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Legal Arrangements for Use and Control of Real-Time Data (2011)

Chapter: APPENDIX A--DISCUSSION OF RESPONSES TO SURVEY QUESTIONS

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40 APPENDIX A--DISCUSSION OF RESPONSES TO SURVEY QUESTIONS A. Profile of Transit Agencies Collecting Real-Time Data As seen in Table 2, of the 65 agencies that responded to the survey,481 34 stated that they are collecting real-time data for trains or buses. Thirty-one agencies responded that they presently are not collecting real- time data. Twelve agencies responding to the survey also reported that they collect real-time data for both bus and rail service. Table 2. Sixty-Five Agencies' Responses to the Survey Regarding Collection of Real-Time Data Transit Agencies Collecting Real- 34 Time Data Transit Agencies Not Collecting 31 Real-Time Data Transit Agencies Collecting Real- 12 Time Data for Both Trains and Buses Table 3 shows the number of passenger trips by rail annually by agencies that are collecting real- time data. The number of trips ranged from less than 10 million to more than 80 million. Table 3. Number of Annual Passenger Trips by Rail by Agencies Reporting They Collect Real-Time Data No. of Passenger Trips by No. of Agencies Responding Rail Annually 9,999,999 or less 3 Between 10,000,000 and 7 49,999,999 Between 50,000,000 and 2 81,000,000 The agency collecting real-time data with the least passenger trips by rail yearly was San Mateo County Transit with 1,057,634; the agency reporting the most trips was LIRR with more than 81 million trips an- nually.482 Table 4 shows the number of passenger trips by bus annually by agencies collecting real-time data. Not all agencies responded to the question; however, the agency responding to the survey collecting real-time data with the smallest number of passenger trips by bus annually was Montachusett Regional Transporta- tion Authority with 610,867 passenger trips per year; the agency reporting the most trips was Miami-Dade Transit with 84,775,337 passenger trips per year.483 481 Some agencies participating in the survey did not respond to every question. 482 Two agencies responded that they collected real-time data for rail service but did not indicate their annual number of passenger trips by rail. 483 Some agencies that reported collecting real-time data did not state their annual number of passenger trips by bus.

41 Table 4. Number of Passenger Trips by Bus Annually by Agencies Reporting That They Collect Real-Time Data 484 No. of Passenger Trips by Bus No. of Agencies Responding Annually 9,999,999 or less 2 Between 1,000,000 and 5,999,999 4 Between 6,000,000 and 3 19,999,999 Between 20,000,000 and 7 49,999,999 Between 50,000,000 and 4 85,000,000 B. Profile of Transit Agencies Not Collecting Real-Time Data As for transit agencies not collecting real-time data, although not all agencies responded to the question, Table 5 illustrates the agencies' profile by number of passenger trips by bus each year. Table 5. Number of Passenger Trips by Bus Annually by Agencies Reporting That They Do Not Collect Real-Time Data 485 No. of Passenger Trips by Bus No. of Agencies Responding Annually Less than 99,999 2 Between 100,000 and 499,999 3 Between 500,000 and 999,999 5 Between 1,000,000 and 1,499,999 6 Between 1,500,000 and 1,999,999 1 Between 2,000,000 and 2,999,999 2 Between 3,000,000 and 3,999,999 2 Between 4,000,000 and 4,999,999 2 Between 5,000,000 and 5,999,999 2 Between 6,000,000 and 6,999,999 1 Between 7,000,000 and 9,999,999 1 Between 10,000,000 and 0 36,999,999 More than 37,000,000 1 As for the number of passenger trips by rail by agencies not collecting real-time data, only two agencies responded: the Memphis Area Transit Authority with more than 1.3 million passenger trips by rail annually and the Connecticut Department of Transportation with annual passenger trips by rail of 38 million. 484 Not all agencies responding to the survey provided information. 485 Not all agencies responding to the survey provided information.

42 C. Method for Collecting Real-Time Data Respondents to the survey indicated a variety of systems for collecting real-time data. However, several of the agencies responded in some detail. AC Transit stated that "ACS AVL is used for internal operations. We also have a contract with NextBus to provide Real-Time Passenger information. NextBus uses the location data from the ACS AVL but pro- vides the real-time predictions themselves. NextBus owns the prediction data." The Charlotte Area Transit System reported: CATS does collect real-time data from both its bus and light rail vehicles. The bus fleet utilizes an Automatic Vehi- cle Locator (AVL) system equipped on each bus to collect and transmit location and adherence information every sixty seconds. This system works in conjunction with the Automatic Passenger Counters (APC), which collect and transmit passenger boarding and alighting data whenever activity occurs. Other data is also transmitted real-time, such as communication transactions with the control center, and mechanical alarms that are triggered. Farebox transaction data is also collected continuously, though this data is only transmitted to the central system at the end of each service day through a manual probe of the farebox. For the rail service, a Supervisory Control and Data Acquisition (SCADA) system collects real-time vehicle location data based on track occupancy. Each rail vehicle is also equipped with an APC system, which collects and stores passenger boarding and alighting data. This data is available the next day after the rail vehicle returns to the yard. Dallas Area Rapid Transit's response to the survey on data collection was: Our AVL system is 17+ years old. The onboard control systems (MDU) are connected to an on board GPS receiver and to the radio system. The MDU communicates to Central Dispatch servers via 800 and 900 mhz radio frequen- cies. Approximately every 90 seconds (more rapidly when less vehicles are on the street) the central dispatch serv- ers send a request for vehicle location to the onboard units. The onboard units respond with the vehicle number, the latitude, longitude and a timestamp. Other data, the block number that the vehicle is running and the operator id are transmitted as part of this data stream if that data is available. The Maryland Transit Administration stated that it used an ACS-TMS CAD/AVL system for its fixed- route bus system, a Trapeze-Mon system for paratransit service, and SCADA systems for its light, heavy, and commuter rail services. The most detailed information was provided by the LIRR: 1. The Train Information Monitoring and Control System (TIMACS). TIMACS is the real-time application used by Transportation to keep track of train movement. This system provides the tower operators with "user- friendly" screens that allow him/her to record train timings and other transactions at their location. The operator also receives timings and transactions from other tower locations. This gives them and the Transportation Dis- patchers a better perspective of what is happening throughout the Long Island Rail Road. Different versions of the TIMACS application exist at the Movement Bureau, tower locations, PSCC (Penn Station Central Control) and usher locations. Each version of the application shows train information in a format pertinent to each type of user that makes it easier to perform their day-to-day operations. In addition, TIMACS information is accessible through the LIRR Corporate Intranet. 2. Wayside Monitoring and Diagnostics System (WMDS). The WMDS is utilized to track, monitor and record data from the M7 MU fleet via GPS and cellular technology for the purpose of obtaining maintenance information. The system transmits status heartbeats, log files, software version control, event recorder and system's real time data to LIRR wayside users for 24/7 support of the M7 fleet. 3. ArcGIS Global Information System (ArcGIS). The ArcGIS is utilized to record LIRR infrastructure assets with geographical data of Long Island and the New York City Metro area onto map documents. Custom maps can be created by user departments with the ArcGIS application. These maps can be referenced by a web based browser interface available to LIRR users on the LIRR Intranet.

43 4. Automated Vehicle Locating & Monitoring (AVLM). The AVLM is an electronic fleet web-based tracking system deployed on the LIRR automotive fleet assets. The AVLM tracks, transmits, and records real time positional data and status of the vehicles and its drivers. 5. Passenger Information/Automated Station Identification (PIS/ASI). The Passenger Informa- tion/Automated Station Identification system, which is integrated with TIMACS, is responsible for the communicat- ing with the M7 fleet to supply active and backup route information, which propagates data to the M7 onboard signs and audio system upon demand by train operators. Active routes, which use TIMACS Points of Interest (POI), are tracked by GPS technology. D. Models or Formats Used or Requested for Sharing Real-Time Data Twelve agencies collecting real-time data reported having a variety of models or formats for sharing real- time data. The Charlotte Area Transit System stated that [f]or the bus system, real-time vehicle departure data is transmitted and displayed on digital signage at CATS' main transportation center via a SOAP interface with the AVL system. This data is also announced audibly at the trans- portation center for ADA compliance. CATS' customer service call center also has the ability to provide real-time lo- cation and adherence information to customer on demand. Bus APC data, while collected and transmitted in real- time, is not currently shared with the general public. For the rail system, the SCADA system provides train data that is collected based on track occupancy, and train movement information is provided as audible and visual messages at each station. Dallas Area Rapid Transit said: "The data is stored and utilized in its simplest form: · Time stamp­date and time that the record is collected. · Latitude. · Longitude. · Vehicle Id number--burned to an EPROM on the MDU and transmitted in the data stream."486 The LIRR stated that "[d]ata is shared in the form of free form text messages and display screens." Simi- lar to the foregoing response, the only format the Maryland Transit Administration uses "for external real- time data sharing is plain text." WMATA stated that it shared "the data via various media, such as the Metro Web site, at www.wmata.com, Interactive Voice Response (IVR) on phone lines, and LED signs at rail and bus stations. The real-time data for rail and bus schedules are provided in PDF and GTFS file formats, and via RSS feeds." E. Paying for Collection of Real-Time Data Of agencies responding that they collect real-time data, 25 said that collection was paid for by the gov- ernment, whereas 10 agencies said that a government entity did not pay for the cost of collecting the data. One agency (AC Transit) stated that originally the government had paid the cost of collecting real-time data as the result of a federal grant.487 F. Archival of Real-Time Data As for whether and for how long agencies archive real-time data, 23 agencies responded that they ar- chived the data; however, as indicated by Table 6 below, the responses varied considerably regarding the length of time that the data are archived. 486 The agency also states that readers should see http://m.dart.org for the agency's initial rollout of the data to the public and "[a]t this time, we are not seeking to generate revenue from this data stream. Vehicle arrival predictions are being provided to the transit customer at no charge and we have not sought sponsorship from private companies to attempt to generate revenue from providing this service to our customers." 487 Three agencies did not respond to the inquiry regarding whether a government agency paid for the cost of collecting real-time data.

44 Table 6. Duration of Archival of Data Period of Time in Years, No. of Agencies Responding Months, or Days Indefinitely 6488 10 years 1 7 years 1 3 years 1 2 years 1 (bus arrivals only) 13 months 1 1 year 4489 9 months 1 6 months 1 3 to 6 months 1 90 days 2 30 days 1 2 weeks 1 1 day 1 (train arrivals only) As for specific responses, AC Transit stated that "[f]or the AVL system there is a long-term database that stores data for 3 months. For NextBus, they do not archive the real-time predictions, but do archive the AVL data." According to BART, "[m]ost real-time data is ephemeral, but some is archived as required for regula- tory compliance." The LIRR advised that [d]ata for the ArcGis, AVLM and WMDS systems is transmitted by an Oracle wireless connection to a database and is archived for six months. After six months the information is routed to a warehouse for permanent storage. PIS/ASI and M7 data is temporarily retained and has no permanent storage process. For these two systems infor- mation is stored up to 2100 entries and then information is purged based on seniority of the information (the oldest being purged first) once that capacity is reached. WMATA stated that it archived data for bus and rail trips: "Predictions for train arrival information are kept for 1 day. Predictions for bus arrivals are kept for 2 days." G. Sharing of Real-Time Data 1. Reasons for Sharing Real-Time Data As seen in Table 7, of the 34 agencies reporting that they collect real-time data, 17 agencies are presently sharing their real-time data, whereas 17 are not.490 488 One agency responded that it archived the data on-site for 1 year and thereafter off-site indefinitely. Another agency reported that it archived data without a "set duration." 489 One agency reported that it archives data on-site for 1 year and thereafter off-site without a "set duration." 490 One agency's response was not clear; another agency responded that it was willing to share its real-time data.

45 Table 7. Agencies Responding to the Survey Reporting They Share Real-Time Data No. of Agencies Collecting and 17 Sharing Real-Time Data No. of Agencies Collecting But 17 Not Sharing Real-Time Data As for any laws and regulations that are or would be applicable to an agency's shared-use or protection of real-time data or that require that collected data be made publicly available, 22 agencies stated that there are none; 1 agency responded that the city had an administrative regulation concerning the protection of information; and the other agencies did not respond to the inquiry.491 Although there was some overlap in the reasons given for sharing real-time data, as indicated in Table 8 below, of the agencies that responded to the question, most agencies identified customer service as the prin- cipal reason. Table 8. Agencies' Reasons for Sharing Real-Time Data Reason Stated for Sharing No. of Agencies Responding Build confidence in service reli- 1 ability Customer service (e.g., conven- 6 ience, improve ridership, integ- rity in trip-plans, provide en- hanced information) Increase advertising 1 Increase ridership 1 Provide real-time arrival predic- 1 tions (e.g., communication and trip planning) AC Transit stated that it provides real-time passenger information through NextBus on the internet and signage at stations and bus shelters. Currently AC Transit is working on providing the regional funding body, MTC, with a data stream for real-time passenger information. It is unsure at this time as to how they will then provide this information to the public. As for its reasons for sharing real-time data, BART stated that it had been sharing transit data with other public agencies, including a metropolitan planning organization, for about 12 years. These other agencies [that] present BART data on various websites, in electronic displays and in brochures, posters and other printed materials. BART opened a public schedule data feed in 2007 and a public real time data feed in 2008. 491 Seven agencies responded by identifying their public records disclosure act, a topic discussed in pt. VII, supra.

46 With no in-house developers to create new applications, and in a time of extremely limited budgets, we view our open data initiatives as an ideal way to foster new and innovative services that directly benefits customers. As an agency BART is accustomed to sharing transit data and we're used to seeing it presented by others. Many agencies have historically exercised tighter controls, but for us the idea of sharing may have been easier given our history. (Emphasis supplied.) The Maryland Transit Administration stated: Real-time data is shared via Next Vehicle Arrival electronic signs at selected bus stops. Also, commuter rail train status is provided via text to mobile devices using the MARCTracker system. In addition, text based service adviso- ries are provided on our web site, via telephone, and to radio and TV media outlets. These are all aimed at improv- ing customer service and providing feedback for future projects to expand the availability of real-time data. (Empha- sis supplied.) The LIRR said: Operations Systems supports train movement, on time performance reporting and passenger information business functions. Systems supported by this section assist the LIRR's Transportation Department with monitoring the movement of trains, the associated equipment schedule and recording the location of each train over its entire run. For its customers, the use of train location information keeps customers informed automatically as to the train's lo- cation and on-time performance. For LIRR's Information Technology Department, via TIMACS and delay analysis, actual train information is used for corporate on-time performance reporting. (Emphasis supplied.) WMATA stated that it shared its scheduling data in GTFS format on its Web site "for anyone to download and publish via web site or mobile applications." WMATA further stated: The information provides a major convenience to the riders by letting them know where their bus or train is located and how long it will be before it arrives at a specific station. We share the data via various media, such as the Metro Web site, at www.wmata.com, Interactive Voice Response (IVR) on phone lines, and LED signs at rail and bus stations. The real-time data for rail and bus schedules are pro- vided in PDF and GTFS file formats, and via RSS feeds. (Emphasis supplied.) 2. Reasons for Not Sharing Real-Time Data Of the 18 agencies not sharing their data, many did not give a reason. Of those agencies that did provide a reason for not sharing data, their reasons were: the agency had just begun collecting real-time data; the agency had a first generation AVL system that was not capable of "interfacing" with systems beyond its own dispatch office, but the transit agency was in the process of installing a new system; there had been no re- quests for the data; the data was not "100 percent" complete or accurate and thus were not reliable for the public's use; the AVL project was not fully operational; there was a lack of well-developed regional architec- ture to share the real-time data; there was no requirement for sharing the data; or the agency was still in the process of planning a system for the collection of real-time data. 3. Benefits of Sharing Real-Time Data In addition to the responses discussed below, although there was some overlap in the responses to the survey questions, two agencies said that providing real-time data had improved service and increased rider- ship; two agencies said that there had been a reduction in complaints; one agency reported that there had been an improvement in customer relations; and two agencies reported an improvement in customer service. One agency said that the sharing of real-time data had improved operational efficiency; another agency cited an improvement in customer communication. Three agencies responded that no benefits could be identified as yet; that it was "too soon to tell"; or that there were no data because the agency's system was relatively new. Dallas Area Rapid Transit's response was that the agency had "not attempted to quantify increases in ridership, re- duction of complaints or other positive impacts providing this data might have achieved. The real time data sets are used extensively by transportation management to monitor operator performance and calculate On-Time perform- ance and route segment level running times for schedule optimization."

47 The LIRR stated that there are benefits from sharing real-time data: Keeping customers informed is beneficial because it has the effect of improving customer relations, which is meas- ured by annual surveys. There are different mechanisms in place that have helped to improve customers' travel ex- periences. An example of this is Notification Alerts. This new and expanded alert system allows subscribers to re- ceive email and text messages for alerts about LIRR train movement, as well as travel information from other MTA agencies. Information is communicated in real time to assist customers with planning travel arrangements. The Maryland Transit Administration responded that "[t]he data has enhanced MTA's image as a cus- tomer-friendly organization and has assisted our customers in accessing transit services." BART's detailed explanation of benefits stated that "value" is created when third parties promote transit services through their use of open data. Anecdotally, as far as "effects" are concerned, open data initiatives have allowed BART to reach more customers in more places than otherwise would be possible: · There are dozens of mobile apps, free and fee, for Android, BlackBerry, iPhone, J2ME, and other mobile platforms (see http://bart.gov/apps). In fact, there is literally competition among developers over who can serve BART custom- ers "best" on these platforms (e.g., there are four BART apps on iPhone alone). This sort of competition is extremely beneficial for customers. · There are BART apps for Facebook and Twitter (See http://bart.gov/apps), which supplement BART's existing presence in these social channels. · There are BART real-time ETA displays in cafes, buildings, and shopping malls that use our open data services (See http://bart.gov/display). BART did not fund the capital, maintenance, or operation costs for these displays, which essentially advertise BART services for free. In addition, providing open-format data: · Creates a perception that BART is more "open" and transparent than other agencies that don't share their data; · Allows BART to benefit from the "halo effect" of being involved in so many innovative third-party platforms and uses; · Allows BART to build partnerships with a local developer community--an important stakeholder segment in the San Francisco Bay Area; · Has not adversely impacted Web site traffic; · Has not resulted in lower quality information / incorrect information for customers; · Has not confused customers about the origin or location of "official" BART information; [and] · Has not generated additional customer services complaints. WMATA similarly states that [f]or the most part, sharing the real-time data has resulted in improvements in customer relations, including a re- duction in customer complaints. The introduction of real-time NextBus information, as when the electronic Public Information Display Signs (PIDS) were deployed, has generated quite a few positive comments from customers and garnered some positive press. Overall bus and rail complaints have increased, and it is not possible to determine whether the availability of real-time information affected the number of complaints 4. Use of Real-Time Data to Increase Advertising Revenue As for whether the agencies are sharing real-time data to increase advertising revenue, only 1 replied that it was; 32 agencies replied that they had not previously used, nor are presently using, real-time data to increase advertising revenue. The Maryland Transit Administration reported that "[a]dvertising was previ-

48 ously considered for MARCTracker, but currently there is no use of real-time data to increase advertising revenue." WMATA reported that it was "in the RFP process for the `Metro Channel' which intends to sup- plement the Metro advertising system with real-time data."

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