Analytics and Big Data — Rail Public Transportation is a Leader

1. Analytics and Big Data — Rail Public Transportation is a Leader Lyndon Henry Blog Columnist, Railway Age Magazine Co-Principal, Urban Rail Today Technical Consultant , Light Rail Now Project APTA 2013 Rail Transit Conference Philadelphia June 2013

2. What are …? Big Data Significantly large volumes of data, particularly involving human activities and characteristics Analytics High technology applied to data processing, complex calculations, and automation

3. Common Examples Private/Public Sector • Consumer behavior analysis • Customer mailing lists/marketing • Smartphone apps • GPS • Financial market trading • Astronomical tracking/mapping •Weather tracking/forecasting • Genome mapping • Crowd surveillance • Monitoring electronic communications • Data-mining online/wireless data (Emails, texting, social media) • Robots Public Transportation • Ridership forecasting • Train signaling/dispatching • Route planning/scheduling • Automatic Vehicle Location (AVL) • Passenger Information Systems • Automated Fare Collection (AFC) • Automated Passenger Counting (APC) • Driverless Automatic Train operation (ATO)

4. Major Applications in Public Transportation

5. Travel Demand Modeling & Ridership Forecasting • Forefront of Big Data & Analytics for many decades! • Project demographic characteristics for each TAZ • Project future growth in population, economic activity, travel patterns • All trips from all households in all zones to all other zones • Forecasting ridership • Really Big Data! Travel Analysis Zones in Baltimore Metro Area

6. Train Signal and Control Systems • Legacy goes back to 19th century! • High-tech, complex process for tracking location of trains, estimating travel times, etc. • From electro-mechanical to electronic-digital • Automatic Block Signaling (ABS), Cab Signaling System (CSS), Centralized Traffic Control (CTC), Automatic Train Control (ATC), Communications-Based Train Control (CBTC), Automatic Train Operation (ATO), Positive Train Control (PTC), Driverless ATO

7. Route Planning and Scheduling • Performs routine, tedious tasks — routing, developing timetables, blocking into bus and train schedules, runcutting, and other essential component tasks such as rostering • Allows schedulers and transit planners to quickly develop many different scheduling scenarios • Significantly increases operational efficiency

8. Automatic Vehicle Location (AVL) • Uses GPS-based data + Analytics to track both buses and trains Passenger Information System • Based on AVL or train signal/dispatching system • Big hit with passengers

9. Automated Fare Collection (AFC) • Uses ticket vending machines (TVMs) • Smartcards provide access to all types of transit services across multiple operating agencies and jurisdictions • AFC Analytics provide details of how passengers are using systems, identify trends, help improve service

10. Automated Passenger Counting (APC) • Informs agency as to how many passengers are boarding-deboarding each vehicle, precisely where this happens • Data can be used to provide better service and project evolving ridership trends

11. Selected System Examples

12. Bay Area Rapid Transit (BART) • Analytics/Big Data is key element of train operations, passenger services, power delivery, wayside facilities • Operational analytics includes delay analysis, passenger flow modeling (PFM), system performance analysis • PFM ensures on-time service, optimizes train schedules (ensuring high customer satisfaction) while constraining service operating costs

13. Austin — Capital Metro's MetroRail • CTC control center uses data radio as primary system, cellular phone system as secondary backup • GPS currently used mainly as component of passenger information system (with PIDs in stations) • APC used for gathering passenger statistics plus planning and operations (e.g., adjusting schedules to accommodate passenger flows, changes in traffic demand by time of day)

14. Philadelphia — SEPTA Regional Rail • Wide variety of Analytics/ Big Data functions — operations control, scheduling, AVL, train signaling/dispatching, AFC with TVMs, APC, passenger information with PIDs, etc. • Passenger information system provides PIDs in some larger stations, plus app providing bus/train status to smartphones • APC data to be used to adjust scheduled consists and track trips for Job Access and Reverse Commute (JARC) services

15. Seattle – Sound Transit's Link, Sounder • Analytics/ Big Data involved in signaling-control-dispatching; passenger information with online and smartphone train status information and station PIDs; APC; GPS and AVL capabilities; AFC with TVMs in stations • AFC system uses “seamless” regional, trans-agency ORCA payment card • Source of Big Data for local transit agencies — information on individual passenger movements throughout region, plus passenger flows at various locations and times of day

16. Current Issues and Trends

17. Data Mining • Poor public reputation, mainly because of privacy issues • But data mining is typically just a computer-based process of discerning patterns in sizable sets of data • Especially with AFC and APC, opportunities abound to utilize data mining of data flows to analyze operations, passenger behavior, etc. • Aim: improve services and performance

18. Cloud Computing • Computing resources (hardware/ software) available over a network (e.g., online — Email or blogging software) • As Big Data and Analytics needs grow, Cloud is a means of getting access to more powerful outside-vendor resources • Apache Hadoop — NOT a database! Open-source framework for distributed processing needed for data-intensive tasks

19. Sentiment Analysis • Form of data mining applied to textual, verbal information (from Emails, social media, open forums, etc.) • Attitudes, opinions, intentions, etc. in source materials can be identified and extracted for processing and scrutiny • Useful to gauge public attitudes toward transit agency's services, attitudes regarding new plans or services, sentiment on a political issue such as a ballot measure

20. Security issues • Concern is magnified with Big Data (far more data to lose) • Issue has escalated with recent "cyber-attacks" on data and functioning of large institutions

21. Privacy Concerns • Very hot-button issue for general public • Potential to extract great volumes of Big Data from fare transactions, passenger counts, surveillance of passengers in trains and stations opens opportunity for abuse • Seattle ORCA card issue — employers could track employees’ use of transit passes!

22. Predictive Analytics • Applies Analytics to current and historical Big Data to develop predictions about future • Used to evaluate future role of public transit systems, forecast ridership, and suggest need for new transit systems and facilities • Further benefits include passenger flow modeling (a la BART), other operational projections and simulations

23. Robotics • Automated machines or devices that can replicate human activity or behavior, including operating a vehicle • Rail transit has led the way with ATO and now driverless trains

24. Summing Up

25. Rail Public Transportation Leads! • Legacy of analytical and data-based high technology going back to 19th century • Rail transit probably has one of the heaviest utilizations of Analytics/Big Data among modern industries • Continuing to lead with automated systems, robotics, and other leading-edge transportation technologies

26. Lyndon Henry Blog Columnist, Railway Age Magazine Co-Principal, Urban Rail Today Technical Consultant , Light Rail Now Project 512.441-3014 Nawdry@gmail.com