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 [email protected] 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.
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