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 26
16 (37.9%) and audits (31.0%) are other common methods for (11) have set fare evasion goals and 27.6% (8) have set making the counts. In one case, a formula is used based on the inspection goals. The goals average 4% for fare evasion and percentage of the type of revenue collected and total ridership. 10% for inspection. One agency has a goal of 1,000 inspec- tions each day. A summary of respondents follows: TABLE 8 COMPARISON OF RATIO OF CITATIONS TO WARNINGS No. Agencies ISSUED That Set Goals Range Average Ratio of Number of Citations to Number of Warnings Issued n % Fare evasion rate goals 11 2.15% to 15% 3.8% 10.0 or over 2 11.1 4.09.9 4 22.2 Inspection rate goals 8 3.5% to 25% 9.6% 1.03.9 5 27.8 The survey inquired as to recent actions taken to reduce Less than 1.0 7 38.9 fare evasion. Table 11 indicates that the primary action Total responding agencies 18 100.0 is implementation of a special sweep involving 100% inspection of riders; 75.9% (22 of 29) employ this action. Hiring more inspectors (34.5%) is the second likeliest tac- TABLE 9 tic, and engaging the assistance of local law enforcement HOW FARE EVASION IS SURVEYED agencies (27.6%) is the third likeliest. Other reported tac- Method n % tics include Inspector counts 19 65.5 Internal agency audit function 9 31.0 · Redeployed, saturated, and focused on customer education/assistance; Independent audits by contractor 2 6.9 · Addressed attendance issues with inspectors and focus Periodic samples by agency staff 11 37.9 on increasing the inspection rate; Periodic samples by another public entity 1 3.4 · Added TVMs at one high-volume station and also Automatic passenger counters 7 24.1 added bolder, clearer graphics on the machines; Other 1 3.4 · Engaged and educated passengers; · Expanded duties of field operations personnel to pro- Total responding agencies 29 vide authority to inspect fares; Multiple responses allowed; percentages do not add to 100%. · Varied fare inspection schedules; and · Implemented special sweep tactics, but then had to The survey found that most operators are satisfied with scale them back because of community concerns. the accuracy of their estimates of fare evasion. As shown in Table 10, 86.2% of respondents indicated being satisfied or better. One of 29 expressed extreme dissatisfaction with the TABLE 11 accuracy of its fare evasion counts. ACTION(S) TAKEN TO REDUCE FARE EVASION Action n % TABLE 10 Increased budget 4 13.8 SATISFACTION WITH FARE EVASION STATISTICS Hired more inspectors 10 34.5 Level n % Implemented special sweep tactics 22 75.9 Extremely satisfied 5 17.2 Increased overtime for inspectors 4 13.8 Very satisfied 10 34.5 Engaged the assistance of local law 8 27.6 Satisfied 10 34.5 enforcement agencies Not satisfied 3 10.3 Added turnstiles/gates at some stations 1 3.4 Extremely dissatisfied 1 3.4 Other 8 27.6 Total responding agencies 29 100.0 No special actions taken 1 3.4 Total responding agencies 29 Multiple responses allowed; percentages do not add to 100%. MEASURING PERFORMANCE The 11 agencies that set inspection goals were asked The survey found that a majority of agencies do not have whether the goal is adjusted on a regular basis. Table 12 either evasion or inspection goals. Of 29 respondents, 37.9% shows the results: Two agencies indicated yes--one noted
OCR for page 27
17 that the rate was adjusted at least monthly and another Reporting on fare evasion was found to be a normal part responded that it varies on the basis of changes in the eva- of the agency's performance reports for 86.2% (25 of 29) of sion rate. the operators. Table 13 shows that, of the 25 that regularly report on performance, the most common report (60%) is TABLE 12 monthly. Another 28% of the operators report quarterly. The INSPECTION RATE ADJUSTMENT BASED ON THE table can also be used as a guide for operators wishing to MEASURED EVASION RATE view example reports from any of the agencies. Adjustment n % Yes, on a regular basis, at least monthly 1 9.1 Fare evasion statistics are reported in different ways, Yes, varies depending on evasion rate trend 1 9.1 as shown in Table 14. A vast majority include evasion rate (84%, or 21 of 25). Most also report numbers of citations and No 9 81.8 warnings issued (76% and 64%, respectively). In addition, Total responding agencies 11 100.0 two operators noted the following: TABLE 13 SUMMARY OF FARE ENFORCEMENT PERFORMANCE REPORTING BY OPERATOR Operator Regular Report Made? Weekly Monthly Quarterly Annual Other Baltimore--Maryland Mass Transit Administration Yes l l l Buffalo--Niagara Frontier Transportation Authority Yes l Calgary Transit Yes l Charlotte Area Transit System Yes l Greater Cleveland Regional Transit Authority No Dallas Area Rapid Transit Yes l Denver--Regional Transit District Yes l Edmonton Transit System Yes l Eugene--Lane Transit District Yes l Everett--Community Transit No Houston--Metropolitan Transit Authority of Harris County Yes l Las Vegas--Regional Transit Commission of Southern Nevada Yes 1 1 1 1 Los Angeles County Metropolitan Transit Authority Yes 1 MinneapolisSt. Paul--Metro Transit Yes 1 Newark--NJ Transit Yes 1 1 New York City--MTANew York City Transit Yes l OceansideNorth San Diego County Transit District No Ottawa Regional Transit Commission Yes 1 Phoenix--METRO Light Rail Yes 1 Portland--Tri-County Metropolitan District of Oregon Yes 1 Sacramento Regional Transit District Yes 1 Salt Lake City--Utah Transit Authority Yes l San Diego Metropolitan Transit System Yes l San Francisco Municipal Transportation Agency Yes l San Jose--Santa Clara Valley Transportation Authority Yes l Seattle--Sound Transit Yes l St. Louis--Bi-State Development Agency Yes l Vancouver--TransLink/SkyTrain No York Region Transit/Viva Yes l l Total 25Yes 3 15 7 5 2 4No There were 29 responding agencies; "Other" were (1) New York City "as requested" and (2) San Diego MTS "semiannual."
OCR for page 28
18 · "We have `education' categories where the officer operators. For the other transit modes, data were obtained for shows the customer how to use the TVM. There are CR (5 operators), BRT (6), bus (1), and HRT (1). subcategories that include those who comply and buy a fare or noncompliance if they choose not to buy a Evasion Rates (Figure 2) fare. We have a courtesy ride category and a `took off' category where we track those who exit the vehicle or · The range for 31 operations was from 0.1% to 9.0%. platform when they see an officer approaching." · The average across all modes was 2.7%, and the · "We include enforcement rate [or the rate of fining, median was 2.2%. defined to be equal to the number of citations/(number of citations + number of warnings)]." Inspection Rates (Figure 3) · The range in rates, 23 in all, was from 0.4% to 30.0%. TABLE 14 · The average across all modes was 11.3%, and the MEASURE OF FARE EVASION PERFORMANCE median was 9.2%. Measure n % Number of citations issued 19 76 When viewing the data across transit modes, the limited experiences for all but LRT prevented any conclusion other Number of warnings issued 16 64 than that the rates are generally similar for all modes. Other Number of inspections 15 60 factors (e.g., operating environment, time of day, day of Evasion rate (evasions/rider) 21 84 week, on-board loads) are likely to be more of an influence Inspection rate (inspections/rider) 13 52 on the evasion rate than service mode. Other 4 16 When evasion rates are compared with inspection rates Total responding agencies 25 for those where paired data are available, as displayed in Multiple responses allowed; percentages do not add to 100%. Figure 4, no direct correlation is found. There is a wide scattering of evasion rates where inspection rates are less From the survey and follow-up contacts, current data on than 20%. A similar chart was developed for the TCRP fare evasion and inspection rates were collected from 22 Report 80 data and is displayed in Figure 5. As with current of the operators using PoP fare collection. The results are experience, no direct correlation between the evasion and shown in Figures 2 and 3. Data were reported for 19 LRT inspection rates is shown. However, a wide scattering of FIGURE 2 Survey of evasion rates.
OCR for page 29
19 FIGURE 3 Survey of inspection rates. FIGURE 4 Evasion rates vs. inspection rates--2011. evasion rates is shown, mostly for inspection rates greater reporting issues related to measuring fare evasion that than 15%. compromise transferability: Operators and researchers making use of the evasion 1. There are definitional issues on what is included as and inspection data are advised to be careful about the "evasion." The definition used in the TCRP Report 80 transferability of any of the data. There are a number of and in this study includes warnings issued. Follow-
OCR for page 30
20 FIGURE 5 Evasion rates vs. inspection rates--TCRP Report 80. ing are the definitions of evasion and inspection rates becomes a 100% sample and the definition of fare used in this study: evasion rate becomes. Fare evasion rate--The percentage of passengers Fare evasion rate (100% inspection)--The percent- inspected who DO NOT possess adequate PoP. Further, age of passengers inspected that DOES NOT possess evasion is defined to be the total number of violators adequate proof of payment during a zero-tolerance, (i.e., warnings and citations) rather than citations alone. 100% inspection. Further, evasion is defined as the total number of violators (i.e., warnings and citations) Inspection rate --The percentage of the agency's total rather than citations alone. passengers [i.e., on the PoP service(s)] who have been approached by a fare inspector and requested to pro- 5. Finally, there are deployment techniques that will duce PoP. influence the evasion numbers, either up or down depending on the method and its objective. "Heavy" 2. There is the agency's policy with regard to issuing enforcement when inspections increase for a short warnings and the discretion permitted the inspec- period of time can tamp down the evasion rate as tor. As noted in the discussion of Table 8, among 18 word spreads. The use of discretion can be modified responding agencies, the number of citations issued further, spiking or diminishing the numbers. average 3.5 times the number of warnings issued. Eight operators do not keep records of warnings. To gain further perspective on the variance in the fare evasion statistics, rates obtained through follow-up with sev- 3. There is the issue with regard to sampling technique. eral operators were compared for five systems (four LRT and To obtain a statistically reliable count of evaders one CR) over a 12- to 14-month period. This comparison is requires a technique that covers the route's or sys- summarized in Table 15, showing the spread in fare evasion tem's geography, at all times of the day and week. rates (i.e., low to high over that period) and the average over Such a technique will account for the normal variance the 12- to 14-month period. inherent in daily ridership patterns and numbers for any operator. There is no standard industry approach. During a 12-month period, quite a spread can be seen for Operator B, ranging from a low of 1.34% to a high of 4. Some operators use monthly systemwide statistics for 4.84% over a 14-month period. For Operator A, its highest calculating the evasion rate and others use samples rate (2.93%) was more than 5 times its lowest rate (0.58%) based on 100% sweeps. With the latter, the basis over 12 months.