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14 CHAPTER 2 Automatic Vehicle Location TCRP Synthesis of Transit Practice 24: AVL Systems for Bus (known) route. All transit coaches have electronic odometers, Transit provides an insightful description of AVL systems and making it easy to integrate odometers into a location system. a review of AVL's history (9). Historically, AVL was developed Route deviations present a problem for odometer-based dead for two real-time applications: emergency response and reckoning, which is one of the reasons GPS is preferred. Some computer-aided dispatch (CAD). CAD represents a major AVL systems include a gyroscope, which makes it possible to advance in complexity, because it involves matching the track a bus off-route using dead reckoning. observed operation to the schedule. AVL has long been adver- Many GPS-based systems often use dead reckoning as a tised as a means of obtaining data to be archived for off-line backup. When GPS signals indicate a change in location incon- analysis as well. That promise, which has seen limited fulfill- sistent with the odometer, dead reckoning takes over from the ment, is the focus of this report. last reliable GPS measurement, until GPS and odometer meas- urements come back into harmony. Odometers require calibration against known distances 2.1 Location Technology measured using signposts or GPS, because the relationship In the last decade, the U.S. government's global positioning between axle rotations (what is actually measured) and dis- system (GPS) has become the preferred location technology. tance covered depends on changeable factors such as tire GPS receivers on vehicles determine their location by triangu- inflation and wear. lation based on signals received from orbiting satellites. Loca- tion accuracy for buses is generally better than 10 m, depending 2.2 Route and Schedule Matching on the accuracy of clocks in the GPS receivers and on whether differential corrections are used. Matching a bus's trajectory to route and schedule is impor- Because GPS requires a line of sight to the satellites, GPS tant for data analysis, as well as many real-time applications signals can be lost as buses pass through canyons, including including CAD and real-time passenger information systems. man-made canyons caused by tall buildings. Tall buildings also The rate at which data is rejected for inability to match it to reflect GPS signals, causing a phenomenon called multipath a route can be substantial, reaching 40% at agencies that were that can lead to erroneous location estimation. For example, on interviewed. Data matching was cited by many agencies as a GPS-driven map display, buses approaching Chicago's Loop the single greatest challenge faced in making their AVL-APC (downtown) appear to jump into Lake Michigan. In a system data useful. intended for real-time monitoring only, predictable errors Some very simple AVL systems perform no matching; they such as this can be tolerated; however, for archived data simply display on a map where the buses are. However, most intended for off-line analysis, errors like this pose a threat to transit AVL systems include CAD, which involves real-time data integrity. In tunnels and covered areas, GPS cannot be matching to route and schedule. Because the most demand- used unless repeaters are installed, as in NJ Transit's Newark ing application in regards to matching is stop announcements City Subway. (because matching errors are so apparent to the public), Older AVL-APC systems, like King County Metro's, use a archived data derived from stop announcement systems should combination of beacons, which serve as fixed-point location be of particularly high quality. devices, and dead reckoning for determining location between In traditional APC systems, which lack a real-time compo- beacons, using the assumption that the bus is following a nent such as CAD or stop announcements, data is matched

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15 off line based on signpost, odometer, and/or GPS reading Data collection systems not tied to the radio, like traditional recorded during operation. APC systems, present a challenge.Agencies are reluctant to force Matching algorithms themselves tend to be proprietary, operators to sign in again to another system when they are developed by AVL vendors or (for APC) developed in house. already signing in to the radio, farebox, and destination sign; As a general rule, the more data available, and the greater its and, if sign-in is not necessary for any real-time operating func- detail and accuracy, the better the matching accuracy is. tion, compliance is sure to be an issue. King County Metro solved this problem by connecting its APCs to the radio control head, which transmits sign-in information to the (otherwise 2.2.1 Route/Run Data and Operator Sign-In independent) APC on-board computer. Matching, whether in real time or off line, is more success- Lacking sign-in data, NJ Transit's APC/event recorder sys- ful when the algorithm doing the matching has prior knowl- tem still tries to take advantage of the scheduled runs that edge of the route and schedule the bus is supposed to be buses follow by using a two-step matching procedure: (1) the following. With the scheduled bus path known, real-time route/run is inferred from pull-out, pull-in, and stop records measurements are then used to verify and update the path. If and then (2) the inferred run is used for stop-level matching. door opening and closing sensors are part of the data collection If matching fails, the system may guess a different route/run. system, each door opening/closing event suggests that a bus is Metro Transit eases the burden on operators while improv- at a stop, permitting a comparison between reported location ing accuracy by providing automated sign-in, communicated and expected next stop location. by wireless link during pull-out, based on vehicle-block assign- In newer AVL systems, the schedule and base map infor- ments made overnight. In its new AVL-APC system, operators mation used for matching are held in the on-board computer. are asked only to verify and correct their sign-in information. Recognizing that schedules often change, many systems pro- Houston Metro improves the accuracy of its route/run data vide for schedule information to be uploaded daily. At King by comparing sign-in data with payroll data as part of routine County Metro, where the older AVL system's on-board com- post-processing. A semi-automated procedure allows an ana- puters cannot hold the full schedule, buses are tracked against lyst to make corrections if there seems to be a simple, cor- the schedule by the central computer; nevertheless, King rectable error, such as a miskeyed run code. County Metro devised and implemented a method for local, real-time matching. About 3 min of running time before each 2.2.2 Base Map Accuracy timepoint, the central computer radios to the bus a message indicating the odometer reading at which the coming time- Without data matching as a driving application, transit point will be located; local sensing and logic will then suffice agencies have little need historically for an accurate stop data- to know when the bus has reached the next timepoint. This base. Many agencies have no stop database, because they do technique substantially improved King County Metro's suc- not own the stops (i.e., the sidewalk space and signs) and cess at matching timepoints. because routes and schedules are detailed only to the time- The main source of route/run data is operator sign-in. point level. Before AVL, stop databases only had to be accurate Sign-in to radio systems is routine in the transit industry, and enough for operators and maintenance personnel to locate the non-compliance is generally limited to a small percentage of stop. However, automatic applications do not forgive errors operators on any given day, because operators who do not sign and omissions the way manual data collection can. Generally, in can be readily detected at the control center. At King County agencies implementing AVL have needed to make a major Metro, for example, operators who fail to sign in can be called effort to correct their stop location database. Some agencies out of service for having a faulty radio, and face possible dis- and vendors have used dedicated crews to field map all stop cipline if the problem turns out to be simple failure to sign in. locations using mobile GPS units. Buses themselves can be Therefore, AVL systems connected to the radio benefit from configured to be those mobile units. getting relatively good-quality sign-in data. The 2002 case study of NJ Transit emphasizes the importance The validity of sign-in data can also be a problem. Accu- of having a good base. On patterns for which at least 90% of the racy will be better if the system taking the sign-in accepts reference locations are coded to within 300 feet of actual, NJ only valid codes for operator number, run number, and so Transit's matching algorithm was able to match 81% of the trips on. Systems in which sign-in errors are not detected until to a scheduled trip and pattern, in contrast to a 65% matching off-line processing cannot benefit from operators correct- rate overall. Starting with a well-calibrated GIS base map based ing their own input errors. As an example, farebox data sys- on aerial photography can reduce the burden of field mapping. tems often have very high rates of sign-in error, making Equally important is maintaining the stop location file for both boarding counts and revenue difficult for agencies to attrib- temporary and permanent changes. Some large agencies report ute to route (10). changing 5% of their 10,000 stops each year.

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16 While AVL-APC systems need accurate bus stop locations, during pull-ins, pull-outs, and deadheads, but the schedul- the location data that AVL-APC systems supply can also be ing system vendor's database excluded those details. Another used to improve the base map. One APC vendor recommends problem is that schedule databases define routes as a series of comparing average GPS coordinates at observations of a stop timepoints, not stops, while an AVL or APC system doing to its reference coordinates, updating the base map if the obser- stop-level tracking sees a route as a sequence of stops. vations are consistent. One complicating factor is that different enterprise systems 2.2.4 Control-Ordered Schedule Changes scheduling, facilities, transportation, passenger information systems such as on-line trip planners, and traffic manage- Route and schedule matching becomes complicated when mentuse the term "bus stop" for different functions, leading buses do not exactly follow their assigned block. Examples to slightly varying definitions that often entail differing loca- are when a bus breaks down, when buses are short-turned or tions. A transit agency can have four or more definitions of inserted into the schedule to try to balance headways, or stop location (11): when buses swap duties. In such cases, capturing informa- tion about schedule changes ordered by dispatchers can ease Intersection or landmark (e.g., Third and Main) the task of matching. Intersection quadrant If the change is simply that a bus assumes a new block or run, Nominal coordinates along an ideal route, often following that information can be captured through (a fresh) sign-in. the roadway centerline Otherwise, to the researchers' knowledge, no method has yet Coordinates of the point on the curb closest to the bus been developed for capturing control-ordered schedule changes stop sign in a form suitable for automated processing. At King County Metro, for example, the AVL/radio database includes con- Additionally, the complication of determining coordinates, troller logs indicating changes to bus and operator assignments; which may differ between location system and the base map, however, those records need to be interpreted manually. introduces a possible calibration problem. A recently pub- lished U.S.DOT report on location referencing offers valuable guidance for making location accurate and consistent across 2.2.5 End-of-Line Identification data systems (12). End-of-line operations can be both complex and unpre- dictable, making a trip's start and end times difficult to identify. 2.2.3 Schedule Integration One reason such identification is difficult is that terminals are often located where GPS accuracy is worst--near tall down- Thanks to the near-universal adoption of automated sched- town buildings or in a covered terminal. uling, route and schedule data is always imported from the A second reason is the unpredictability of operations at scheduling system. The schedule database tends to be accurate route ends. Operators approaching the end of the line with an and carefully maintained because of its critical role in opera- empty bus may feel free to deviate from the prescribed route tions and payroll. (e.g., to stop at a sandwich shop, thereby spending their layover In large cities, transit schedules tend to be extremely at a different location). At the terminal, an operator getting in dynamic, with route, vehicle, and operator schedules changing and out to adjust a mirror can be mistaken as passengers getting almost daily. It is therefore vital to the performance of AVL to off and on and a stop being served. Operators may open and have a mechanism for keeping the schedule up to date. Many close doors several times to let passengers board during layover AVL systems reload the entire schedule to bus on-board com- periods, which makes door closing an inadequate criterion for puters daily at pull-out. inferring departure from the stop. A vehicle jockeying for posi- Several transit agencies have reported difficulties in inte- tion in a layover area may be mistaken for an early departure. grating the schedule database with AVL, sometimes delaying a For these reasons, several agencies report treating first and project for years. The desire for a standard interface was echoed last segment running time data with some skepticism. Some by many transit agency and vendor representatives. Even agencies simply exclude first and last segments from running though there are only two major schedule software suppliers, time analysis, forcing them to assume a fixed running time on databases tend to be highly customized to each transit agency's those extreme segments. Not being able to track operations particular routing, schedule, and work rules practices; there- from the start to the end of a line compromises the integrity fore, a standard interface, even for a single scheduling system of route-level running time analyses such as determining vendor, can be elusive. periods of homogeneous running time and the sufficiency of In one case, the problem that had to be overcome was that recovery time. the AVL vendor's software expected that the schedule data- Agencies have used various means to improve end-of-line base would have details concerning the path taken by buses identification. King County Metro made its tracking algorithm