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What Is Red Light Running? A Case Study from Rhode
Island
Christopher D. Hunter
ABSTRACT. The goal of the project was to determine the severity of red light running
in Rhode Island. Central to the data capture process was the use of specialized portable
video camera set-ups, which captured views of every approach with one camera. Signal
phasing was captured simultaneously by linking to the signal controller. The audio data
were transmitted using wireless technology.
Twenty intersections were viewed
throughout the state, ranging from rural to urban settings.
For the twenty intersections viewed, there were a total of 8,587 violations observed over
a period of 1359 hours. This amounts to an average RLR violation rate of 6.3
violations/hr. For the individual intersections, the violation rates ranged from 1.2 to 15.0
per hour. The violations were also specified also by the time that had elapsed in the red
phase. From analysis of the data, there are intersections in Rhode Island where RLR is a
problem.
A model was developed to prioritize intersections based on a Composite Intersection
Index (CII), where the highest score indicated the most problematic intersection. The CII
was based on a comprehensive set of variables including the following: (1) entering ADT
(1000s of vehicles); (2) number of lanes entering the intersection; (3) RLR violation rate;
(4) proportion of violations occurring after 1 second; (5) number of phases; and the (6)
average approach speed (based on approach speed limits).
BACKGROUND
As the demand on roadways in this country continues to increase and the average
person’s desire is to get everywhere in a hurry, more dangerous driving habits seem to be
pervasive. In an attempt to address locations in the roadway system where safety can be
improved, different types of strategies are being employed. One particular portion of the
roadway system where there is a trend of increased accidents is at the signalized
intersection. A variety of reasons may be cited as the cause of some accidents at the
signalized intersection, but the most prominent one is red light running (RLR). RLR is
recognized as an act of non-compliance.
According to the FHWA, more than 1.8 million intersection crashes occur per year. For
the year 2000, there were 106,000 crashes, 89,000 injuries, and approximately 1036
fatalities that were reported, which were attributed directly to red light running (FHWA,
2002). This is part of an upward trend that is being seen with respect to where and how
accidents are occurring in the roadway system. Interestingly, 55.8 percent of Americans
admit to running red lights and 96% of drivers fear that they will be struck by a red light
running vehicle when they enter an intersection (FHWA, 2002).
This goal of this research effort was to determine the severity of RLR violations in the
state of Rhode Island. Annually, there are numerous complaints about the safety of
Rhode Island intersections, and due to this, a study was suggested to determine the level
of red light running associated with signalized intersections in the state. The Rhode
Island Department of Transportation (RIDOT), AMICA Insurance, the Governor’s Office
on Highway Safety (OHS), and the University of Rhode Island Transportation Center
(URITC) were the initiators of the effort. The URITC, RIDOT, and Nestor Traffic
Systems were involved in the actual collaborative effort to perform the research.
RESEARCH OBJECTIVES
The overall study had the following objectives:
•
To determine the level of red light violations at a sample of intersections
throughout the state
•
To determine, for the intersections studied, how the red light running severity
potentially contributes to possible accidents at an intersection
•
To determine for the intersections studied, if there are times of day or traffic
conditions that are more correlated with increased levels of red light running
activity
•
To determine, for the intersections studied, if certain intersection characteristics
are correlated with the level of red light running at an intersection; among them,
location of the intersection (urban vs. rural), traffic volume, time of day, site
visibility, signal timing, etc.
•
To capture and record traffic movement data in a quantity and manner sufficient
to produce valid measurements, as well as a permanent record of data that can be
independently reviewed for the purpose of verifying all red light running
measurements documented in this final report; and
•
To make recommendations, on the basis of the red light running data gathered in
this study, about the need for and types of corrective measures that can be used to
reduce the number of violations occurring at the monitored locations.
METHODOLOGY
The primary purpose of this research effort was to determine the scope and the severity of
RLR violations in the state of Rhode Island. This section describes the process that was
undertaken to accomplish the overall goal and the objectives of the project, including onsite observations, analysis of RIDOT records on Average Daily Traffic (ADT), and
accident history.
The initial issue was defining explicitly what was considered a red light running
violation. Four separate issues were involved in the overall project: (1) specification of
the intersections to be studied; (2) information to be obtained; (3) how the data is to be
collected; and (4) analysis techniques.
THE DEFINITION OF RED LIGHT RUNNING FOR THIS PROJECT
For the purposes of this study, the definition of “red-light running” will conform to the
law as specified by the Rhode Island Criminal and Traffic Law Manual. The statute
(31-13-6) is provided below.
31-13-6. Specifications and meaning of traffic lights.
Red alone or "stop."
Vehicular traffic facing the signal shall stop before entering the crosswalk on the
near side of the intersection or, if none, then before entering the intersection, and
shall remain standing until the green or "go" is shown alone, and shall not, prior
to reaching the intersection, make any turn over or through private property in
order to avoid the signal, provided, however, a right hand turn shall be permitted
after vehicular traffic reaches a complete stop, at intersections when safety would
permit the turn and no sign forbids it.
Hence, for this project, a red light violation will be defined as a movement of a vehicle
across the crosswalk or stop bar and through the intersection when the traffic signal is
red. A stop bar is commonly found on each vehicular approach prior to the intersection.
See Figure 1 for a visual depiction of the position of the vehicle in reference to a
crosswalk or a stop bar.
Vehicle
location
Figure 1. Red Light Running Diagram
INTERSECTIONS STUDIED
A committee, consisting of persons from the Rhode Island Department of Transportation,
the Head of the Rhode Island Association of Police Chiefs, and the Rhode Island State
police developed an initial list of candidate intersections to be studied. These
intersections were selected, based on the objective of assembling a sample of
intersections from around the state, representing both urban and rural locales. Among the
candidate intersections, there was a fairly equal distribution of sites that were in urban
locations and non-urban locations. To obtain a better balance of intersections with
representation from each area of the state, other candidate locations were provided by a
representative of URI. A major factor in the final choice of intersections included
needing to use state maintained intersections so as to have access consistently to traffic
controller cabinets as needed with no greater coordination efforts. From that list, site
investigations took place, and twenty intersections were chosen for collection of relevant
data. These sites exhibit a fairly random distribution of traffic volumes, which includes
heavy traffic flow and light-to-moderate traffic flow.
See Table 1 for the actual
intersections studied in this effort. Figure 2 indicates the actual locations graphically in
the state.
Table 1. Red Light Running Study Sites
Intersecting Roadways
Location
Route 102 & Route 107
Route 2 & Park Avenue
Route 120 & Route 122
Route 3 & Route 102
Route 6A & Route 5
Route 116 & Route 126
Route 138 & Route 214
Route 214 & Green End Ave
Route 4 & Oak Hill Rd
Route 1 & Route 102
Route 146 & Sayles Hill Rd
Smith St & River Ave
Memorial Blvd & Exchange St
Route 6 & Route 101
Route 101 & Route 116
Route 7 & Route 116
Route 1 & Route 138
Airport Road & Warwick Ave
Route 1 & Lang worthy Rd
Route 1 & Ward Street
Burrillville
Cranston
Cumberland
Exeter
Johnston
Lincoln
Middletown
Middletown
N. Kingstown
N. Kingstown
N. Smithfield
Providence
Providence
Scituate
Scituate
Smithfield
S. Kingstown
Warwick
Westerly
Westerly
Figure 2. Distribution of Red Light Running Intersection Locations in Rhode Island
DATA CAPTURE
Violations and intersection characteristics were the two sets of data important for this
study.
The first objective with respect to the potential sites was to perform intersection
evaluation and selection. This helped determine the set of intersections that would be
studied in the project. Being able to obtain accident and volume data were initial issues.
A site visit to each intersection was needed as well to collect relevant data as well as to
evaluate the intersection from the perspective of suitability for equipment deployment
and operation. The site visits to the intersections helped ascertain the following: (1) the
availability of a suitable pole for camera mounting; (2) the ability to capture video of all
approaches of travel from a camera mounted on this pole; (3) the proper operation of
wireless communications between camera and receiver; and (4) the installation issues
involved in connecting traffic signal phase sensing equipment within the traffic controller
cabinet are all evaluated on site. As part of this evaluation, the traffic signal timing plan
for the intersection was made available at some intersections for review to determine how
the violation counting equipment would be installed at the intersection. The deliverable
for this task was a report indicating the list of intersections to be studied, the basis for
their selection, and the equipment installation plan for each intersection.
Inventory and Site Data
The inventory data captured some or all of the following.
•
Lane markings
•
Stop bars or not; cross-walks
•
Speed limits for approaches
•
Bus stops
•
Conditions that may affect visibility and/or sight distance (horizontal/vertical curves,
steep grades at approach)
•
Driveways near intersection
•
Abutting or nearby land uses (schools, businesses, entertainment centers, malls, etc.)
•
Estimated roadway widths, shoulder widths, lane widths
•
Phase movements (along with narrative description of how intersection operates, i.e.
are there numerous free right turn movements)
Violation Data
Ultimately, the critical data to be captured in this project was the number of red light
running violators. The common measure for identifying this in the literature is violations
per hour. Also, analyses using comparisons of violations by time of day or by time of
week have been used, as well as violations per numbers of vehicles entering the
intersection. For this project, the chosen measure was violations/hour. Other data
obtained to further characterize the problem follows in the list below.
•
Approach (NB, SB, EB, WB)
•
Turning movement (through, left, right)
•
Number of seconds after the red light that the vehicle enters the intersection
•
Weather conditions
•
Approach speed limit
•
Length of change interval (yellow and all-red if it exists)
Schedule of Violation Data Collection
Which days and what times to capture data were the most difficult issues to determine
without more specific data about the intersections. The literature indicated that multiple
studies had captured data on weekdays and weekends with a variation in the time periods
during the day. The common approach for most traffic studies involves capturing data
through the peak hour or peak periods. Depending on the nature of the data, different
time periods are more appropriate. As for the red light running violation data, there
seemed to be no standard, but it seemed most appropriate to capture data throughout the
week and through a variety of times. Reports show higher rates during the peak hour in
some locations and during the off-peak hours in others. Ultimately, the purpose of the
study was to capture the severity, and in doing so, capturing the typical characteristics
was important. There were two issues of overall concern here. One was moving forward
on the time schedule of the project, and the second was coordinating the times when the
cameras were to be moved.
.
Violation Recording Equipment
For the study, the Crossing Guard VIP Equipment from Nestor Traffic Systems was used.
Two issues were important with respect to this equipment: (1) when deployed, the
equipment was easy to place inconspicuously so as to not alert drivers to the data
collection effort; and (2) it was relatively easy to install and remove, thus facilitating the
ability to do data capture at all the targeted locations within the confines of the project
budget.
Equipment Installation
To obtain data, Nestor Traffic Systems (NTS) set-up and removed the mobile Crossing
Guard VIP equipment at the desired intersections for the study period. At each
intersection to be monitored, NTS deployed equipment consisting of an NTSC video
camera and mounting pole, a VCR, a wireless transmitter/receiver pair, a pair of heavyduty, rechargeable 12V batteries, and a traffic signal encoding device. The camera was
positioned to capture traffic movements in all directions. The traffic signal encoding
device captured and converted the information from the green phase of the signal to audio
tones that are recorded, along with the camera images, to the VCR videotape. With this
equipment, NTS recorded on single field videotape, 8 scheduled hours of traffic
movement through the intersection in all directions, along with the phases of the traffic
signal lights. Problems arose with regard to logistics, weather, equipment, etc., and a
scheme to capture 16 hours of data was used to finish the data collection in the desired
time-frame.
Field Servicing
Field servicing consisted of replacing the depleted batteries for freshly charged batteries
and retrieving recorded field videotape and replacing it with a blank tape. URI students
and sometimes faculty performed field servicing.
Tape Processing
Once field videotape had been retrieved from the intersection, initially, it was processed
to decode the audio signal and create from it an image that contains traffic signal phase
information overlaid onto the recorded video of traffic movements. This process results
in ”composite videotape” with combined traffic movement and traffic status signal
information. This image is suitable for manual review to identify red light violations,
noting time of day and time after red for each such incident. Nestor Traffic Systems did
most of this, although URI performed some of the work.
Tape Review
Obtaining actual data was incumbent primarily on students from the University of Rhode
Island. They were responsible primarily for the capture of field data, as well as the
violation data from videotape viewing. A lab was established in Bliss Hall of the
University of Rhode Island campus for videotape viewing and processing as needed.
This room housed the monitors and VCRs to view the videotapes. A civil engineering
graduate student from the Department of Civil Engineering was assigned full-time to the
project and helped to manage a crew of students. The majority of the students were civil
engineering majors, who were involved in different aspects of the project.
To prepare for the data collection, training sessions were held regarding the capture of
field data and the recording of violation data. For the field data, the students were given
an example of the type of information to be placed on the field data sheet that was
specified earlier. The students were also shown sample videotape with the recording
sheet to train them in recognizing a violation and marking it correctly.
RESULTS
The capture of RLR data was the responsibility of the University of Rhode Island. The
task included gathering the observed violations and other pertinent data in a database that
allowed the ability to characterize the violations by approach and specific movement, by
time-after-red, and by violation rates associated with certain times of day.
SUMMARY OF INDIVIDUAL INTERSECTIONS
Overall, there were a total of 8,587 violations recorded over the course of 1359 hours.
This yielded a violation rate of 6.3 violations per hour. The violation rates for the rural
versus the urban locations varied from 5.7 to 8.8 respectively.
To place the level of RLR running violations in context, the average daily traffic (ADT)
and a three-year accident profile were investigated as well. The ADT and the accident
reports were collected through the RIDOT. See Table 2 for cumulative summary data
for each intersection. Table 3 provides data about the distribution of RLR violations in
time intervals.
Table 2. Summaries of Intersections
INTERSECTION
Rt 102/ Rt 107
Rte 2 & Park
Rt 120/ Rt 122
Rt 3/ Rt 102
Rt 6A/ Rt 5
Rte 116/ Rt 126
Rt 138&214
Rt 214 & Green End
Rt 4 & Oak Hill Rd
Rt 1 & 102
Rt 146 & Sayles Hill Rd
Smith St & River St
Memorial & Exchange
Rt 6/ Rt 101
Rt 101/ Rt 116
Rt 7 & 116
Rt 1 & 138
Airport Rd/ Warwick Ave
Rt 1 & Langworthy
Rt 1/ Tower
Total
Vio.Rate
Hours Violations (Vio./Hr)
78
63.0
1.2
886
75.5
11.7
173
56.3
3.1
71.3
284
4.0
240
44.0
5.5
531
97.3
5.5
811
83.0
9.8
204
87.0
2.3
964
88.0
11.0
364
54.6
6.7
520
70.1
7.4
417
75.0
5.6
215
57.0
3.8
130
51.0
2.6
180
55.5
3.2
117
35.6
3.3
422
66.0
6.4
525
78.5
6.7
578
86.9
6.7
948
63.0
15.0
Entering
Accident Data
ADT Number Injuries Fatalities
15050
14
4 0
46500
68
44 0
16300
43
35 0
9200
30
28 0
35700
69
39 0
21350
31
18 0
31500
86
54 0
22450
17
17 0
48300
5
2 0
37650
58
50 0
28000
56
37 0
24550
8
13 0
24050
15
8 0
15750
12
12 0
13200
14
8 0
24500
27
15 0
47000
62
42 0
59250
80
56 0
23850
25
17 2
22650
3
1 0
Table 3. Distributions of RLR Violations w/ Respect to Time-After-Red
INTERSECTION
%( percentage) of total violations.
Seconds after signal has turned Red.
0-1
1-2
2-3
3-4
>4
Rte 102& Rte 107
49%
9%
3%
1%
38%
Rte 2 & Park
40%
33%
12%
5%
9%
Rte 120 & Rte 122
60%
17%
6%
3%
14%
Rte 3& Rte 102
35%
38%
16%
5%
5%
Rte 6A& Rte 5
56%
24%
11%
4%
5%
Rte 116& Rte 126
40%
17%
5%
3%
34%
Rte 138&214
62%
27%
8%
2%
1%
Rte 214 & Green End
66%
29%
3%
0%
1%
Rte 4 & Oak Hill Rd
62%
29%
6%
2%
1%
Rte 1 & 102
63%
21%
8%
4%
3%
Rte 146 & Sayles Hill Rd
49%
35%
9%
2%
5%
Smith St & River St
57%
31%
7%
2%
3%
Memorial & Exchange
60%
25%
5%
2%
8%
Rte 6& Rte 101
31%
33%
19%
6%
11%
Rte 101& Rte 116
68%
20%
4%
1%
7%
Rte 7 & 116
50%
17%
3%
4%
26%
Rte 1 & 138
55%
27%
11%
3%
5%
Airport Rd& Warwick Ave
39%
37%
15%
4%
5%
Rte 1 & Langworthy
Rte 1& Tower
56%
31%
5%
1%
7%
57%
29%
9%
2%
3%
ANALYSIS & EVALUATION
This section is dedicated to the analysis and evaluation of the red light running violations
observations. The analyses focus on three issues: (1) violation rates; (2) time elapsed
after the red signal when the violation occurred and (3) determination of characteristics
leading to red light running.
ANALYSIS OF VIOLATION RATES
Two things were critical with respect to the violation rates. The first dealt with when the
highest violation rates were occurring specifically by location and by time of day. The
second dealt with how do the violation rates correlate with accidents at the intersections.
By time of day, it is noticed that the majority of the highest violation rates for each
intersection occur during the “common” peak period—between 4PM and 6PM. The next
most common occurrence is between 12PM and 1PM. In the literature, it was noticed
that peak violation rates did not always occur during the peak hour. The data in Rhode
Island does suggest that most of the occurrences do happen in higher volume periods—
PM peak period and midday. Most noticeable in the data was that the locations with
higher noontime violation rates occurred in commercial locations with restaurants in
close proximity. Figure 3 shows the distribution of peak violation rate occurrences.
7
5
5PM - 6PM
4PM - 5PM
3PM-4PM
2PM-3PM
4
3
2
1
0
12PM - 1PM
Number of
Occurrences
6
Time Period
Figure 3. Distribution of Peak RLR Violation Rates Occurrence Time Periods
Red light running violation rates by location was another item of interest in the research.
There was a fairly equal distribution of rural and urban locations used as sites for the data
capture and analysis. As for the outcome, the rural locations did tend to show lower
violation rates in general—5.4 violations/hr to 8.1 violations/hr respectively. The mean
was 6.3 violations/hr for the state.
A t-test revealed that there was no significant
difference in the locations with respect to RLR violation rates at the 95-percentile
confidence level.
One of the issues of interest was the level of violations during the PM peak hour and peak
period. Seven intersections yielded rates of 12/hr. Table 4 indicates these intersections
that yielded these levels of RLR violation rates.
Table 4. Intersections with 12 or Greater RLR Violations During the PM Peak
Intersection
Route 1 & Ward street
Route 2 & Park Ave
Route 6A & Route 5
Route 138 & Route 214
Route 1 & Route 102
Airport Road & Warwick Ave
Route 4 & Oak Hill Road
Peak period RLR violation rate
14
16
12
14
14.7
12
15.7
ANALYSIS OF RLR WITH RESPECT TO TURNING MOVEMENTS
With respect to vehicle movements through the intersection, the majority of the violations
occurred on through-movements. Through-movements accounted for 62% of the
violations, while 36% of the violations were attributed to left-turn movements. The
remainder are attributed to right-turn movements, where right-turns-on-red were
prohibited.
There are six intersections, where left-turn movements contribute to the majority of the
violations. Of these six intersections, left-turn RLR violations yield the majority of the
violations occurring after 1 second had lapsed. The intersections are listed in Table 5,
and the ones with a majority of the violations occurring after 1 second had elapsed have
asterisks next to them. Most of these intersections had protected left-turn phases, and
movements that were termed as “chaining” movements were prevalent. The chaining
movement was one where platoons of vehicles continued to follow each other into the
intersection even though the signal had already turned red. The occurrence was most
prevalent at higher-volume intersections that had heavy left-turn movements.
Table 5. Intersections with High Left-Turn RLR Violation Rates
Intersection
Airport Rd and Warwick Avenue *
Route 6A & Route 5
Route 7 & Route 116 *
Route 1 & Tower Rd
Route 120 & Route 122
Reservoir Ave & Park Avenue *
*
Majority of left turns occur after first second of Red light.
RELATIONSHIP OF VIOLATION RATES TO VARIOUS ATTRIBUTES
One of the major issues that this research effort wanted to investigate was the relationship
of RLR violation rates to various factors. The first hypothesis was that the violation rate
would correlate well with accidents. See Figure 4 for the plot of the data. A correlation
was run with the data from each of the twenty intersections. A strong fit could not be
accomplished even with the removal of outliers.
Other factors that were tested initially against the violation rate included the number of
lanes entering (LaneEnt), Entering Average Daily Traffic (EADT), number of phases
(phases), approach speed limits (speed). When correlations were run with violation rates
and these factors, no strong correlations were present.
Due to this, the research efforts turned toward developing a comprehensive look at the
intersection and trying to use the violation rate to make some determination about the
“intersection picture” and relate it to accidents. The following section discusses this
issue.
3-Yr Accident Totals
100
80
60
40
20
0
0.00
10.00
20.00
RLR Violation Rate
Figure 4. Accident Totals vs. RLR Violation Rates
DEVELOPMENT OF A COMPOSITE MODEL TO IDENTIFY SEVERITY OF INTERSECTION
The initial motivation for working toward a composite model was that it appeared that
multiple factors should be involved in driving a relationship between the intersection and
the number of accidents occurring at those intersections. For this reason, a set of
variables that included roadway characteristics, traffic phasing, RLR violation rates, and
entering ADT was set forward. The equation for the comprehensive intersection index
(CII) follows.
CII = (EADT/ENL)(VR)(PROP)(P)(SPD)
CII
EADT
ENL
VR
PROP
P
SPD
= Composite Intersection Index
= ADT (1000s of vehicles) Entering Intersection
= Number of lanes entering intersection
= RLR Violation Rate
= Proportion of violations occurring after 1 second
= Number of phases
= Average approach speed or average speed limit
The values that resulted from this are included in Table 6. The values ranged from 127
to 5404, with the highest values suggesting the most problematic intersection.
Accidents (3-Yr Period)
As with the first analysis with the raw violations/hr versus accidents, there was not a
strong positive correlation with all 20 intersections (r=0.56), but it was stronger than the
violation rate by itself. After looking at the plot of the data, once again there appear to be
data points that are not appropriate. See Figure 5. With the points removed a correlation
was run that did provide a stronger positive correlation (0.80).
100
80
60
40
Remove point
Remove point
20
0
0
1000
2000
3000
4000
Composite Intersection Index
Figure 5. Plot of Accidents vs. CII
5000
6000
Table 6. Composite Intersection Index
INTERSECTION
Reservoir &Park
Rte 138 &Rte 214
Rte 4 &Oak Hill
Rte 1 &Rte 138
Airport Rd &Warwick Av
Rte 146 &Sayles Hill Rd
Rte 1 &Tower Rd
Rte 6A&Rte 5
Rte 1 &Langworthy
River Ave &Smith St
Rte 7 &Rte 116
Rte 116 &Rte 126
Rte 1 &Rte 102
Rte 120 &Rte 122
Rte 214 &Green End
Rte 101 &Rte 116
Exchange St &Mem'l Blvd
Rte 3 &Rte 102
Rte 6 &Rte 101
Rte 102 &R107
Composite Score
5405
5203
4530
3666
3632
2312
1961
1373
1196
1147
1077
950
796
651
609
348
340
335
333
127
Accidents
68
86
5
62
80
56
3
69
25
8
27
31
58
43
17
14
15
30
12
14
MODELING DATA
After investigating the issues with correlation, the effort was then focused on finding a
relationship that fit the data. Two types of models were proposed based on the data
points observed in the scatter plots. One was linear, and the other was a logarithmic
model. With the linear approach, the simple intuitive notion was that as the Composite
Intersection Index (CII) increased, so would the number of accidents. With the
logarithmic model, the expectation was that there would not be a situation of total chaos
at an intersection at higher CII levels because one would expect the number of accidents
to stabilize gradually.
With this in mind, a linear model and a logarithmic model were applied to find the best fit
for the data. The final model chosen was the logarithmic model. After running
diagnostics on the model with plots of residuals against the model and the residuals
against the independent values, the best model would be one that included 17 of the
original 20 points. The intersections with accident totals less than 10 were the ones
removed from the model. These particular intersections were among the top ten in CII
rating (See Table 6). The final fitted model is provided as follows.
Y= 19.75 ln (X) – 94.39
R2= 0.733
Where Y= Number of accidents (3-yr period)
X= Composite Intersection Index (CII)
EVALUATION
The evaluation is dedicated to making judgments about the Rhode Island intersections by
comparison to other locations that have measured RLR running in the United States.
Other studies provide a context for the results of discovery here in our base case
observations on red light running. An anecdotal report found in a paper in Rhode Island
provides a context for what makes an intersection “appear dangerous” with respect to
safe entry into the intersection when the green signal appears.
Issues such as vehicle exposure, RLR violation rates, and time-after-red serve as the
measurable basis for comparison. Vehicle exposure relates to multiple issues such as
number of vehicles entering the intersection, number of cycles per hour or phases per
cycle, which essentially relate to the number of opportunities for RLR violations to occur.
The RLR violation rate is just the raw number of violations versus the number of hours
that the intersection was under observation. Time-after-red serves as another level of
exposure as one analyzes the vehicles by viewing the time after red when the vehicle
enters the intersection.
The most difficult issue to resolve in studying RLR by itself (not relating to accidents per
se) was identifying a numerical standard for saying that an intersection has a high rate.
There is no national standard that exists. The most critical consideration seems to be
where are the accidents occurring, not the potential for accidents. Certainly, as more
vehicles run the red light, there is greater potential for accidents to occur. Since, there
is no pure standard for quantifying the level for high RLR violation rates, then there have
to be qualitative views that provide a context for an intersection or intersections to be
considered a problem.
Violation Rates
The easiest comparison to make is the RLR violation rate. The only study that was found
to study every approach of the intersection was one in Arlington, VA. In Arlington, VA,
5 violations/ hr was the average rate overall, while 6.4/hr was the average rate for Rhode
Island. In Arlington during the peak hour, the average violation rate was 12/hr. At least
seven of the intersections studied in RI matched or exceeded that rate during the peak
hour.
Time-After-Red
The time-after-red analysis provided further analysis of the severity of the RLR violation.
Whereas many other locations just provided data on RLR violations occurring, this study
provided the detail of listing the time of occurrence and the time that had elapsed after the
beginning of the red phase. The All-Red phase was 1 second for all intersections
studied. Hence, when vehicles from other approaches enter the intersection after 1 full
second or more, the probability of being involved in an accident increases. Seven of the
twenty intersections from this research effort had a majority of their violations occurring
after 1 full second.
Anecdotal
There was one anecdotal work that helped provide some sense of what was considered a
dangerous intersection with respect to RLR violations.
This came in the form of an
article in a local newspaper, The Narragansett Times. During the same time period that
the data collection was ongoing, the Improvement Association of Kingston, RI noted that
RLR was a problem at the intersection of SR 138 and Upper College Road, URI,
Kingston. This prompted police to monitor this intersection more intensely. For 21
days, the South Kingstown police monitored this location. On one day, during the peak
PM period (3:30PM – 6:30PM), it was noted that the police issued 24 citations for RLR.
For the sake of comparison to the data captured in the research effort, there are numerous
intersections where we at least show 8 RLR violations/ hr during the peak PM period, and
we could potentially say that these intersections could be considered “dangerous”.
For those persons who were caught running the red light, the excuses included the
following:
(1) “It was yellow.”
(2) “I didn’t’ see the light.”
(3) “I was going too fast to stop.”
Each of these excuses shows some level of disregard for how to treat a signalized
intersection.
Certainly, “it was yellow” is a tough one to treat. Many persons are
caught in the “dilemma” zone, and they aren’t sure if they should stop or go when they
see the yellow light appear. The second and third excuses really show poor regard for
others. Signals at an intersection tend to be placed in conspicuous locations, usually in
the center of the intersection or above each lane of approach. If a driver is cognizant, the
driver will locate the signal as they approach the intersection. The third reason shows
that the driver is not conforming to the driver’s appropriate response to the yellow light,
which is to approach with caution.
CONCLUSIONS
Increasing traffic volumes and the desire to move to and from origins and destinations
quickly all too often results in lack of tolerance, which sometimes results in aggressive
behavior and non-compliance of traffic laws, including abiding by the rules of the traffic
signals. One major portion of the roadway transportation network involves signalized
intersections. At these signalized intersections, a major issue with respect to compliance
is red light running (RLR) specifically. RLR places drivers, passengers, and pedestrians
at risk. This research effort quantified the phenomenon in Rhode Island through a
sampling of twenty intersections throughout the state, as well as identified issues
involved with red light running in general.
The major conclusion is that there are locations in Rhode Island where red light running
is a problem. Overall, there were considerable numbers of red light running violations
captured in the study, but when we used the measure of violations/hr, it was easy to note
that in comparison with other work done, that there were problems. This was
documented through quantitative and qualitative evaluations. In comparison to the one
other comparable study that analyzed all approaches of an intersection for RLR, there
were numerous intersections that exceeded violation rates noted there. Overall, violation
rates ranged from 1.24 violations /hr to 15.0 violations /hr for the 20 intersections that
were studied. The average violation rate for the sum of the total violations versus the
sum of the total number of hours of video viewed was 6.3 violations/hr. This translates
to a RLR violation occurring every 9.5 minutes.
To characterize the RLR violations further, it can be noted that persons are not merely
pushing through the red light just as the light turns, but a sizeable percentage are entering
the intersection after 1 full second with many noted entering the intersection after 2 or
more seconds.
Other conclusions derived from the study are that there are specific times of day that
RLR violations occur most often and that there are some roadway environment
characteristics that link closely to them. For the twenty intersections studied, the
common time period to find the highest RLR violations rates was between 4PM – 6PM,
which is commonly viewed as the peak PM period. At least seven of the intersections
yielded violation rates exceeding 12/hr during the peak period. The next most common
occurrence is 12PM – 1PM. For the intersections that had higher RLR violation rates
near mid-day, each had commercial development and restaurants in the vicinity.
A final conclusion is that the development of the Comprehensive Intersection Index (CII)
is helpful in prioritizing the most problematic intersections when red light running data
has been captured. Factors involved in the index included the following: (1) entering
ADT; (2) number of lanes entering the intersection; (3) violation rate; (4) percent of
violations occurring after 1 second; (5) average number of phases per cycle; and (6)
average approach speed limit. A strong relationship was found between the CII and the
level of accidents associated with an intersection.
RECOMMENDATIONS
Based on the work that was done, there are specific directions that should be taken with
respect to the data captured during the research effort. They are based around education,
engineering, and enforcement.
With respect to education, the following types of ideas should be considered in Rhode
Island. First, and foremost, there should be some type of traffic safety campaign that
attempts to educate the public about the findings of the report with respect to the typical
violation rate. This shouldn’t be done in a manner that may cause paranoia, but as a
educational piece that works to alert persons that their need to be in a hurry should not
cause someone else’s life to be in peril because they did not want to stop. This
educational piece could come in articles in the newspaper or “traffic spots” on television
as a public service announcement. An easy way to pass the information out is to send out
a brief statement along with vehicle registration notices that alert persons “STOP ON
RED—it’s not an option.”
With respect to engineering, there are many avenues to broach. Using the CII to
prioritize the intersections is worthwhile, especially when all intersections of interest
can’t be investigated at once. A suggestion is to investigate the first five intersections
with the highest CII ratings. One of the first things is to analyze the traffic volume and
the signal timing and phasing to determine if they are appropriate. One of the major
issues with respect to the timing that comes up is the length of the yellow light. The
author does not favor extending the designated yellow time unless it is appropriate
according to timing standards. Another idea worth considering is setting a standard
minimum yellow light time interval along certain corridors of signals just to promote
consistency, which may help motorists better judge if they should attempt to stop or
continue when they see a yellow signal. Other engineering factors that may need to be
visited include checking sight impairment issues (lighting-based or design-based) or
investigating the use of traffic calming features that may induce people to approach an
intersection at a slower pace. Even the engineering based with signal design and
construction of the signal itself with different types of signal heads can be effective in
some locations.
With respect to enforcement, targeted enforcement campaigns could be directed at certain
periods of day, based on the data provided from the observations. This particular detail,
although one of the better ways to discourage RLR, can also prove to be somewhat
dangerous for the enforcement officer, as well as other drivers moving from approaches
where they have just gotten a green signal indication. Ultimately, as an officer tries to go
after a RLR, the light has turned green for the other approach(es), so there is a potential
conflict that occurs. Of course, there are ways to use enforcement officers in tandem to
view the violation from one approach and then signal ahead to an officer downstream of
the intersection.
Automated enforcement is another option, but there is no legislative support for using it
in Rhode Island. The benefits of using an automated enforcement program have been
documented very well from numerous locations around the country. The major benefits
have been reductions in accidents at signalized intersections, which lead to fewer
incidents of general property damage, injuries, and fatalities. It could be useful to have
this legislation in place, so that automated enforcement could be implemented if
educational and engineering countermeasures don’t help reduce the violation rates
significantly.
Author’s Information
Christopher D. Hunter
Assistant Professor
University of Rhode Island
310 Bliss Hall
Department of Civil & Environmental Engineering
Kingston, RI 02881
Phone: (401) 874-2818
Fax: (401) 874-2786
hunter@egr.uri.edu
REFERENCES
1.
2.
3.
City of Charlotte, N.C. SafeLight, First Year Report. Charlotte, NC, 1999.
Datta, T.K., K. Schattler, and S. Datta. Red Light Violations and Crashes at
Urban Intersections. In Transportation Research Board 79th Annual Meeting.
TRB, National Research Council, Washington, D. C., January 2000.
FHWA. Stop Red Light Running Literature. FHWA. USDOT, Washington,
D.C., 2002.
4.
Fleck, J.L. and B.B. Smith, “Can We Make Red-Light Runners Stop? Red Light
Enforcement in San Francisco, California”, Transportation Research Record
1693, TRB, Washington, D.C., 1999.
5.
Hans, M. Cameras Catch Red-Light Runners. Traffic Safety, Jan./Feb. 1997, pp.
8-13.
http://www.fhwa.dot.gov/stoprlr/camr/camrtech.htm. Accessed June 27, 2001.
http://safety.fhwa.dot.gov/programs/slrl.html. Accessed on April 25, 2001.
6.
7.
8.
http://www.iihs.org.safety/safety_facts/comments.htm. Comments on “The Red
Light Running Crisis: Is it Intentional?” from the Office of the Majority Leader,
US House of Representatives.
9.
http://www.napa.ufl.edu/2001news/redlight.html. Accessed on April 26, 2001.
10.
http://www.siouxfalls.org/Citywide/Redlightcampaign/redlight.asp. Accessed
Sept 30, 2002.
http://safety.fhwa.dot.gov/fourthlevel/pro_res_srlr_facts.htm. Accessed Cited
July 31,2001.
Insurance Institute for Highway Safety, Status Report, Vol. 35, No. 3, March 11,
2000.
11.
12.
13.
Insurance Institute of Highway Safety. 1st Time in United States: Study Finds
Red Light Cameras Yield Reductions in Crashes, Especially Injury Crashes, News
Release, April 26, 2001.
14.
Insurance Institute of Highway Safety, Highway Loss Data Institute. Red Light
Cameras in Action, May 8, 2001.
15.
Kamyab, A. and McDonald, T. Red Light Running in Iowa: The Scope, Impact,
and Possible Implications, Final Report, CTRE Management Report No. 99-49,
Center for Transportation Research and Education (Iowa State University),
December 2000.
16.
Nestor Traffic Systems (NTS). Red Light Running Study for City of Herndon,
VA. 2001.
17.
Office of the Majority Leader, US House of Representatives. The Red Light
Running Crisis, Is it Intentional?, May 2001.
Passetti, K.A., and T. H. Hicks. Use of Automated Enforcement for Red Light
Violations. Dept. of Civil Engineering, Texas A&M University, College Station,
TX, pp. 1-60, 1999.
18.
19.
Polk, A. “Electronic Enforcement of Traffic Laws”. ITS Quarterly, Summer
1998,pp. 12-27.
20.
Red Light Running Literature. Photocop, Cedar Park, TX.
http://www.photocop.com/red-light.htm. Accessed August 2, 2001.
21.
Retting, R.A., Statement before the Kentucky Senate Transportation Committee,
On Red Light Violations and Red Light Cameras, March 9, 2000, Insurance
Institute for Highway Safety.
22.
Retting, R.A. and M.A. Greene, “Influence of Traffic Signal Timing on Red-Light
Running and Potential Vehicle Conflicts at Urban Intersections”, Transportation
Research Record 1595, TRB, Washington, D.C., 1997.
23.
Retting, R.A. and A.F. Williams. Public Opinion Regarding Red Light Cameras
and the Perceived Risk of Being Ticketed. Transportation Research Board 79th
Annual Meeting (Pre-print, CD-ROM). TRB, National Research Council,
Washington,D.C., January 2000, pp. 1-5.
24.
Tarawneh, T.M., V.A. Singh, and P.T. McCoy, “Investigation of Effectiveness of
Media Advertising and Police Enforcement in Reducing Red-Light Violations”,
Transportation Research Record 1693, TRB, Washington, D.C. 1999.
25.
Urban Transportation Monitor. “Battle Lines Drawn in California Legislature
Over Red Light Running Cameras”, May 22, 1998, p. 3.
Wissinger, L., J. Hummer, J. Milazzo II. Using Focus Groups to Investigate the
Issues Surrounding Red Light Running. Transportation Research Board 79th
Annual Meeting (Preprint CD-ROM), Transportation Research Board, National
Research Council, Washington, D.C., Jan. 2000, pp.1-28.
26.