to make smarter business decisions. It begins with our proven method of recording fare collection data. Our hardware and software work together to validate tickets with information on time, date, location, route, and more. With wireless technology, agencies can download this data from each farebox and begin robust fare collection analytics. By understanding the behavior of riders, agencies can better anticipate and serve their needs, providing increased rider satisfaction, more cost-efficient services, and overall increase in revenue.
Here are some of the many current and future benefits of our proprietary transit analytics capabilities.
More Efficient Routes
Oftentimes, the collected transit data will immediately show patterns. Routes may be overloaded during certain periods or under-used during others, both of which may demand route reconfiguration. Other patterns may become apparent over time, such as decreasing or increasing ridership. Noticing these patterns helps agencies modify or create new routes to better serve the public.
The ability to detect common transfer points can also help indicate where full-through routes may need to provide better service. Similarly, time stamps may help identify routes that are unexpectedly long due to city traffic patterns or other repeated delays. In some cases, the fare collection analytics can even pinpoint particularly inefficient drivers who may be slowing down boarding times or causing other unique delays.
Complex transit systems can take advantage of the data’s ability to help design multi-modal systems. This can include trip planning that includes multiple routes across light rail, buses, and other forms of transit owned by the agency. It can also allow cities to plan symbiotically with current or future bike paths, parking lots, hourly car rentals, and other important infrastructure, both private and public.
Accurate Prediction Models
Big data is proven effective across all industries at producing accurate prediction models. Fare collection analytics is no different—the data collected by Genfare can help inform the pros and cons of various proposed changes to the transit system. Using historical as well as real-time data, prediction model software can accurately and instantly predict various outcomes of each potential decision.
These models can not only help assure transit agencies and city authorities of the usefulness of changes but the city’s public, too. This is especially helpful in situations where public approval is necessary for large-scale transit projects to begin. The collection of data now can help garner the public’s support for projects that may not break ground for five to ten years.
There are innumerable new uses for transit analytics that can be helpful in the future. Looking to the near future, cloud-based databases may soon allow us to record the time and place of every single transit trip from beginning to end. This data can revolutionize the ability to guide long-term economic development plans.
Other possibilities include the ability to incorporate additional external data, such as weather, into analysis of efficiency. Future transit analytics may also create the ability to alert riders to delayed buses and trains, allowing them to utilize their wait times more effectively with increased rider satisfaction. Innovations like “flexible transit” could soon allow agencies to dynamically adjust routes based on real-time need with riders consulting smartphone apps for the latest route information.