Effects of red light cameras on violations and crashes: a review of the international literature

Red light running is a frequent cause of motor vehicle crashes and injuries. A primary countermeasure for red light running crashes is police traffic enforcement. In recent years, many police agencies have begun using automated red light cameras as a supplement to conventional enforcement methods. The present study reviewed and evaluated available evidence in the international literature regarding the effectiveness of cameras to reduce both red light violations and crashes. Camera enforcement generally reduces violations by an estimated 40-50%. In terms of crash effects, most studies contain methodological flaws that, to varying degrees, either overestimate (failure to adjust for regression to the mean) or underestimate (comparison with nearby signalized intersections affected by cameras) crash effects. Mindful of these limitations, the research generally indicates that camera enforcement can significantly reduce injury crashes at signalized intersections, in particular right-angle injury crashes. Most studies reported increases in rear-end crashes following camera installation. Taken together the studies indicate that, overall, injury crashes, including rear-end collisions, were reduced by 25-30% as a result of camera enforcement.     

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.     

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.     

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.     

Estimating safety effects of adaptive signal control technology using the Empirical Bayes method

IntroductionAdaptive signal control technology (ASCT) has long been investigated for its operational benefits, but the safety impacts of this technology are still unclear. The main purpose of this study was to determine the safety effect of ASCT at urban/suburban intersections by assessing two different systems.MethodCrash data for 41 intersections from the Pennsylvania Department of Transportation (PennDOT), along with crash frequencies computed through Safety Performance Functions (SPFs), were used to perform the Empirical Bayes (E-B) method to develop crash modification factors (CMF) for ASCT. Moreover, a crash type analysis was conducted to examine the safety impact of ASCT on a regional scale and the variation of safety among type of crashes observed.ResultsThe results from this study indicated the potential of ASCT to reduce crashes since the Crash Modification Factor (CMF) values for both ASCT systems (SURTRAC and InSync) showed significant reductions in crashes. Average CMF values of 0.87 and 0.64 were observed for total and fatal and injury crash categories at a 95% confidence level, and results were consistent between systems. While a reduction in the proportion of rear end crashes was observed, the change was not determined to be statistically significant. The overall distribution of crash types did not change significantly when ASCT was deployed.Conclusion and practical applicationThe results indicate that safety benefits of ASCT were generally consistent across systems, which should aid agencies in making future deployment decisions on ASCT.     

A simultaneous equations model of crash frequency by collision type for rural intersections

Safety at roadway intersections is of significant interest to transportation professionals due to the large number of intersections in transportation networks, the complexity of traffic movements at these locations that leads to large numbers of conflicts, and the wide variety of geometric and operational features that define them. A variety of collision types including head-on, sideswipe, rear-end, and angle crashes occur at intersections. While intersection crash totals may not reveal a site deficiency, over exposure of a specific crash type may reveal otherwise undetected deficiencies. Thus, there is a need to be able to model the expected frequency of crashes by collision type at intersections to enable the detection of problems and the implementation of effective design strategies and countermeasures. Statistically, it is important to consider modeling collision type frequencies simultaneously to account for the possibility of common unobserved factors affecting crash frequencies across crash types. In this paper, a simultaneous equations model of crash frequencies by collision type is developed and presented using crash data for rural intersections in Georgia. The model estimation results support the notion of the presence of significant common unobserved factors across crash types, although the impact of these factors on parameter estimates is found to be rather modest.     

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.     

Characteristics of rear-end crashes involving passenger vehicles with automatic emergency braking

Abstract

Objectives: Automatic emergency braking (AEB) is a proven effective countermeasure for preventing front-to-rear crashes, but it has not yet fully lived up to its estimated potential. This study identified the types of rear-end crashes in which striking vehicles with AEB are overrepresented to determine whether the system is more effective in some situations than in others, so that additional opportunities for increasing AEB effectiveness might be explored.

Methods: Rear-end crash involvements were extracted from 23?U.S. states during 2009–2016 for striking passenger vehicles with and without AEB among models where the system was optional. Logistic regression was used to examine the odds that rear-end crashes with various characteristics involved a striking vehicle with AEB, controlling for driver and vehicle features.

Results: Striking vehicles were significantly more likely to have AEB in crashes where the striking vehicle was turning relative to when it was moving straight (odds ratio [OR]?=?2.35; 95% confidence interval [CI], 1.76, 3.13); when the struck vehicle was turning (OR = 1.66; 95% CI, 1.25, 2.21) or changing lanes (OR = 2.05; 95% CI, 1.13, 3.72) relative to when it was slowing or stopped; when the struck vehicle was not a passenger vehicle or was a special use vehicle relative to a car (OR = 1.61; 95% CI, 1.01, 2.55); on snowy or icy roads relative to dry roads (OR = 1.83; 95% CI, 1.16, 2.86); or on roads with speed limits of 70+ mph relative to those with 40 to 45?mph speed limits (OR = 1.49; 95% CI, 1.10, 2.03). Overall, 25.3% of crashes where the striking vehicle had AEB had at least one of these overrepresented characteristics, compared with 15.9% of strikes by vehicles without AEB.

Conclusions: The typical rear-end crash occurs when 2 passenger vehicles are proceeding in line, on a dry road, and at lower speeds. Because atypical crash circumstances are overrepresented among rear-end crashes by striking vehicles with AEB, it appears that the system is doing a better job of preventing the more typical crash scenario. Consumer information testing programs of AEB use a test configuration that models the typical rear-end crash type. Testing programs promoting good AEB performance in crash circumstances where vehicles with AEB are overrepresented could guide future development of AEB systems that perform well in these additional rear-end collision scenarios.     

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.     

Safety effectiveness and crash cost benefit of red light cameras in Missouri

Objective: Red light cameras (RLCs) have generated heated discussions over issues of safety effectiveness, revenue generation, and procedural due process. This study focuses on the safety evaluation of RLCs in Missouri, including the economic valuation of safety benefits. The publication of the national Highway Safety Manual (HSM; American Association of State Highway and Transportation Officials) in 2010 produced statistical safety models for intersections and spurred the calibration of these models to local conditions.

Methods: This study adds to existing knowledge by applying the latest statistical methodology presented in the HSM and more current data. Driver behavior constantly changes due in part to driving conditions and the use of technology. The safety and economic benefit evaluation was performed using the empirical Bayes method, which accounts for regression to the mean bias. For the economic benefit evaluation, the KABCO crash severity scale and crash cost estimates were used. A total of 24 4-leg urban intersections were randomly selected from a master list of RLCs in Missouri from 2006 to 2011. Additionally, 35 comparable nontreated intersections were selected for the analysis.

Results and Conclusions: The implementation of RLCs reduced overall angle crashes by 11.6%, whereas rear-end crashes increased by 16.5%. The net economic crash cost benefit of the implementation of RLCs was $35,269 per site per year in 2001 dollars (approximately $47,000 in 2015 dollars). Thus, RLCs produced a sizable net positive safety benefit that is consistent with previous statistical studies.     

Quantifying the impact of adaptive traffic control systems on crash frequency and severity: Evidence from Oakland County,Michigan

IntroductionDespite seeing widespread usage worldwide, adaptive traffic control systems have experienced relatively little use in the United States. Of the systems used, the Sydney Coordinated Adaptive Traffic System (SCATS) is the most popular in America. Safety benefits of these systems are not as well understood nor as commonly documented.MethodThis study investigates the safety benefits of adaptive traffic control systems by using the large SCATS-based system in Oakland County, MI known as FAST-TRAC. This study uses data from FAST-TRAC-controlled intersections in Oakland County and compares a wide variety of geometric, traffic, and crash characteristics to similar intersections in metropolitan areas elsewhere in Michigan. Data from 498 signalized intersections are used to conduct a cross-sectional analysis. Negative binomial models are used to estimate models for three dependent crash variables. Multinomial logit models are used to estimate an injury severity model. A variable tracking the presence of FAST-TRAC controllers at intersections is used in all models to determine if a SCATS-based system has an impact on crash occurrences or crash severity.ResultsEstimates show that the presence of SCATS-based controllers at intersections is likely to reduce angle crashes by up to 19.3%. Severity results show a statistically significant increase in non-serious injuries, but not a significant reduction in incapacitating injuries or fatal accidents.     

The interactive effect on injury severity of driver-vehicle units in two-vehicle crashes

IntroductionThis study sets out to investigate the interactive effect on injury severity of driver-vehicle units in two-vehicle crashes.MethodA Bayesian hierarchical ordered logit model is proposed to relate the variation and correlation of injury severity of drivers involved in two-vehicle crashes to the factors of both driver-vehicle units and the crash configurations. A total of 6417 crash records with 12,834 vehicles involved in Florida are used for model calibration.ResultsThe results show that older, female and not-at-fault drivers and those without use of safety equipment are more likely to be injured but less likely to injure the drivers in the other vehicles. New vehicles and lower speed ratios are associated with lower injury degree of both drivers involved. Compared with automobiles, vans, pick-ups, light trucks, median trucks, and heavy trucks possess better self-protection and stronger aggressivity. The points of impact closer to the driver's seat in general indicate a higher risk to the own drivers while engine cover and vehicle rear are the least hazardous to other drivers. Head-on crashes are significantly more severe than angle and rear-end crashes. We found that more severe crashes occurred on roadways than on shoulders or safety zones.ConclusionsBased on these results, some suggestions for traffic safety education, enforcement and engineering are made. Moreover, significant within-crash correlation is found in the crash data, which demonstrates the applicability of the proposed model.     

Comparison of Expected Crash and Injury Reduction from Production Forward Collision and Lane Departure Warning Systems

Objectives: The U.S. New Car Assessment Program (NCAP) now tests for forward collision warning (FCW) and lane departure warning (LDW). The design of these warnings differs greatly between vehicles and can result in different real-world field performance in preventing or mitigating the effects of collisions. The objective of this study was to compare the expected number of crashes and injured drivers that could be prevented if all vehicles in the fleet were equipped with the FCW and LDW systems tested under the U.S. NCAP.

Methods: To predict the potential crashes and serious injury that could be prevented, our approach was to computationally model the U.S. crash population. The models simulated all rear-end and single-vehicle road departure collisions that occurred in a nationally representative crash database (NASS-CDS). A sample of 478 single-vehicle crashes from NASS-CDS 2012 was the basis for 24,822 simulations for LDW. A sample of 1,042 rear-end collisions from NASS-CDS years 1997–2013 was the basis for 7,616 simulations for FCW. For each crash, 2 simulations were performed: (1) without the system present and (2) with the system present. Models of each production safety system were based on 54 model year 2010–2014 vehicles that were evaluated under the NCAP confirmation procedure for LDW and/or FCW. NCAP performed 40 LDW and 45 FCW tests of these vehicles.

Results: The design of the FCW systems had a dramatic impact on their potential to prevent crashes and injuries. Between 0 and 67% of crashes and 2 and 69% of moderately to fatally injured drivers in rear-end impacts could have been prevented if all vehicles were equipped with the FCW systems. Earlier warning times resulted in increased benefits. The largest effect on benefits, however, was the lower operating speed threshold of the systems. Systems that only operated at speeds above 20 mph were less than half as effective as those that operated above 5 mph with similar warning times. The production LDW systems could have prevented between 11 and 23% of drift-out-of-lane crashes and 13 and 22% of seriously to fatally injured drivers. A majority of the tested LDW systems delivered warnings near the point when the vehicle first touched the lane line, leading to similar benefits. Minimum operating speed also greatly affected LDW effectiveness.

Conclusions: The results of this study show that the expected field performance of FCW and LDW systems are highly dependent on the design and system limitations. Systems that delivered warnings earlier and operated at lower speeds may prevent far more crashes and injuries than systems that warn late and operate only at high speeds. These results suggest that future FCW and LDW evaluation should prioritize early warnings and full-speed range operation. A limitation of this study is that additional crash avoidance features that may also mitigate collisions—for example, brake assist, automated braking, or lane-keeping assistance—were not evaluated during the NCAP tests or in our benefits models. The potential additional mitigating effects of these systems were not quantified in this study.     

A multinomial logit model of motorcycle crash severity at Australian intersections

Introduction: Motorcyclists are exposed to more fatalities and severe injuries per mile of travel as compared to other vehicle drivers. Moreover, crashes that take place at intersections are more likely to result in serious or fatal injuries as compared to those that occur at non-intersections. Therefore, the purpose of this study is to evaluate the contributing factors to motorcycle crash severity at intersections. Method: A data set of 7,714 motorcycle crashes at intersections in the State of Victoria, Australia was analyzed over the period of 2006–2018. The multinomial logit model was used for evaluating the motorcycle crashes. The severity of motorcycle crashes was divided into three categories: minor injury, serious injury and fatal injury. The risk factors consisted of four major categories: motorcyclist characteristics, environmental characteristics, intersection characteristics and crash characteristics. Results: The results of the model demonstrated that certain factors increased the probability of fatal injuries. These factors were: motorcyclists aged over 59 years, weekend crashes, midnight/early morning crashes, morning rush hours crashes, multiple vehicles involved in the crash, t-intersections, crashes in towns, crashes in rural areas, stop or give-way intersections, roundabouts, and uncontrolled intersections. By contrast, factors such as female motorcyclists, snowy or stormy or foggy weather, rainy weather, evening rush hours crashes, and unpaved roads reduced the probability of fatal injuries. Practical Applications: The results from our study demonstrated that certain treatment measures for t-intersections may reduce the probability of fatal injuries. An effective way for improving the safety of stop or give-way intersections and uncontrolled intersections could be to convert them to all-way stop controls. Further, it is recommended to educate the older riders that with ageing, there are physiological changes that occur within the body which can increase both crash likelihood and injury severity.     

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.     

Spillover effects of yield-to-pedestrian channelizing devices

A great number of pedestrians are killed or injured in traffic crashes every year in the US. Vehicle crashes involving pedestrians are often more severe than other crashes because pedestrians are unprotected and are hence more likely to suffer injuries or death if struck by a motor vehicle. To improve pedestrian safety, a variety of treatments such as overhead flashing beacons, in-street crossing signs, in-roadway warning lights, and traffic calming measures have been used. One treatment, in-street yield-to-pedestrian channelizing devices (YTPCD), has been used in many states, including Pennsylvania, where approximately 10% of traffic crash fatalities are pedestrians each year.In an effort to improve pedestrian safety, the Pennsylvania Department of Transportation (PennDOT) has widely deployed YTPCD. This study examines the spillover (indirect) effects of such devices on motorist and pedestrian behavior. With data collected from eight sites that did not have but were in the vicinity of YTPCD implementations, analysis results show that such devices have significantly positive spillover effects on pedestrian safety at intersections, but they tend to have negative spillover effects at mid-block locations. Overall, the YTPCD appear to have a positive impact on changing motorist and pedestrian behavior, and merit consideration for future usage of this type of device.     

Use of empirical and full Bayes before–after approaches to estimate the safety effects of roadside barriers with different crash conditions

IntroductionAlthough many researchers have estimated the crash modification factors (CMFs) for specific treatments (or countermeasures), there is a lack of prior studies that have explored the variation of CMFs. Thus, the main objectives of this study are: (a) to estimate CMFs for the installation of different types of roadside barriers, and (b) to determine the changes of safety effects for different crash types, severities, and conditions.MethodTwo observational before–after analyses (i.e. empirical Bayes (EB) and full Bayes (FB) approaches) were utilized in this study to estimate CMFs. To consider the variation of safety effects based on different vehicle, driver, weather, and time of day information, the crashes were categorized based on vehicle size (passenger and heavy), driver age (young, middle, and old), weather condition (normal and rain), and time difference (day time and night time).ResultsThe results show that the addition of roadside barriers is safety effective in reducing severe crashes for all types and run-off roadway (ROR) crashes. On the other hand, it was found that roadside barriers tend to increase all types of crashes for all severities. The results indicate that the treatment might increase the total number of crashes but it might be helpful in reducing injury and severe crashes. In this study, the variation of CMFs was determined for ROR crashes based on the different vehicle, driver, weather, and time information.Practical applicationsBased on the findings from this study, the variation of CMFs can enhance the reliability of CMFs for different roadway conditions in decision making process. Also, it can be recommended to identify the safety effects of specific treatments for different crash types and severity levels with consideration of the different vehicle, driver, weather, and time of day information.     

An empirical bayes safety evaluation of tram/streetcar signal and lane priority measures in Melbourne

Objective: Streetcars/tram systems are growing worldwide, and many are given priority to increase speed and reliability performance in mixed traffic conditions. Research related to the road safety impact of tram priority is limited. This study explores the road safety impacts of tram priority measures including lane and intersection/signal priority measures.

Method: A before–after crash study was conducted using the empirical Bayes (EB) method to provide more accurate crash impact estimates by accounting for wider crash trends and regression to the mean effects. Before–after crash data for 29 intersections with tram signal priority and 23 arterials with tram lane priority in Melbourne, Australia, were analyzed to evaluate the road safety impact of tram priority.

Results: The EB before–after analysis results indicated a statistically significant adjusted crash reduction rate of 16.4% after implementation of tram priority measures. Signal priority measures were found to reduce crashes by 13.9% and lane priority by 19.4%. A disaggregate level simple before–after analysis indicated reductions in total and serious crashes as well as vehicle-, pedestrian-, and motorcycle-involved crashes. In addition, reductions in on-path crashes, pedestrian-involved crashes, and collisions among vehicles moving in the same and opposite directions and all other specific crash types were found after tram priority implementation.

Conclusions: Results suggest that streetcar/tram priority measures result in safety benefits for all road users, including vehicles, pedestrians, and cyclists. Policy implications and areas for future research are discussed.     

Whether conversion and weather matter to roundabout safety

IntroductionRoundabouts, as a form of intersection traffic control, are being constructed increasingly because of their promise to improve both efficiency and safety. However, roundabout performance varies from one context to another; and information on their performance during inclement weather is limited.MethodsTo evaluate the safety effects of converting signal-controlled intersections to modern roundabouts in a region that historically was unfamiliar with this type of traffic control, an empirical Bayes approach was used to analyze. Second, to examine the potential effects of rainfall on roundabout safety, a matched-pair approach was used to compare risk estimates of collision occurrence at roundabouts and signalized intersections under inclement weather conditions.ResultsRoundabout installation is shown as an effective safety intervention for serious collisions since conversion from signalized intersections to roundabouts translates into an overall 20% reduction in the occurrence of injury/fatal collisions. However, roundabouts witnessed more property-damage collisions than what would have been expected had the conversion not occurred. With respect to weather, there is no evidence of a statistically significant increase in crashes on days with rainfall relative to good weather conditions for roundabouts, whereas there is evidence of such an increase in crash risk estimated to be 4% to 22% for signalized intersections.ConclusionsWhile injury collisions are consistently found to be lower at intersections that have been converted from signalized intersections to roundabouts, the same is not always that case for property-damage collisions, suggesting that drivers need time to adjust. In terms of weather, the evidence in this paper shows that roundabouts show less sensitivity to rainy conditions than signalized intersections.Practical applicationsThe trade-offs between design, operation, and safety should be considered carefully when planning a new roundabout. More research is required on the specific problems users experience with roundabouts and the effectiveness of public education programs.