Dale Gedcke, B.Eng., M.Sc., Ph.D.
Marketing & Technical Consultant
Oak Ridge, TN
OR RLC Presentation 5-18-08.ppt

Crossing sensor on red captures ±6 sec of video
Traffic
Light
Sensor
Car
Camera

If you cross the sensor on red, about 2 weeks later a citation like this arrives in the mail for the owner of the vehicle.
The black bars include the time, place, speed limit, your speed, and amount of time the light was red when your crossed the sensor.
Where to view the video on-line.

 View video on-line, then chose one of 3 options:
1) Pay $50
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No points on license
No notification to insurance company
 No notification to TN Dept. of Safety
2) Name the actual driver
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Affidavit
Vehicle owner is liable if actual driver fails to respond
No notification to Insurance Company, nor TN Dept. of Safety
3) Contest the ticket in court. If you lose :
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Additional $8 scheduling fee, plus $60 court fee
Judgement becomes a public record available to data mining companies

• Revenue Sharing Formula :
< $4500 per camera per month: 15% to City, 85% to Redflex
> $4500 per camera per month: 50% to City, 50% to Redflex
• 15 Intersections with cameras
• 60,299 Red-light violations
•
$955,014 to City revenue
• $1,644,719 to Redflex revenue
• Net = $43.11 per initial citation. (Compare to $50 ticket.)

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Drivers running a red light risk a collision with crosstraffic operating on green
Red-Light Cameras catch ALL red-light violations
Drivers soon learn to stop on red to avoid a ticket

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In a rush. Tried to beat the red.
(Sensitive to RLC)
Misjudged time versus distance (Minor sensitivity to RLC)
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Thought there was time to make it on yellow
Distracted when it changed to yellow
Did not see the signal (Not sensitive to RLC)
 Visibility problem
Could not stop in time (Not sensitive to RLC)
 Dilemma Zone (yellow too short for speed limit)
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Simple analyses are almost always misleading
Requires a comprehensive and sound statistical analysis because:
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Many confounding variables (traffic rate, traffic patterns, weather, intersection characteristics, speed, time of day, day of week, changes in vehicle safety features, driver characteristics, truck traffic, yellow duration, all-red duration, etc.)
Must correct for changes in traffic volume
Must compare the before and after accident rates to similar intersections without RLCs (to determine what changes were due to the RLCs)
Important to test for spill-over effects at nearby intersections without RLCs
Paucity of data and poor quality of data
Dealing with low numbers of random accidents: Statistical uncertainty is large.
 To detect a 10% difference with 95% confidence requires >800 accidents
Before/After RLC installation and >1600 Before/After at non-RLC control sites.
Must use tests for statistical significance of trends
 t-test, Chi-squared test, F-test, variance analysis, regression analysis, empirical Bayes analysis
 If an analysis does not use any of these tests, its conclusions are worthless.

Several Sound Statistical Studies are Available
 Barbara Langland-Orban et al., Red Light Running Cameras: Would Crashes,
Injuries and Automobile Insurance Rates Increase If They Are Used in Florida?
Florida Public Health Review, 2008; 5:1-7, and 5: 47-52.
 Nattaporn Yaungyai, Evaluation Update of Red Light Camera Programming in
Fairfax County, Virginia ; Master’s Thesis, Virginia Polytechnic Institute and State
University, April 2004.
 Mark Burkey and Kofi Obeng, A Detailed Investigation of Crash Risk Reduction
Resulting from Red Light Cameras in Small Urban Areas, North Carolina
Agricultural & Technical State University, Greensboro, NC, July 2004.
 Nicholas J. Garber et al ., The Impact of Red Light Cameras (Photo-Red
Enforcement) on Crashes in Virginia, Virginia Transportation Research Council,
Charlottesville, VA, June 2007.

 Excellent review and critique of all statistical studies performed on RLC installations to date.
 Easy to read for the non-statistician.
 A good place to start!

Nattaporn Yaungyai, Thesis, Virginia Polytechnic Institute and State University, April 2004.
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Excellent introduction to the RLC technology, history, laws and statistical testing process
Summarizes laws in all USA States extant up to April 2004.
Summarizes experience in several countries
Reviews public opinion surveys on RLCs in various cities.
Analyzes RLC impact in Fairfax County, VA
13 camera intersections; 12 to 82 accidents per year per intersection category (RLC, comparison, spill-over); only 2 comparison intersections; 4453 to 887 total RLC violations per month
Inadequate number of accidents and too few comparison intersections for determining significant accident trends.
Enough RLC violations to determine RLC violation trend.
RLCs reduced red-light violations as much as 58% in 22nd -
27th month after installation
Lengthening yellow light duration reduced red-light violations as much as 70%
Statistically non-significant reduction in accident rate.

Burkey and Obeng, Greensboro, NC, July 2004.
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Large data base yields good statistical accuracy:
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303 intersections
18 RLC sites: 840 accidents before & 777 accidents after RLC installation
285 non-RLC sites: 4827 accidents before, 4211 after
Analyzed correlation with weather
RLC installation associated with a statistically significant 40% increase in accident rates compared to non-RLC intersections.
No change in angle accident rates, and large increases in rear-end crash rates and other types of crashes relative to non-RCL intersections
Statistically non-significant increase in fatal accident rate
Decrease in left-turn accident rate with cross traffic at RLC sites
Longer yellow light duration decreases accident rate

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Large data set yields good statistical accuracy in the aggregate:
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More than 3500 crashes over 7 years
28 RLC intersections and 44 non-RCL intersections
6 jurisdictions (VA): Alexandria, Arlington, Fairfax City, Fairfax County, Falls
Church & Vienna
Analyzes aggregate versus individual jurisdictions and intersection types for differing trends. (Statistical accuracy suffers when subdivided by jurisdiction or intersection.)
Offers guide for selecting successful accident-reduction RLC sites
Attempts cost vs. benefit analysis: Inconclusive +/- result
Aggregate total accident rates increased 29% with RLC
Aggregate Rear-end crash rates increased 42% with RLC
Aggregate red-light running crash rates decreased a statistically non-significant 8% with RLC
4 of RLC intersections experienced increased angle crash rates
2 of RLC intersections showed decreased rear-end collision rates.

You can get trapped by a dilemma zone, if the yellow duration is too short for the speed limit.
Traffic
Light
Camera d s d c
Sensor
Dilemma Zone:
If light turns yellow, it is impossible to enter the intersection before red, and impossible to stop safely before the intersection.

Approach speed = v = 40 mph = 58.7 ft/s
Yellow light duration = t
Y
Decision time = t
D
= 4.0 seconds
= 1.00 seconds
Reaction time = t
R
= 0.50 seconds
Maximum safe deceleration rate = a = 10 ft/s/s
Percent Grade (+ve uphill, -ve downhill) = G
%
= 0
Maximum distance to make it on yellow: d c
 v t
Y

235 ft
Minimum distance to stop safely (avoiding rear-end collision): d s
 v
 t
D
 t
R
  a
 v
2
0 .
32 G
%


260 ft
Dilemma Zone exists from 235 to 260 ft from intersection.
If the light turns yellow when you are in this zone you can neither continue safely nor stop safely.

From 2003 TN Traffic Design Manual, recommended yellow light durations for level intersections are:
Approach Speed (mph): 25 30 35 40 45 50 55 60 65
Yellow Duration (sec.): 4.0 4.0 4.0 4.5
4.5 5.0 5.0 5.5 6.0
NOTE: Descending grades require longer delays.
Using values from the previous slide, the minimum yellow duration at
40 mph is computed as: t
Y min

 t
D
 t
R

 v
2
 a

0 .
32 G
%


4 .
4 sec .
For more realistic 85th percentile reaction times (t
D
+ t
R
), see: 1) APPENDIX B and 2) Thomas J. Triggs and
Walter G. Harris, Reaction Time of Drivers to Road Stimuli , Human Factors Report No. HFR-12, ISBN 0 86746
147 0. Human Factors Group, Department of Psychology, Monash University, Victoria 3800, Australia,
June 1982.

 The most important and most effective safety solution: Increase yellow duration according to approach speed and grade to eliminate unsafe Dilemma Zones.
 Statistically sound studies show that Red-Light Cameras are NOT a reliably effective solution for improving safety.
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The RLC effect on angle collision rates varies from positive to negative
RLCs usually significantly increase the rate of rear-end collisions
RLCs tend to increase total accident rates
However, RLC citation rates do decline in the first two years of operation
 Red-Light Cameras generate addictively large revenues
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Conflict of Interest : Safety can easily become less important than revenue
Analyze the operating costs carefully.
Some municipalities have lost money because of increased direct labor, overhead, and court costs.
Some have discontinued RLCs due to declining revenue.
 See Appendices A through D for more details.

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US DOT Federal Highway Administration Manual on Uniform Traffic Control Devices
( MUTCD ): http://mutcd.fhwa.dot.gov/
Tennessee MUTCD Traffic Design Manual: http://mutcd.fhwa.dot.gov/resources/state_info/tennessee/tn.htm
Making Intersections Safer: A Toolbox of Engineering Countermeasures to Reduce
Red Light Running , FHWA and Institute of Transportation Engineers, Pub. No. IR-
115, ISBN: 0-935403-76-0 (2003): http://safety.fhwa.dot.gov/intersections/rlr_report/index.htm ( published before the
2004 and 2007 studies on RLCs )
Dr. Peter T. Martin, Vikram C. Kalyani and Aleksander Stefanovic, Evaluation of
Advanced Warning Signals on High Speed Signalized Intersections, Univ. of Utah,
Nov. 2003.: http://www.mountain-plains.org/pubs/html/mpc-03-155/index.php
( Dilemma Zones )
Philip R. Bevington and D. Keith Robinson, Data Reduction and Error Analysis for the
Physical Sciences , WCB/McGraw-Hill, ISBN 0-07-911243-9, 1992. ( Excellent introductory book on statistical analysis )

Dependent on several factors:
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Distractions
Anticipation of, or focus on a particular warning or hazard
Difficulty of interpreting the significance of the hazard or warning
Difficulty of figuring out the best solution
Physical motion required to implement the solution
Mechanical delay in vehicle actuation
 What is the Right Reaction Time?
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MUTCD documents use a 1-second reaction time with a yellow light.
Dilemma Zone example used 1.5 seconds.
Studies showed a longer yellow reduces accidents and red-light violations.

1.5 sec. is a reasonable minimum
Driver Reaction Time to Surprise Encounter: Triggs and Harris 1982
Around a blind curve, past the crest of a hill, or triggered ON at the last moment
Field Test
Car Following (response to lead car brake light)
Protruding Vehicle with Tyre Change
Lit Vehicle Under Repair at Night
Flashing Railway Crossing - Night (Rally Drivers)
Flashing Railway Crossing - Night (General Population)
Flashing Railway Crossing - Day
Speed Trap: Tynong
Parked Police Vehicle (just past crest in hill)
C.R.B. "Roadworks Ahead" Sign
Speed Trap: Beaconsfield
Speed Trap: Dandenong North
Speed Trap: Gisborne
Mean
Reaction
Time (s)
0.92
0.97
1.02
1.14
1.18
1.77
1.75
2.37
1.64
2.46
2.45
2.54
Standard
Deviation
(s)
0.28
0.45
0.36
0.34
0.36
0.84
0.7
0.69
1.26
1.04
0.92
0.66
85th
Percentile
(s)
1.26
1.50
1.50
1.50
1.50
2.53
2.54
2.80
3.00
3.40
3.60
3.60
Traffic Engineers typically use the 85th Percentile for design: i.e., 85% of drivers have a lower reaction time.
From: Thomas J. Triggs and Walter G. Harris, Reaction Time of Drivers to Road Stimuli , Human Factors Report No. HFR-12,
ISBN 0 86746 147 0. Human Factors Group, Department of Psychology, Monash University, Victoria 3800, Australia, June 1982.

Appendix C: Required Yellow Duration and Green Delay to Eliminate Dilemma Zone and Clear the Intersection
Maximum Deceleration Measurement & Basic Parameters: Enter Measured Red Values
Time to recognize
Initial
Speed
(mph)
Minimum Time to
Stop, after applying brake
(sec.)
Minimum
Stopping
Distance (ft.)
Effective
Deceleration
Constant
(ft/sec/sec) change from Green to Yellow light and decide whether or not to stop (sec.)
Time to Move foot Duration of from Accelerator to Brake pedal
(sec.)
Yellow
Light
(sec.)
40 5.86
171.9
-10.0
1.0
0.5
4
Green Delay is also called the “All-Red” phase (red for all directions).
Minimum Yellow Duration to Eliminate Dilemma Zone
Distance
Initial
Speed
(mph)
Initial Speed
(ft/sec)
Travelled (ft.) while deciding to stop
Distance travelled (ft.) while moving foot to brake
5
10
7.3
14.7
7.3
14.7
3.7
7.3
15
20
25
30
35
40
45
50
55
60
65
70
75
22.0
29.3
36.7
44.0
51.3
58.7
66.0
73.3
80.7
88.0
95.3
102.7
110.0
22.0
29.3
36.7
44.0
51.3
58.7
66.0
73.3
80.7
88.0
95.3
102.7
110.0
11.0
14.7
18.3
22.0
25.7
29.3
33.0
36.7
40.3
44.0
47.7
51.3
55.0
Distance Travelled while Decelerating
(ft.)
2.69
10.74
24.17
42.97
67.15
96.69
131.61
171.89
217.55
268.58
324.99
386.76
453.91
526.42
604.31
Total Distance to
Stop (ft.)
13.7
32.7
57.2
87.0
122.1
162.7
208.6
259.9
316.6
378.6
446.0
518.8
596.9
680.4
769.3
Minimum
Required
Yellow
Duration
(sec)
1.9
2.2
2.6
3.0
3.3
3.7
4.1
4.4
4.8
5.2
5.5
5.9
6.3
6.6
7.0
Required Green Delay vs. Intersection Width
40-ft 60-ft 80-ft 100-ft 120-ft
Width:
Green
Delay
(sec)
Width:
Green
Delay
(sec)
Width:
Green
Delay
(sec)
Width:
Green
Delay
(sec)
Width:
Green
Delay
(sec)
5.5
2.7
8.2
4.1
10.9
5.5
13.6
6.8
16.4
8.2
1.8
1.4
1.1
0.9
0.8
0.7
0.6
0.5
0.5
0.5
0.4
0.4
0.4
2.7
2.0
1.6
1.4
1.2
1.0
0.9
0.8
0.7
0.7
0.6
0.6
0.5
3.6
2.7
2.2
1.8
1.6
1.4
1.2
1.1
1.0
0.9
0.8
0.8
0.7
4.5
3.4
2.7
2.3
1.9
1.7
1.5
1.4
1.2
1.1
1.0
1.0
0.9
5.5
4.1
3.3
2.7
2.3
2.0
1.8
1.6
1.5
1.4
1.3
1.2
1.1

Why the Sample Size Must Be Large
• Accidents have a low probability: typically < 50 per 1 million cars thru the intersection.
• Poisson Statistics apply: the probability of observing N accidents in a time period t is:
P ( N )

 N
 e
N !
N
 = the mean or average of the distribution.
A measure of the width or dispersion of the distribution about the mean is the standard deviation, s s  
Poisson Probability Distribution for Mean = 9
0.14
0.12
0.10
0.08
0.06
0.04
0.02
0.00
0 5 s
Mean s
10
N
15 20 25

Why the Sample Size Must Be Large
For a single sample of N accidents observed in a time t, the best estimate of the mean of the underlying probability distribution is
 
N
The best estimate of the standard deviation of the underlying probability distribution is s   
N
The dispersion, expressed as a percent of the mean value is s
%
 s 
100 %
N

100 %
N s % represents the percent uncertainty in estimating the true, mean number of accidents from a single measurement, N.

Why the Sample Size Must Be Large
Percent Uncertainty in the Number of Accidents
N : s % :
1
100
10
32
100
10
1,000
3.2
10,000
1
100,000 1,000,000
0.32
0.1
• To detect changes of the order of a few percent, one must have a sample of more than 10,000 accidents.
• When comparing accident rates at RLC intersections to similar, non-RLC intersections, one needs more than twice as many non-RLC intersections to keep from degrading the statistical uncertainty.