Effects of red light camera enforcement on fatal crashes in large U.S. cities

Objective

To estimate the effects of red light camera enforcement on per capita fatal crash rates at intersections with signal lights.

Methods

From the 99 large U.S. cities with more than 200,000 residents in 2008, 14 cities were identified with red light camera enforcement programs for all of 2004-2008 but not at any time during 1992-1996, and 48 cities were identified without camera programs during either period. Analyses compared the citywide per capita rate of fatal red light running crashes and the citywide per capita rate of all fatal crashes at signalized intersections during the two study periods, and rate changes then were compared for cities with and without cameras programs. Poisson regression was used to model crash rates as a function of red light camera enforcement, land area, and population density.

Results

The average annual rate of fatal red light running crashes declined for both study groups, but the decline was larger for cities with red light camera enforcement programs than for cities without camera programs (35% vs. 14%). The average annual rate of all fatal crashes at signalized intersections decreased by 14% for cities with camera programs and increased slightly (2%) for cities without cameras. After controlling for population density and land area, the rate of fatal red light running crashes during 2004-2008 for cities with camera programs was an estimated 24% lower than what would have been expected without cameras. The rate of all fatal crashes at signalized intersections during 2004-2008 for cities with camera programs was an estimated 17% lower than what would have been expected without cameras.

Conclusions

Red light camera enforcement programs were associated with a statistically significant reduction in the citywide rate of fatal red light running crashes and a smaller but still significant reduction in the rate of all fatal crashes at signalized intersections.

Impact on Industry

The study adds to the large body of evidence that red light camera enforcement can prevent the most serious crashes. Communities seeking to reduce crashes at intersections should consider this evidence.     

Effects of turning on and off red light cameras on fatal crashes in large U.S. cities

IntroductionThis study updates estimates of effects of activating red light cameras and offers a first look at effects of turning them off.MethodAmong 117 large U.S. cities with more than 200,000 residents in 2014, trends in citywide per capita rates of fatal red light running crashes and of all fatal crashes at signalized intersections were compared between 57 cities that initiated camera programs during 1992–2014 and 33 cities without cameras to examine effects of activating camera programs. Trends also were compared between 19 cities that removed cameras and 31 regionally matched cities with continuous camera programs to evaluate effects of terminating camera programs. Because several cities removed cameras during 2005–2008 and estimated effects might have been confounded by the subsequent economic downturn, primary analyses were limited to the 14 cities that removed cameras during 2010–2014 and 29 regionally matched cities with continuous camera programs. Poisson regression examined the relationship of activating and deactivating cameras with fatal crash rates.ResultsAfter controlling for temporal trends in annual fatal crash rates, population density, and unemployment rates, rates of fatal red light running crashes and of all fatal crashes at signalized intersections were 21% and 14% lower, respectively, in cities with cameras after cameras were turned on than would have been expected without cameras; 30% and 16% higher, respectively, in 14 cities that terminated cameras during 2010–2014 after cameras were terminated than expected had cameras remained; and 18% and 8% higher, respectively, in all 19 cities that removed cameras, but not significantly.ConclusionsThis study adds to the body of evidence that red light cameras can reduce the most serious crashes at signalized intersections, and is the first to demonstrate that removing cameras increases fatal crashes.Practical applicationsCommunities thinking about removing cameras should consider impacts to safety.     

Effects of red light running camera systems installation and then deactivation on intersection safety

IntroductionThe primary objective of this paper is to evaluate the safety impacts of red-light running camera (RLC) system installation and then deactivation at 48 intersections in Houston, Texas. The second objective is to evaluate the spillover effect at nearby non-treated intersections in Houston after the deactivation.MethodsTo accomplish study objectives, an Empirical Bayes (EB) before-after analysis was used.ResultsThe results indicate statistically significant collision reductions on all red-light running (RLR) crash types (37 percent) as well as right-angle RLR crashes (47 percent) at the treated intersections after RLC activation. By way of comparison, the RLC deactivation analysis indicated that crashes increased by 20 percent for all RLR crash types and by 23 percent in right-angle RLR crashes at the formerly treated intersections. After deactivation, all severity RLR crashes increased more than expected at nearby non-treated intersections, which indicates the possibility of an adverse spillover effect. However, fatal/injury crashes associated with rear-end decreased after deactivation at both formerly treated and non-treated intersections, although those rear-end crashes account for smaller proportions when compared to all crash types/right-angle crashes.Practical applicationsOverall, removing RLC treatments results in a negative reaction to the safety benefits that the treatment provides when it is in place and actively working and to the nearby intersections where the treatment has not been implemented. This study helps define the effects that RLCs have on safety at signalized intersections after installation and deactivation.     

Analyses of rear-end crashes based on classification tree models

OBJECTIVE: Signalized intersections are accident-prone areas especially for rear-end crashes due to the fact that the diversity of the braking behaviors of drivers increases during the signal change. The objective of this article is to improve knowledge of the relationship between rear-end crashes occurring at signalized intersections and a series of potential traffic risk factors classified by driver characteristics, environments, and vehicle types. METHODS: Based on the 2001 Florida crash database, the classification tree method and Quasi-induced exposure concept were used to perform the statistical analysis. Two binary classification tree models were developed in this study. One was used for the crash comparison between rear-end and non-rear-end to identify those specific trends of the rear-end crashes. The other was constructed for the comparison between striking vehicles/drivers (at-fault) and struck vehicles/drivers (not-at-fault) to find more complex crash pattern associated with the traffic attributes of driver, vehicle, and environment. RESULTS: The modeling results showed that the rear-end crashes are over-presented in the higher speed limits (45-55 mph); the rear-end crash propensity for daytime is apparently larger than nighttime; and the reduction of braking capacity due to wet and slippery road surface conditions would definitely contribute to rear-end crashes, especially at intersections with higher speed limits. The tree model segmented drivers into four homogeneous age groups: < 21 years, 21-31 years, 32-75 years, and > 75 years. The youngest driver group shows the largest crash propensity; in the 21-31 age group, the male drivers are over-involved in rear-end crashes under adverse weather conditions and the 32-75 years drivers driving large size vehicles have a larger crash propensity compared to those driving passenger vehicles. CONCLUSIONS: Combined with the quasi-induced exposure concept, the classification tree method is a proper statistical tool for traffic-safety analysis to investigate crash propensity. Compared to the logistic regression models, tree models have advantages for handling continuous independent variables and easily explaining the complex interaction effect with more than two independent variables. This research recommended that at signalized intersections with higher speed limits, reducing the speed limit to 40 mph efficiently contribute to a lower accident rate. Drivers involved in alcohol use may increase not only rear-end crash risk but also the driver injury severity. Education and enforcement countermeasures should focus on the driver group younger than 21 years. Further studies are suggested to compare crash risk distributions of the driver age for other main crash types to seek corresponding traffic countermeasures.     

Evaluation of countermeasures for red light running by traffic simulator–based surrogate safety measures

Objective: The conflicts among motorists entering a signalized intersection with the red light indication have become a national safety issue. Because of its sensitivity, efforts have been made to investigate the possible causes and effectiveness of countermeasures using comparison sites and/or before-and-after studies. Nevertheless, these approaches are ineffective when comparison sites cannot be found, or crash data sets are not readily available or not reliable for statistical analysis. Considering the random nature of red light running (RLR) crashes, an inventive approach regardless of data availability is necessary to evaluate the effectiveness of each countermeasure face to face.

Method: The aims of this research are to (1) review erstwhile literature related to red light running and traffic safety models; (2) propose a practical methodology for evaluation of RLR countermeasures with a microscopic traffic simulation model and surrogate safety assessment model (SSAM); (3) apply the proposed methodology to actual signalized intersection in Virginia, with the most prevalent scenarios—increasing the yellow signal interval duration, installing an advance warning sign, and an RLR camera; and (4) analyze the relative effectiveness by RLR frequency and the number of conflicts (rear-end and crossing).

Results: All scenarios show a reduction in RLR frequency (?7.8, ?45.5, and ?52.4%, respectively), but only increasing the yellow signal interval duration results in a reduced total number of conflicts (?11.3%; a surrogate safety measure of possible RLR-related crashes). An RLR camera makes the greatest reduction (?60.9%) in crossing conflicts (a surrogate safety measure of possible angle crashes), whereas increasing the yellow signal interval duration results in only a 12.8% reduction of rear-end conflicts (a surrogate safety measure of possible rear-end crash).

Conclusions: Although increasing the yellow signal interval duration is advantageous because this reduces the total conflicts (a possibility of total RLR-related crashes), each countermeasure shows different effects by RLR-related conflict types that can be referred to when making a decision. Given that each intersection has different RLR crash issues, evaluated countermeasures are directly applicable to enhance the cost and time effectiveness, according to the situation of the target intersection. In addition, the proposed methodology is replicable at any site that has a dearth of crash data and/or comparison sites in order to test any other countermeasures (both engineering and enforcement countermeasures) for RLR crashes.     

Investigation of crashes at pedestrian hybrid beacons: Results of a large-scale study in Arizona

Introduction: The pedestrian hybrid beacon (PHB) is a traffic control device used at pedestrian crossings. A recent Arizona Department of Transportation research effort investigated changes in crashes for different severity levels and crash types (e.g., rear-end crashes) due to the PHB presence, as well as for crashes involving pedestrians and bicycles. Method: Two types of methodologies were used to evaluate the safety of PHBs: (a) an Empirical Bayes (EB) before-after study, and (b) a long-term cross-sectional observational study. For the EB before-after evaluation, the research team considered three reference groups: unsignalized intersections, signalized intersections, and both unsignalized and signalized intersections combined. Results: For the signalized and combined unsignalized and signalized intersection groups, all crash types considered showed statistically significant reductions in crashes (e.g., total crashes, fatal and injury crashes, rear-end crashes, fatal and injury rear-end crashes, angle crashes, fatal and injury angle crashes, pedestrian-related crashes, and fatal and injury pedestrian-related crashes). A cross-sectional study was conducted with a larger number of PHBs (186) to identify relationships between roadway characteristics and crashes at PHBs, especially with respect to the distance to an adjacent traffic control signal. The distance to an adjacent traffic signal was found to be significant only at the α = 0.1 level, and only for rear-end and fatal and injury rear-end crashes. Conclusions: This analysis represents the largest known study to date on the safety impacts of PHBs, along with a focus on how crossing and geometric characteristics affect crash patterns. The study showed the safety benefits of PHBs for both pedestrians and vehicles. Practical Applications: The findings from this study clearly support the installation of PHBs at midblock or intersection crossings, as well as at crossings on higher-speed roads.     

Examining driver behavior using data gathered from red light photo enforcement cameras

INTRODUCTION: To develop an effective driver assistance system that can prevent red light violations, it is important to have a thorough understanding of contributing factors and circumstances surrounding such violations. METHODS: Red light violation behavior was examined using about 47,000 violation records that were captured by photo enforcement cameras from 11 signalized intersections in the city of Sacramento, California, over a four-year period. This examination identified factors with strong correlation to red light running behavior. RESULTS: Key findings based on Sacramento's red light violation records include: (a) younger drivers showed a higher tendency of running the red light and were more likely to commit such a violation at speeds above the posted speed limit; (b) off-peak time period between 8 p.m. to 5 a.m. had lower violation counts, but red light violators in this time frame had a higher propensity of racing through intersections at high speeds; (c) also during the time period between 8 p.m. to 5 a.m., violators showed a higher probability of entering intersections two or more seconds after the onset of red light; and (d) violators were less likely to cross high traffic-volume intersections with speeds greater than the posted speed limit. DISCUSSION: Sacramento's data suggest that some red light violators might have committed such an offense unintentionally. The top three violation speeds were all below 20 mph and more than 94% of red light runners crossed intersections within 2 seconds after the onset of the red light. IMPACT ON INDUSTRY: In the next several years, studies will be executed to assess whether a red light violation warning system can reduce "unintentional red light running" such as drivers who made incorrect judgment regarding the adequate time to clear the intersection and inattentive motorists who fail to observe the presence and status of the red light.     

Factors leading to older drivers' intersection crashes

OBJECTIVES: Older drivers are overinvolved in intersection crashes compared with younger drivers, but the reasons are not clearly understood. The purpose of the present study was to identify the factors that lead to older drivers' intersection crashes. METHOD: Study participants were composed of two groups of older drivers -- ages 70-79 (n = 78) and 80 and older (n = 76) -- and a comparison group of drivers ages 35-54 (n = 73); all were at fault in intersection crashes involving nonfatal injuries. Police crash reports, telephone interviews with at-fault drivers, and photographs of intersections were used to determine the kinds of driver actions and errors that led to the intersection crashes. RESULTS: Drivers 80 and older had fewer rear-end crashes than drivers ages 35-54 and 70-79, and both groups of older drivers had fewer ran-off-road crashes than drivers ages 35-54. Crashes where drivers failed to yield the right-of-way increased with age and occurred mostly at stop sign-controlled intersections, generally when drivers were turning left. The reasons for failure-to-yield crashes tended to vary by age. Compared with drivers ages 35-54 and 80 and older, drivers ages 70-79 made more evaluation errors -- seeing another vehicle but misjudging whether there was adequate time to proceed. In contrast, drivers 80 and older predominantly failed to see or detect the other vehicle. Drivers ages 35-54 also tended to make search errors, but theirs were due more often to distraction. CONCLUSIONS: Factors leading to intersection crashes vary with age, even between two age groups of older drivers. Because the number of older drivers is projected to increase, it is important to identify ways to reduce the frequency and severity of their intersection crashes. Roundabouts and protected left turn lanes at signalized intersections may help to reduce failure-to-yield crashes at intersections, especially among older drivers. Crash avoidance systems may help to reduce crashes for drivers of all ages, but most systems have not been thoroughly investigated using real-world crash data.     

Red light violations at rural and suburban signalized intersections in Jordan

This case study investigated red light violations at rural and suburban signalized intersections in Jordan. Field observations were conducted at 15 signalized intersections located in different Jordanian regions: Amman, Irbid, and Zarqa. The results showed that, out of a total of 1,190 drivers who had a chance for violation, 153 (12.9%) drivers ran red lights. It was found that older drivers have less tendency for running red lights. Based on vehicle type, the analysis showed that truck drivers had the highest violation rate followed by small vehicles and then buses. The Y-shaped intersection had a higher percentage of violations as compared to the T- and cruciform-shaped intersections. The percentage of red light violations was found to be directly proportional to the subjects approach speed and inversely proportional to the conflicting traffic volumes.     

Safety analysis of urban signalized intersections under mixed traffic

IntroductionThis study examined the crash causative factors of signalized intersections under mixed traffic using advanced statistical models.MethodHierarchical Poisson regression and logistic regression models were developed to predict the crash frequency and severity of signalized intersection approaches. The prediction models helped to develop general safety countermeasures for signalized intersections.ResultsThe study shows that exclusive left turn lanes and countdown timers are beneficial for improving the safety of signalized intersections. Safety is also influenced by the presence of a surveillance camera, green time, median width, traffic volume, and proportion of two wheelers in the traffic stream. The factors that influence the severity of crashes were also identified in this study.Practical applicationAs a practical application, the safe values of deviation of green time provided from design green time, with varying traffic volume, is presented in this study. This is a useful tool for setting the appropriate green time for a signalized intersection approach with variations in the traffic volume.     

Analysis of motor-vehicle crashes at stop signs in four US cities

Problem: Nearly 700,000 police-reported motor vehicle crashes occur annually at stop signs, and approximately one-third of these crashes involve injuries. The purpose of this study was to develop a better understanding of the crashes that occur at stop signs and to identify potential countermeasures. Method: Police reports of crashes at stop sign-controlled intersections during 1996–2000 in four U.S. cities were examined in detail. At total of 1,788 crash reports for intersections with two-way stop signs were included in the study. Results: Stop sign violations accounted for about 70% of all crashes. Typically these crashes were angular collisions. Among crashes not involving stop violations, rear-end crashes were most common, accounting for about 12% of all crashes. Stop sign violation crashes were classified into several subtypes — driver stopped, driver did not stop, snow/wet/ice, and other/unknown. In about two-thirds of stop sign violation crashes, drivers said they had first come to a stop. In these cases, inability or failure to see approaching traffic often was cited as the cause of the crash. Drivers younger than 18 as well as drivers 65 and older were disproportionately found to be at fault in crashes at stop signs. Impact on industry: Potential countermeasures include changing traffic control and intersection design, improving intersection sight distance, and increasing conspicuity of stop signs through supplemental pavement markings and other devices.     

Analysis of the injury severity of crashes by considering different lighting conditions on two-lane rural roads

IntroductionMany studies have examined different factors contributing to the injury severity of crashes; however, relatively few studies have focused on the crashes by considering the specific effects of lighting conditions. This research investigates lighting condition differences in the injury severity of crashes using 3-year (2009–2011) crash data of two-lane rural roads of the state of Washington.MethodSeparate ordered-probit models were developed to predict the effects of a set of factors expected to influence injury severity in three lighting conditions; daylight, dark, and dark with street lights. A series of likelihood ratio tests were conducted to determine if these lighting condition models were justified.ResultsThe modeling results suggest that injury severity in specific lighting conditions are associated with contributing factors in different ways, and that such differences cannot be uncovered by focusing merely on one aggregate model. Key differences include crash location, speed limit, shoulder width, driver action, and three collision types (head-on, rear-end, and right-side impact collisions).Practical ApplicationsThis paper highlights the importance of deploying street lights at and near intersections (or access points) on two-lane rural roads because injury severity highly increases when crashes occur at these points in dark conditions.     

The effects of mobile speed camera introduction on road traffic crashes and casualties in a rural county of England

PROBLEM: This study assesses the impact of crash and casualty numbers in correspondence to the introduction of mobile speed cameras in the rural county of Norfolk, England. METHOD: Road traffic accident casualty and crash data were collected for two years before the introduction of cameras and two years subsequently. The casualties and crashes occurring at 29 camera sites were identified and separated from those occurring in the rest of the county. Trends in crashes and casualties, and their severity, were examined graphically and comparisons were made between before and after periods. The regression to the mean effect at individual sites was estimated. RESULTS: After the introduction of cameras, overall crashes declined by 1% and crashes involving fatalities or serious injuries declined by 9% on the roads without cameras. At the camera sites, crashes decreased by 19% and fatal and serious crashes by 44%. The reduction in total crashes was significantly greater than that expected from the effect of regression to the mean in 12 out of 20 sites tested. SUMMARY: The introduction of cameras appears to have resulted in real and measurable reductions in crash risk in this rural county. IMPACT ON INDUSTRY: Our results suggest the deployment of mobile speed cameras is an effective tool for organizations wishing to reduce road traffic casualties in areas where high crash rates have been associated with excessive vehicle speeds.     

Some determinants of possible injuries in crashes at signalized intersections

INTRODUCTION: This paper identifies some determinants of possible injuries from crashes that occur at signalized intersections using a conditional probability model. METHOD: It uses longitudinal data for one city and calculates the marginal effects of these determinants. RESULTS: Among its findings, an airbag deploying in a crash reduces the conditional probability of sustaining possible injury. The size of this decrease is similar for the front airbag or both side airbags deploying. When crashes occur because a driver suddenly falls ill, or because a driver has an existing medical condition that flares up, the results show that the conditional probability of sustaining possible injury increases by 0.1414 and 0.1217, respectively. In comparison the conditional probability of sustaining possible injury increases by 0.0706 when the crash is because of impairment from drugs or alcohol. Additionally, the probability of sustaining possible injury in the event of a crash is 0.0435 and 0.0459 higher in passenger cars and vans respectively than in other vehicles. CONCLUSIONS: Comparing these results to those in the traffic safety literature, the marginal effects from national data are similar to those from local level data.     

Disaggregated traffic conditions and road crashes in urban signalized intersections

Introduction: Road safety studies in signalized intersections have been performed extensively using annually aggregated traffic variables and crash frequencies. However, this type of aggregation reduces the strength of the results if variables that oscillate over the course of the day are considered (speed, traffic flow, signal cycle length) because average indicators are not able to describe the traffic conditions preceding the crash occurrence. This study aims to explore the relationship between traffic conditions aggregated in 15-min intervals and road crashes in urban signalized intersections. Method: First, an investigation of the reported crash times in the database was conducted to obtain the association between crashes and their precursor conditions. Then, 4.1 M traffic condition intervals were consolidated and grouped using a hierarchical clustering technique. Finally, charts of the frequency of crashes per cluster were explored. Results: The main findings suggest that high vehicular demand conditions are related to an increase in property damage only (PDO) crashes, and an increase in the number of lanes is linked to more PDO and injury crashes. Injury crashes occurred in a wide range of traffic conditions, indicating that a portion of these crashes were due to speeding, while the other fraction was associated with the vulnerability of road users. Traffic conditions with: (a) low vehicular demand and a long cycle length and (b) high vehicular demand and a short cycle length were critical in terms of PDO and injury crashes. Practical Applications: The use of disaggregated data allowed for a stronger evaluation of the relationship between road crashes and variables that oscillate over the course of the day. This approach also permits the development of real-time risk management strategies to mitigate the frequency of critical traffic conditions and reduce the likelihood of crashes.     

Investigating the impacts of crash prediction models on quantifying safety effectiveness of Adaptive Signal Control Systems

Introduction: Adaptive Signal Control System (ASCS) can improve both operational and safety benefits at signalized corridors. Methods: This paper develops a series of models accounting for model forms and possible predictors and implements these models in Empirical Bayes (EB) and Fully Bayesian (FB) frameworks for ASCS safety evaluation studies. Different models are validated in terms of the ability to reduce the potential bias and variance of prediction and improve the safety effectiveness estimation accuracy using real-world crash data from non-ASCS sites. This paper then develops the safety effectiveness of ASCS at six different corridors with a total of 65 signalized intersections with the same type of ASCS, in South Carolina. Results: Validation results show that the FB model that accounts for traffic volume, roadway geometric features, year factor, and spatial effects shows the best performance among all models. The study findings reveal that ASCS reduces crash frequencies in the total crash, fatal and injury crash, and angle crash for most of the intersections. The safety effectiveness of ASCS varies with different intersection features (i.e., AADT at major streets, number of legs at an intersection, the number of through lanes on major streets, the number of access points on minor streets, and the speed limit at major streets). Conclusions: ASCS is associated with crash reductions, and its safety effects vary with different intersection features. Practical Applications: The findings of this research encourage more ASCS deployments and provide insights into selecting ASCS deployment sites for reducing crashes considering the variation of the safety effectiveness of ASCS.     

Using event-triggered naturalistic data to examine the prevalence of teen driver distractions in rear-end crashes

IntroductionWhile teen driver distraction is cited as a leading cause of crashes, especially rear-end crashes, little information is available regarding its true prevalence. The majority of distraction studies rely on data derived from police reports, which provide limited information regarding driver distraction.MethodThis study examined over 400 teen driver rear-end crashes captured by in-vehicle event recorders. A secondary data analysis was conducted, paying specific attention to driver behaviors, eyes-off-road time, and response times to lead-vehicle braking.ResultsAmong teens in moderate to severe rear-end crashes, over 75% of drivers were observed engaging in a potentially distracting behavior. The most frequently seen driver behaviors were cell phone use, attending to a location outside the vehicle, and attending to passengers. Drivers using a cell phone had a significantly longer response time than drivers not engaged in any behaviors, while those attending to passengers did not. Additionally, in about 50% of the rear-end crashes where the driver was operating/looking at a phone (e.g., texting), the driver showed no driver response (i.e., braking or steering input) before impact, compared to 10% of crashes where the driver was attending to a passenger.ConclusionsThe high frequency of attending to passengers and use of a cell phone leading up to a crash, compounded with the associated risks, underlines the importance of continued investigation in these areas.Practical applicationsParents and teens must be educated regarding the frequency of and the potential effects of distractions. Additional enforcement may be necessary if Graduated Driver Licensing (GDL) programs are to be effective. Systems that alert distracted teens could also be especially helpful in reducing rear-end collisions.     

Effect of pavement condition and geometrics at signalised intersections on casualty crashes

IntroductionThis study investigated the effects of pavement surface condition and other control factors on casualty crashes at signalized intersections. It involved conducting a before and after study for road surface condition and situational factors. It also included assessing the effects of geometric characteristics on safety performance of signalized intersections post resurfacing to control for the effect of pavement surface condition. Pavement surface condition included roughness, rutting, and skid resistance. The control factors included traffic volume, light and surface moisture condition, and speed limit. The geometric characteristics included approach width, number of lanes, intersection depth, presence of median, presence of shared lane, and presence of bus stop.MethodTo account for the repeated observations of the effect of light and surface moisture conditions in four occasions (day-dry, day-wet, night-dry and night-wet) Generalized Estimating Equation (GEE) with Negative Binomial (NB) and log link function was applied. For each signalized intersection in the sample, condition data are collected for the year before and after the year of surface treatment. Crash data, however, are collected for a minimum of three and maximum of five years before and after treatment years.ResultsThe results show that before treatment, light condition, road surface moisture condition, and skid resistance interaction with traffic volume are the significant contributors to crash occurrence. For after treatment; light condition, road surface moisture condition, their interaction product, and roughness interaction with light condition, surface moisture condition, and traffic volume are the significant contributors. The geometric variables that were found to have significant effects on crash frequency post resurfacing were approach width interactions with presence of shared lane, bus stop, or median.ConclusionsThe findings confirm that resurfacing is significant in reducing crash frequency and severity levels.Practical Applications: The study findings would help for better understanding of how geometric characteristics can be improved to reduce crash occurrence.