Cover Image

Not for Sale

View/Hide Left Panel
Click for next page ( 70

The National Academies of Sciences, Engineering, and Medicine
500 Fifth St. N.W. | Washington, D.C. 20001

Copyright © National Academy of Sciences. All rights reserved.
Terms of Use and Privacy Statement

Below are the first 10 and last 10 pages of uncorrected machine-read text (when available) of this chapter, followed by the top 30 algorithmically extracted key phrases from the chapter as a whole.
Intended to provide our own search engines and external engines with highly rich, chapter-representative searchable text on the opening pages of each chapter. Because it is UNCORRECTED material, please consider the following text as a useful but insufficient proxy for the authoritative book pages.

Do not use for reproduction, copying, pasting, or reading; exclusively for search engines.

OCR for page 69
69 Integration with the wheelchair lift (or lift sensors) would On the side of operations data, only near-100% penetra- provide a more accurate and automated record of lift use than tion will provide the large sample sizes needed to determine relying on operators to initiate a message. extreme values used in statistically based running time analy- Integration with the destination sign might prove useful to sis and design. With a small fraction of the fleet equipped (as help with matching. in a traditional APC system), large sample sizes can be obtained Integration with a stop announcement system or next by aggregating over time, but at the risk of some of the data arrival system does not bring in any new data; however, it cre- being out of date. ates an incentive for stop matching to be accurate and thereby Headway analysis requires 100% instrumentation on a route benefits AVL-APC data analysis. at a given time, which can only be achieved with either 100% AVL systems have long attempted to use data from the vehi- penetration or careful allocation of the instrumented sub-fleet. cle's mechanical system (in addition to that from the odome- Another benefit of full coverage is the ability to investigate ter), such as oil temperature and air pressure. In real time, complaints. As many complaints arise from extreme events alarms from these systems have delivered so many false posi- (long waits, overcrowding), full coverage would be most help- tives that they tend to be ignored. Whether the recording and ful in such investigations. off-line analysis of mechanical data integrated with location Many transit agencies report that managing the allocation data can deliver new insights on mechanical performance is a of an instrumented sub-fleet can be a large headache and rich area for further exploration. that concerns other than data collection (e.g., who gets the new buses) often control the allocation, frustrating data col- lection plans. 10.4 Fleet Penetration A major motivation for instrumenting only a fraction of the and Sampling fleet with APCs has been their cost. Tri-Met has shown that by AVL systems, when installed, are usually installed on the integrating APCs with an AVL system, the incremental cost of entire fleet. APCs have traditionally been installed on about an APC can be reduced to the $1,000 to $3,000 range; Tri-Met 10% to 15% of the fleet. now treats them as standard equipment included in all new bus Chapter 9 discusses how fleet penetration affects sample purchases. Note that Tri-Met uses a rather simple-technology size, and what sample size need is for passenger countrelated APC and that more complex and (presumably) accurate APCs data items such as load, boardings, and passenger-miles. The may not offer such an attractive incremental cost. general principle is that if the data is used only to determine mean values, small samples are sufficient; however, when 10.5 Exception Reporting versus extreme values are important, a complete or at least large Exception Recording sample is preferred. For passenger count data, 10% penetra- tion is more than enough for boardings and passenger-miles Exception reporting is certainly a valuable management data, for which only mean values are needed. For load on tool, available for use with any AVL-APC data archive. It crowded bus routes, a near-complete sample is desirable so should be distinguished, however, from "exception record- that extreme values can be observed. With a small fraction of ing," the practice of only recording a bus's location if it is off the fleet instrumented, large sample sizes can still be obtained schedule or off route. This protocol of exception recording from crowded routes if the instrumented buses are dispro- does not permit analysis of normal operations and should portionately allocated to crowded routes. therefore be avoided.