Spatial Variability and Source-Receptor Relations at a Street Intersection

A wind tunnel study of dispersion at a simple urban intersection comprising two perpendicular streets is described. Concentration and flow field measurement were undertaken to determine the importance of the exchange of pollutants between the streets and to investigate source-receptor relationships at the intersection. The results showed that only in a symmetrical situation were exchanges negligible and that small departures from symmetry, brought about in the experiments through an off-set in the street alignment or a change of orientation relative to the wind, were sufficient to establish significant exchanges. The results also showed that significant structure appeared in the concentration fields in the streets as a result. Examples are shown where concentrations on one side of a street are entirely due to emissions from the perpendicular street, whereas on the opposite side concentrations depend on emission upwind in the same street as the receptor. The results imply that exchanges between street systems are likely to be the norm in practice and that the consequences of such exchanges are not confined to the immediate vicinity of the intersection.     

Design unbiased estimation in line intersect sampling using segmented transects

In many applications of line intersect sampling, transects consist of multiple, connected segments in a prescribed configuration. The relationship between the transect configuration and the selection probability of a population element is illustrated and a consistent sampling protocol, applicable to populations composed of arbitrarily shaped elements, is proposed. It is shown that this protocol obviates the arbitrary practice of treating multiple intersections of a single particle as independent probabilistic events and preserves the design-unbiasedness of Kaisers (1983, Biometrics 39, 965–976) conditional and unconditional estimators, suitably generalized to segmented transect designs. The relative efficiency and utility of segmented transect designs are also discussed from a fixed population perspective.     

Gap acceptance behavior at unsignalized intersections: Effects of using a phone and a music player while driving

Objectives: The present study is an attempt to analyze and compare the distraction effects caused by the use of a phone and a music player at unsignalized intersections.

Method: Eighty-eight participants performed simulated driving experiments where they faced a sequence of gaps in the major road traffic at 2 unsignalized intersections. In this process, their driving behavior was evaluated in terms of gap acceptance probability, accepted lag, and maneuver completion time. These parameters were modeled with a generalized estimating equation (GEE) method by considering distraction, demographic factors, driving history, maneuver types, and driving attributes in the approach and completion zones as independent variables.

Results: The results showed that gap acceptance probability decreased by 46% during the conversation task, whereas it increased by 66% during the music player task. Lower gap acceptance could be a compensatory behavior adopted by drivers during the conversation task, whereas no such measure was adapted during the music player task. The results indicate that a higher approach speed during the music player task might have led to increased gap acceptance. Further, though the effect of distraction on the accepted lag was not evident, the completion time was reduced during the conversation task.

Conclusions: Overall, the results suggest that drivers are more likely to adopt a compensatory measure in complex driving situations only if they perceive a high risk. Hence, drivers are exposed to a greater risk while operating a music player, because this is not perceived as risky behavior.     

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.     

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.     

A study of stopping propensity at matured red light camera T-intersections

PROBLEM: This paper evaluates the stopping propensity of drivers at matured in-service red light camera (RLC) signalized T-intersections after a number of years of camera operation. METHOD: A special-purpose data logger working in conjunction with loop sensors was used to gather traffic parameters, vehicle stopping/crossing movements, and signal phases at camera (treatment) and noncamera (comparison) approaches. Logistic modeling was employed to determine the stopping/crossing decisions of civilian vehicle drivers in response to the onset of yellow (amber) with traffic and the associated situational and behavioral variables, including their interactions. SUMMARY: The propensity to stop at camera approaches was about 17 times more than at noncamera approaches. This finding strongly affirmed the positive effect of RLC in encouraging drivers to stop. The likelihood to stop was about 6.5 times higher for an approach that faces an opposing right-turn conflict immediately after the onset of red. Higher stopping propensity was also more prevalent during weekdays and in periods of low traffic volumes. IMPACT ON INDUSTRY: The findings provided an objective measure on the effectiveness of RLC that would be useful to evaluate intersections for camera installation as well as on the implementation and operational aspects of RLC program.     

Analysis of driver injury severity levels at multiple locations using ordered probit models

Problem: The occurrence and outcome of traffic crashes have long been recognized as complex events involving interactions between many factors, including the roadway, driver, traffic characteristics, and the environment. This study is concerned with the outcome of the crash. Method: Driver injury severity levels are analyzed using the ordered probit modeling methodology. Models were developed for roadway sections, signalized intersections, and toll plazas in Central Florida. All models showed the significance of driver's age, gender, seat belt use, point of impact, speed, and vehicle type on the injury severity level. Other variables were found significant only in specific cases. Results: A driver's violation was significant in the case of signalized intersections. Alcohol, lighting conditions, and the existence of a horizontal curve affected the likelihood of injuries in the roadway sections' model. A variable specific to toll plazas, vehicles equipped with Electronic Toll Collection (ETC), had a positive effect on the probability of higher injury severity at toll plazas. Other variables that entered into some of the models were weather condition, area type, and some interaction factors. This study illustrates the similarities and the differences in the factors that affect injury severity between different locations.     

Analysis of Driver Evasive Maneuvering Prior to Intersection Crashes Using Event Data Recorders

Objective: Intersection crashes account for over 4,500 fatalities in the United States each year. Intersection Advanced Driver Assistance Systems (I-ADAS) are emerging vehicle-based active safety systems that have the potential to help drivers safely navigate across intersections and prevent intersection crashes and injuries. The performance of an I-ADAS is expected to be highly dependent upon driver evasive maneuvering prior to an intersection crash. Little has been published, however, on the detailed evasive kinematics followed by drivers prior to real-world intersection crashes. The objective of this study was to characterize the frequency, timing, and kinematics of driver evasive maneuvers prior to intersection crashes.

Methods: Event data recorders (EDRs) downloaded from vehicles involved in intersection crashes were investigated as part of NASS-CDS years 2001 to 2013. A total of 135 EDRs with precrash vehicle speed and braking application were downloaded to investigate evasive braking. A smaller subset of 59 EDRs that collected vehicle yaw rate was additionally analyzed to investigate evasive steering. Each vehicle was assigned to one of 3 precrash movement classifiers (traveling through the intersection, completely stopped, or rolling stop) based on the vehicle's calculated acceleration and observed velocity profile. To ensure that any significant steering input observed was an attempted evasive maneuver, the analysis excluded vehicles at intersections that were turning, driving on a curved road, or performing a lane change. Braking application at the last EDR-recorded time point was assumed to indicate evasive braking. A vehicle yaw rate greater than 4° per second was assumed to indicate an evasive steering maneuver.

Results: Drivers executed crash avoidance maneuvers in four-fifths of intersection crashes. A more detailed analysis of evasive braking frequency by precrash maneuver revealed that drivers performing complete or rolling stops (61.3%) braked less often than drivers traveling through the intersection without yielding (79.0%). After accounting for uncertainty in the timing of braking and steering data, the median evasive braking time was found to be between 0.5 to 1.5 s prior to impact, and the median initial evasive steering time was found to occur between 0.5 and 0.9 s prior to impact. The median average evasive braking deceleration for all cases was found to be 0.58 g. The median of the maximum evasive vehicle yaw rates was found to be 8.2° per second. Evasive steering direction was found to be most frequently in the direction of travel of the approaching vehicle.

Conclusions: The majority of drivers involved in intersection crashes were alert enough to perform an evasive action. Most drivers used a combination of steering and braking to avoid a crash. The average driver attempted to steer and brake at approximately the same time prior to the crash.     

An Application and Evaluation of the CAL3QHC Model for Predicting Carbon Monoxide Concentrations from Motor Vehicles Near a Roadway Intersection in Muscat,Oman

The CAL3QHC model was used to predict carbon monoxide (CO) concentrations from motor vehicles at an existing urban intersection (Star Cinema in Muscat area, Oman). The CO concentrations predicted from the model were compared with those measured in the field. Predicted average CO concentrations were found to compare favorably with measured values obtained at all eight receptors considered within the modeled intersection. In general, the comparison indicates good agreement with some underprediction for CO. For receptor 6, the model overpredicts the average CO concentration. This overprediction is associated with the presence of trees and green area in the location of receptor 6. In general, the measurements and the model results indicated that the highest CO concentrations were found to occur close to the intersection and, hence, a decrease in the concentration levels was seen as the distance from the road increased. The results indicated that the levels of CO were well below the ambient air quality standard and that probably no health risk was present in areas adjacent to the star cinema intersection. However, the predicted worst-case 1-h CO concentrations assuming inversion atmospheric stability conditions (class F) and wind speed of 1 m/s indicated that the levels of CO were close to or higher than the Omans National Ambient Air Quality Standards (NAAQS) value of 35 ppm at all receptors considered. The results of this study are useful in transport development and traffic management planning.Published online.