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Control AreaPicture
Measuring &
Controlling
Subway Fare
Evasion:
Improving
NYCT’s Safety
T R A N S I T
Photo: NYC Transit DRAW
TRB Paper #11-2016New York City Transit Slide 1
PictureNYCT’s Safety
and SecurityAlla Reddy, Jacqueline Kuhls,
and Alex Lu
Operations PlanningOffice of Management & BudgetNew York City Transit Authority
Presented at the 90th Annual Meeting of the
Transportation Research BoardWashington D.C. (2011)
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
• Fare evasion measured by station agents since early 1990s
• Reduced from 6.9% to supposedly about 0.2% because of:– New AFC system
Background
TRB Paper #11-2016New York City Transit Slide 2
– Graffiti control
– Police patrols
– Civil penalties
– General crime reduction
• Renewed concerns:– Booth destaffing program
– Fare increases
– ‘Panic bars’ on exit gatesPhoto: NYC Transit DRAW
Fare Collection Hardware
Booth(Full Time & Part Time) HEETs
Photos: NYC Transit DRAW
TRB Paper #11-2016New York City Transit Slide 3
(Full Time & Part Time) HEETs
HXT(Not surveyed)
Painted HXT(Not surveyed)
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
TRB Paper #11-2016New York City Transit Slide 4
– ‘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
Turnstile Fare Evasion MethodsUnder Bump
TRB Paper #11-2016New York City Transit Slide 5
Over Backcock
Photos: NYC Transit PID Camera Footage
Opportunistic
Gate Fare Evasion Methods
1 2
Photos: NYC Transit PID Camera FootageDeliberate
TRB Paper #11-2016New York City Transit Slide 6
Gate Left Open Questionable
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
Observation Methodology
Evasions Questionable Legal Entries
Traditional Turnstile
• Under (over 44”)
• Jump
• Backcock
• Bump(a) Low TS(b) HEET
Tracked
• School Group
• Police/Fire/Court:(a) Badge(b) Uniform
• Flash Pass
• Open Gate with Key:
• Normal Turnstile Entry
• Normal HEET Entry
• Child under 44”, with fare-paying adult
• Paper Ticket
• Bulk Item
TRB Paper #11-2016New York City Transit Slide 7
Gate (Panic Bar)
• Opportunistic
• Deliberate
• Gate Left Open
(a) TA key(b) Emergency key
• “Other”
Not Tracked
• Selling ‘Swipes’
• MetroCard passback
• 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.
Data Collection Forms
TRB Paper #11-2016New York City Transit Slide 8TRB Paper #11-2016New York City Transit
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
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 0
Hour of Day
Fare Eva
sion Rate (per Psg
r)
0
100
200
300
400
500
600
700
800
900
1,000
Sys
tem Entry Rate (Psg
r/Hour)
Ev asion per Psgr
Entries per Hour
Sample size = 124,069 entries
Weekday Evasion by System Entries*6.0% 9.0
TRB Paper #11-2016New York City Transit Slide 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 System Entries*
0.0%
1.0%
2.0%
3.0%
4.0%
5.0%
6.0%
0.02
(0.
01~0
.02)
0.04
(0.
03~0
.04)
0.06
(0.
05~0
.07)
0.09
(0.
08~0
.10)
0.12
(0.
11~0
.13)
0.16
(0.
14~0
.18)
0.21
(0.
19~0
.22)
0.26
(0.
23~0
.27)
0.31
(0.
28~0
.33)
0.39
(0.
34~0
.42)
0.48
(0.
43~0
.52)
0.61
(0.
53~0
.69)
0.84
(0.
70~1
.00)
1.66
(1.
01~5
.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 Hour)
Ev asion per Psgr
Ev asion per Hour
* Ex cludes afternoon school
discharge hour (15:00-15:59)
Sample size = 170,615 entries
Qui
et s
tatio
ns
Bus
y st
atio
ns
Seasonality of Fare Evasion2.0% 8.0
Evasion Trends: Income & Season
• By median income
– Higher evasions observed in stations where adjacent census tract median income < $30k
– No effect when income > $30k
Weekday Evasion by Median Income
0.0%
0.5%
1.0%
1.5%
2.0%
2.5%
6~18
18~2
4
24~2
8
28~3
2
32~3
6
36~4
2
42~4
8
48~6
2
62~7
0
70~8
6
86~1
76
Station Median Income Range ($ 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 Hour)
Ev asion per Psgr
Ev 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 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 Hour)
Ev asion per Psgr
Ev asion per Hour
Sample size = 37,269 entries per period
• 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)
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
TRB Paper #11-2016New York City Transit Slide 11
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
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
TRB Paper #11-2016New York City Transit Slide 12
• 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
Public Relations
TRB Paper #11-2016New York City Transit Slide 13Reprinted with permission © 2010 New York Daily News.
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
TRB Paper #11-2016New York City Transit Slide 14
• Information sharing is key– Crime of opportunity
– Controls are necessary
• Future work– Measurable benefits of fare
enforcement
– Evader-criminal correlation
– Countermeasure effectiveness
– Socio-demographic patternsPhoto: NYC Transit DRAW
Acknowledgements
• Ben Lonner, Kishor Sharma, Justin Serina
– MTA Audit Services
• Raymond Diaz, Edward O’Brien, Jim Donovan
– NYPD Transit Bureau
• NYCT Colleagues in
TRB Paper #11-2016New York City Transit Slide 15
• 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