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Analytics and Big Data — Rail Public Transportation is a Leader

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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 Analytics
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 Public Transportation
• 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 ( s, 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 — 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 s, 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 512.441-3014
Blog Columnist, Railway Age Magazine Co-Principal, Urban Rail Today Technical Consultant , Light Rail Now Project

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