Post on 27-Apr-2018
TRB Paper #11-2016New York City Transit Slide 1
Measuring & Controlling Subway Fare Evasion: Improving NYCT’s Safety and SecurityAlla Reddy, Jacqueline Kuhls,
and Alex LuOperations Planning
Office of Management & BudgetNew York City Transit Authority
Presented at the 90th Annual Meeting of the Transportation Research Board
Washington D.C. (2011)
T R A N S I T
Notice: Opinions expressed in this presentation are those of the authors and do not necessarily reflect the official policy or position of Metropolitan Transportation Authority or MTA New York City Transit.New York City Transit
Photo: NYC Transit DRAW
TRB Paper #11-2016New York City Transit Slide 2
• Fare evasion measured by station agents since early 1990s
• Reduced from 6.9% to supposedly about 0.2% because of:
– New AFC system– Graffiti control– Police patrols– Civil penalties– General crime reduction
• Renewed concerns:– Booth destaffing program– Fare increases– ‘Panic bars’ on exit gates
Background
Photo: NYC Transit DRAW
TRB Paper #11-2016New York City Transit Slide 3
Fare Collection Hardware
Booth(Full Time & Part Time) HEETs
HXT(Not surveyed)
Painted HXT(Not surveyed)
Photos: NYC Transit DRAW
TRB Paper #11-2016New York City Transit Slide 4
Fare Tariff & Defining Evasion
• Official methods:– Children under 44”
• Must crawl under turnstile• Not allowed alone
– Passengers with bulk items, school field trips• Request agent assistance• Enter through gate
– ‘Block’ or half-fare tickets• Surrender paper ticket• Enter through special entry
turnstile• Unofficially:
– Riders open gates for paid passengers with bulk items
– Children squeeze through high-wheels with paid adults
– Flash passes, uniforms, contractors go through gates
TRB Paper #11-2016New York City Transit Slide 5
Turnstile Fare Evasion MethodsUnder Bump
Over Backcock
Photos: NYC Transit PID Camera Footage
TRB Paper #11-2016New York City Transit Slide 6
Gate Left Open
Opportunistic
Questionable
Gate Fare Evasion Methods
Backcocks, then use panic bar to open gate Catches gate to enter after others exit
Opens unlocked gate to enter, or gate ajar Police opens gate for stroller, bystander enters
1 2
1 2
Photos: NYC Transit PID Camera FootageDeliberate
TRB Paper #11-2016New York City Transit Slide 7
Observation MethodologyEvasions Questionable Legal Entries
Traditional Turnstile• Under (over 44”)• Jump• Backcock• Bump
(a) Low TS(b) HEET
Gate (Panic Bar)• Opportunistic• Deliberate• Gate Left Open
Tracked• School Group• Police/Fire/Court:
(a) Badge(b) Uniform
• Flash Pass• Open Gate with Key:
(a) TA key(b) Emergency key
• “Other”Not Tracked• Selling ‘Swipes’• MetroCard passback
• Normal Turnstile Entry
• Normal HEET Entry• Child under 44”, with
fare-paying adult• Paper Ticket• Bulk Item
• Discreet observations in half-hour periods divided into six-minute blocks; stratified sample (income and throughput); capture unusual activity only. Entries recorded in one of 19 categories.
TRB Paper #11-2016New York City Transit Slide 8
Data Collection Forms
TRB Paper #11-2016New York City Transit
TRB Paper #11-2016New York City Transit Slide 9
Subway Fare Evasion Trends
• Systemwide: 1.3%• By time period:
– Peak periods: ~0.9%• more evasions per hour • but lower rates per passenger
– Midday and nights: 1.3%~1.9%• high evasion rates• but not many evaders
– School hour: almost 3.0%• highest evasions per psgr
• By system entry rate:– Busy stations: ~0.5%
• low per-passenger rates• high per-hour rates (8.0 /hr)
– Quiet stations: up to 5.5%• high per-passenger rates• low per-hour rates (<1.0 /hr)
Weekday Evasion by Hour
0.0%
0.5%
1.0%
1.5%
2.0%
2.5%
3.0%
3.5%
4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 0Hour of Day
Fare
Eva
sion
Rate
(per
Psg
r)
0
100
200
300
400
500
600
700
800
900
1,000
Syst
em E
ntry
Rat
e (Ps
gr/H
our)
Ev asion per PsgrEntries per Hour
Sample size = 124,069 entries
Weekday Evasion by System Entries*
0.0%
1.0%
2.0%
3.0%
4.0%
5.0%
6.0%
0.02
(0.0
1~0.
02)
0.04
(0.0
3~0.
04)
0.06
(0.0
5~0.
07)
0.09
(0.0
8~0.
10)
0.12
(0.1
1~0.
13)
0.16
(0.1
4~0.
18)
0.21
(0.1
9~0.
22)
0.26
(0.2
3~0.
27)
0.31
(0.2
8~0.
33)
0.39
(0.3
4~0.
42)
0.48
(0.4
3~0.
52)
0.61
(0.5
3~0.
69)
0.84
(0.7
0~1.
00)
1.66
(1.0
1~5.
56)
Avg & Range, System Entries per Hour (Thousands)
Fare
Eva
sion
Rate
(per
Psg
r)
0.0
1.0
2.0
3.0
4.0
5.0
6.0
7.0
8.0
9.0
Fare
Eva
sion
Rate
(per
Hou
r)
Ev asion per PsgrEv asion per Hour
* Ex cludes afternoon school discharge hour (15:00-15:59)
Sample size = 170,615 entries
Quiet
sta
tions
Busy
sta
tions
TRB Paper #11-2016New York City Transit Slide 10
Seasonality of Fare Evasion
0.0%
0.2%
0.4%
0.6%
0.8%
1.0%
1.2%
1.4%
1.6%
1.8%
2.0%
09/0
4~09
/06
09/0
5~09
/07
09/0
6~09
/08
09/0
7~09
/09
09/0
8~09
/10
09/0
9~09
/11
09/1
0~09
/12
09/1
1~10
/01
09/1
2~10
/02
10/0
1~10
/03
10/0
2~10
/04
10/0
3~10
/05
10/0
4~10
/06
10/0
5~10
/07
10/0
6~10
/08
Reporting Period (Rolling Average)
Fare
Eva
sion
Rate
(per
Psg
r)
0.0
1.0
2.0
3.0
4.0
5.0
6.0
7.0
8.0
Fare
Eva
sion
Rate
(per
Hou
r)
Ev asion per PsgrEv asion per Hour
Sample size = 37,269 entries per period
Evasion Trends: Income & Season• By median income
– Higher evasions observed in stations where adjacent census tract median income < $30k
– No effect when income > $30k
• Seasonality– Evasion is more prevalent
during warm summer months• Summer = ~1.7%
Winter = ~0.9%• Consistent with literature on
general crime trends• Seasonal ridership impacts
(trip purpose)
Weekday Evasion by Median Income
0.0%
0.5%
1.0%
1.5%
2.0%
2.5%
6~18
18~2
4
24~2
8
28~3
2
32~3
6
36~4
2
42~4
8
48~6
2
62~7
0
70~8
6
86~1
76
Station Median Income Range ($ Thousands)
Fare
Eva
sion
Rate
(per
Psg
r)
0.0
1.0
2.0
3.0
4.0
5.0
6.0
7.0
8.0
Fare
Eva
sion
Rate
(per
Hou
r)
Ev asion per PsgrEv asion per Hour
* Ex cludes afternoon school discharge hour (15:00-15:59)
Sample size = 167,817 entries
TRB Paper #11-2016New York City Transit Slide 11
Combating Fare Evasion• Properly locking service
access gates at all times• Improve communication of
child height restrictions• Fare control configuration
and staff presence don’t seem to have much effect– Gate evasion rates:
0.9% unstaffed, 1.0% staffed– High-wheel evasion rates:
1.2% unstaffed, 1.0% staffed• Tackling organized fare
abuse operations (swipers)– Vending machine vandalism
costs repair expenses– Swiping impacts revenue– Work with NYPD Transit
Bureau and community courts– Use video evidence if availablePhoto: NYC Transit DRAW
TRB Paper #11-2016New York City Transit Slide 12
Fare Enforcement Issues
• Legal framework– New York’s rules were well
established by the 1980s– Important clarifications:
• arrest versus summons• undercover enforcement
permissible?• arresting powers• dispute/appeals process
– Expected fines versus fares• New York’s fine = $100• progressive?• “street economics”
• “Surge” enforcement• Video recording cameras
– Shared use for anti-terrorism
TRB Paper #11-2016New York City Transit Slide 13
Public Relations
Reprinted with permission © 2010 New York Daily News.
TRB Paper #11-2016New York City Transit Slide 14
Conclusions & Future Work• Multi-pronged approach is
required to manage evasion– AFC security & audit features– Legal enforcement framework – Data collection & analysis to
identify ‘hot spots’– Task-force based approach – Comprehensive press strategy
• Information sharing is key– Crime of opportunity– Controls are necessary
• Future work– Measurable benefits of fare
enforcement– Evader-criminal correlation– Countermeasure effectiveness– Socio-demographic patterns
Photo: NYC Transit DRAW
TRB Paper #11-2016New York City Transit Slide 15
Acknowledgements
• Ben Lonner, KishorSharma, Justin Serina– MTA Audit Services
• Raymond Diaz, Edward O’Brien, Jim Donovan– NYPD Transit Bureau
• NYCT Colleagues in– System Data & Research– Automated Fare Collection– Office of Management &
Budget
• TRB AP030 Committee’s Anonymous Reviewers
Notice: Opinions expressed in this presentation are those of the authors and do not necessarily reflect the official policy or position of Metropolitan Transportation Authority or MTA New York City Transit.New York City Transit
Photo: Amanda Marsh