In a paper presented this past June (2013) to the annual Rail Conference of the American Public Transportation Association (APTA) in Philadelphia, Light Rail Now Project technical consultant Lyndon Henry (also an independent transportation planning consultant with Urban Rail Today and a blog columnist for Railway Age magazine) emphasized the leading role that rail public transportation has been playing — actually for a number of decades — in the Analytics and Big Data revolution that has been sweeping through both the private and public sector of global economies. (Lyndon is also a blog writer for the All Analytics online forum, sponsored by business analytics provider SAS.)
The paper — titled Analytics and Big Data — Rail Public Transportation is a Leader — not only highlighted a wide variety of applications of the newly emerging capabilities of this technology, but also the long developmental legacy in which rail public transportation has been a pioneer.
So, what are Analytics and Big Data, anyway? This is best explained in the paper’s introduction itself:
Two concepts currently at the leading edge of today’s information technology (IT) revolution are Analytics and Big Data. Analytics is high-technology applied to data processing, complex calculations, and automation; Big Data is the current term referring to significantly large volumes of data, on virtually every facet of human activities and characteristics, that can be rapidly processed via Analytics, yielding a broad spectrum of highly useful results. Recent technological advances have sparked what amounts to a “revolution” in the application of these cognitive and informational tools.
“Apparently without realizing it,” observes the paper, “the public transportation industry, has, for many decades, been at the forefront in utilizing and implementing Analytics and Big Data, from ridership forecasting to transit operations.” As it goes on to explain:
Rail transit systems have been especially involved with these IT concepts, and tend to be especially amenable to the advantages of Analytics and Big Data because they are generally “closed” systems that involve sophisticated processing of large volumes of data. In virtually any American city, on any normal weekday, one is likely to see the results of analytics literally in motion — the operation of transit buses and trains that are essential to maintaining the mobility of the metro area.
The more that public transportation professionals and decisionmakers understand the role of Analytics and Big Data in their industry in perspective, the more effectively they will be able to utilize its promise. Furthermore, it is useful for both the public and the industry to realize how significantly public transportation has been a leading pioneer in the rich and extensive historic development of these tools, the roots of which in some cases extend back to 19th century rail technology.
The paper then details a number of the major general applications of Analytics and Big data in modern rail passenger and rail transit systems:
• Travel Demand Modeling — how analytics has actually been used for decades in planning new public transportation services and infrastructure
• Train Signal and Control Systems — involving components and technologies such as automatic block signaling (ABS), cab signaling system (CSS), centralized traffic control (CTC), automatic train stop (ATS), automatic train control (ATC), communications-based train control (CBTC), automatic train operation, or ATO, and positive train control (PTC)
• Route Planning and Scheduling — involving analytics-based software for tedious tasks such as routing, developing timetables, blocking (developing bus and train schedules),runcutting, and essential component tasks such as rostering
• Automatic Vehicle Location (AVL) — this transit operating mechanism deploys analytics to track vehicles in operation and and provide information to passengers via passenger information display (PID) monitors or digital signs in stations, or apps on smartphones
• Automated Fare Collection (AFC) — typically relying on ticket vending machine (TVM) devices in stations that can receive cash or process credit card swipes, thus also instantly updating a central database
• Automated Passenger Counting (APC) — tallies how many passengers are boarding or deboarding each vehicle, and precisely where this happens, and relays this information continuously to a central database
To illustrate some of these applications, a number of case studies are highlighted from actual operating systems:
• Bay Area Rapid Transit (BART) — focusing on agency’s operational analytics providing delay analysis, passenger flow modeling (PFM), system performance analysis, and operational forecasting.
• Salt Lake City TRAX — focusing on CTC train tracking and dispatching system, the GPS-based passenger information system, and the AFC system.
• Austin – Capital Metro’s MetroRail — focusing on operational analytics involved with the ABS (automatic block signal) system overseen by CTC (central traffic control), the GPS-based AVL and passenger information system, and APC.
• Philadelphia – SEPTA Regional Rail — focusing on the system’s signaling-dispatching technology, mainly involving a combination of CTC, ABS, and ATC, plus CSS and PTC via compatibility with Amtrak’s Advanced Civil Speed Enforcement System (ACSES).
In addition, Analytics is being utilized in the form of APC, as well as planning and scheduling, plus a passenger information system utilizing both PIDs with train arrival/departure onfprmation and a smartphone app providing bus and train status information to passengers’ personal devices.
• Philadelphia – SEPTA Suburban Trolley Lines — focusing on these lines’ signal systems, currently ABS-based, but with planned conversion to CBTC is being planned.
• Seattle – Sound Transit’s Link and Sounder — focusing on these operations’ enhanced AFC system utilizing the new regional, trans-agency ORCA payment card.
• Tacoma – Sound Transit’s Tacoma Link Streetcar — focusing on how this very small, simple, extremely bare-bones system integrates its APC system with onboard GPS, and provides on-train passenger announcements triggered by wheel pulses from the cars’ propulsion sensors that gauge distance traveled.
The paper concludes with an overview of some of the most salient current issues and trends in Analytics and Big Data, and their relevance for rail public transportation. Topics include:
• Data Mining
• Cloud Computing
• Sentiment Analysis
• Security issues
• Privacy Concerns
• Predictive Analytics
Check out the full paper for a more detailed discussion of these topics.
A PowerPoint slide show presented at the conference is also available online.