Biomedical subjects

Mohamed Abdel-Aty

Publications and source records attributed to Mohamed Abdel-Aty.

10 recordsLinked to original sources

PubMed2006

Temporal and spatial analyses of rear-end crashes at signalized intersections.

In this study, the generalized estimating equations with the negative binomial link function were used to model rear-end crash frequencies at signalized intersections to account for the temporal or spatial correlation among the data. The longitudinal data for 208 signalized intersections over 3 years and the spatially correlated data for 476 signalized intersections which are located along different corridors were collected in the state of Florida. The modeling results showed that there are high correlations between the longitudinal or spatially correlated rear-end crashes. Some intersection related variables are identified as significantly influencing rear-end crash occurrences at signalized intersections. Intersections with heavy traffic on the major and minor roadways, having more right and left-turn lanes on the major roadway, having a large number of phases per cycle (indicated by the left-turn protection on the minor roadway), with high speed limits on the major roadway, and in high population areas are correlated with high rear-end crash frequencies. On the other hand, intersections with three legs, having channelized or exclusive right-turn lanes on the minor roadway, with protected left-turning on the major roadway, with medians on the minor roadway, and having longer signal spacing have a lower frequency of rear-end crashes.

Accidents, Traffic↗

PubMed2006

Assessment of freeway traffic parameters leading to lane-change related collisions.

This study aims at 'predicting' the occurrence of lane-change related freeway crashes using the traffic surveillance data collected from a pair of dual loop detectors. The approach adopted here involves developing classification models using the historical crash data and corresponding information on real-time traffic parameters obtained from loop detectors. The historical crash and loop detector data to calibrate the neural network models (corresponding to crash and non-crash cases to set up a binary classification problem) were collected from the Interstate-4 corridor in Orlando (FL) metropolitan area. Through a careful examination of crash data, it was concluded that all sideswipe collisions and the angle crashes that occur on the inner lanes (left most and center lanes) of the freeway may be attributed to lane-changing maneuvers. These crashes are referred to as lane-change related crashes in this study. The factors explored as independent variables include the parameters formulated to capture the overall measure of lane-changing and between-lane variations of speed, volume and occupancy at the station located upstream of crash locations. Classification tree based variable selection procedure showed that average speeds upstream and downstream of crash location, difference in occupancy on adjacent lanes and standard deviation of volume and speed downstream of the crash location were found to be significantly associated with the binary variable (crash versus non-crash). The classification models based on data mining approach achieved satisfactory classification accuracy over the validation dataset. The results indicate that these models may be applied for identifying real-time traffic conditions prone to lane-change related crashes.

Accidents, Traffic↗

PubMed2005

Evaluation of variable speed limits for real-time freeway safety improvement.

Use of various variable speed limit (VSL) strategies as a tool for safety improvement on freeways was evaluated using simulation of a section of Interstate 4 in Orlando, FL. Real-time crash likelihood was calculated based on models developed in previous research by the first author [Abdel-Aty, M., Uddin, N., Pande, A., January 2005. Split models for predicting multi-vehicle crashes during high-speed and low-speed operating conditions on freeways. In: Presented at the 84th Annual Meeting of the Transportation Research Board, Washington, DC]. VSL implementation produced safety improvement by simultaneously implementing lower speed limits upstream and higher speed limits downstream of the location where crash likelihood is observed in real-time. This improvement was realized in the case of medium-to-high-speed regimes on the freeway, but no benefit was achieved in low-speed situations (no substantial safety benefit from implementing VSL in congested situation's simulation). The final recommendations for implementing VSL are: gradually introducing speed limit changes over time (5 mph every 10 min); abruptly changing speed limit in space ( no gap distance); reducing speed limits upstream and increasing speed limits downstream of location of interest; the speed limit changes up- and downstream should be large in magnitude (15 mph) and implemented within short distances (2 miles) of the location of interest. In addition to the safety benefit, this final strategy also produced travel time savings.

Accidents, Traffic↗

PubMed2005

Characteristics of rear-end accidents at signalized intersections using multiple logistic regression model.

Multi-vehicle rear-end accidents constitute a substantial portion of the accidents occurring at signalized intersections. To examine the accident characteristics, this study utilized the 2001 Florida traffic accident data to investigate the accident propensity for different vehicle roles (striking or struck) that are involved in the accidents and identify the significant risk factors related to the traffic environment, the driver characteristics, and the vehicle types. The Quasi-induced exposure concept and the multiple logistic regression technique are used to perform this analysis. The results showed that seven road environment factors (number of lanes, divided/undivided highway, accident time, road surface condition, highway character, urban/rural, and speed limit), five factors related to striking role (vehicle type, driver age, alcohol/drug use, driver residence, and gender), and four factors related to struck role (vehicle type, driver age, driver residence, and gender) are significantly associated with the risk of rear-end accidents. Furthermore, the logistic regression technique confirmed several significant interaction effects between those risk factors.

Accidents, Traffic↗

PubMed2005

Identifying crash propensity using specific traffic speed conditions.

INTRODUCTION: In spite of recent advances in traffic surveillance technology and ever-growing concern over traffic safety, there have been very few research efforts establishing links between real-time traffic flow parameters and crash occurrence. This study aims at identifying patterns in the freeway loop detector data that potentially precede traffic crashes. METHOD: The proposed solution essentially involves classification of traffic speed patterns emerging from the loop detector data. Historical crash and loop detector data from the Interstate-4 corridor in the Orlando metropolitan area were used for this study. Traffic speed data from sensors embedded in the pavement (i.e., loop detector stations) to measure characteristics of the traffic flow were collected for both crash and non-crash conditions. Bayesian classifier based methodology, probabilistic neural network (PNN), was then used to classify these data as belonging to either crashes or non-crashes. PNN is a neural network implementation of well-known Bayesian-Parzen classifier. With its superb mathematical credentials, the PNN trains much faster than multilayer feed forward networks. The inputs to final classification model, selected from various candidate models, were logarithms of the coefficient of variation in speed obtained from three stations, namely, station of the crash (i.e., station nearest to the crash location) and two stations immediately preceding it in the upstream direction (measured in 5 minute time slices of 10-15 minutes prior to the crash time). RESULTS: The results showed that at least 70% of the crashes on the evaluation dataset could be identified using the classifiers developed in this paper.

Accidents, Traffic↗

PubMed2005

Exploring the overall and specific crash severity levels at signalized intersections.

Many studies have shown that intersections are among the most dangerous locations of a roadway network. Therefore, there is a need to understand the factors that contribute to injuries at such locations. This paper addresses the different factors that affect crash injury severity at signalized intersections. It also looks into the quality and completeness of the crash data and the effect that incomplete data has on the final results. Data from multiple sources have been cross-checked to ensure the completeness of all crashes including minor crashes that are usually unreported or not coded into crash databases. The ordered probit modeling technique has been adopted in this study to account for the fact that injury levels are naturally ordered variables. The tree-based regression methodology has also been adopted in this study to explore the factors that affect each severity level. The probit model results showed that a combination of crash-specific information and intersection characteristics result in the highest prediction rate of injury level. More specifically, having a divided minor roadway or a higher speed limit on the minor roadway decreased the level of injury while crashes involving a pedestrian/bicyclist and left turn crashes had the highest probability of a more severe crash. Several regression tree models showed a difference in the significant factors that affect the different severity types. Completing the data with minor non injury crashes improved the modeling results and depicted differences when modeling the no injury crashes.

Accidents, Traffic↗

PubMed2005

Comprehensive analysis of vehicle-pedestrian crashes at intersections in Florida.

This study analyzes vehicle-pedestrian crashes at intersections in Florida over 4 years, 1999-2002. The study identifies the group of drivers and pedestrians, and traffic and environmental characteristics that are correlated with high pedestrian crashes using log-linear models. The study also estimates the likelihood of pedestrian injury severity when pedestrians are involved in crashes using an ordered probit model. To better reflect pedestrian crash risk, a logical measure of exposure is developed using the information on individual walking trips in the household travel survey. Lastly, the impact of average traffic volume on pedestrian crashes is examined. As a result of the analysis, it was found that pedestrian and driver demographic factors, and road geometric, traffic and environment conditions are closely related to the frequency and injury severity of pedestrian crashes. Higher average traffic volume at intersections increases the number of pedestrian crashes; however, the rate of increase is steeper at lower values of average traffic volume. Based on the findings in the analysis, some countermeasures are recommended to improve pedestrian safety.

Accidents, Traffic↗

PubMed2004

Modeling rear-end collisions including the role of driver's visibility and light truck vehicles using a nested logit structure.

This paper presents an analysis of the effect of the geometric incompatibility of light truck vehicles (LTV)--light-duty trucks, vans, and sport utility vehicles--on drivers' visibility of other passenger cars involved in rear-end collisions. The geometric incompatibility arises from the fact that most LTVs ride higher and are wider than regular passenger cars. The objective of this paper is to explore the effect of the lead vehicle's size on the rear-end crash configuration. Four rear-end crash configurations are defined based on the type of the two involved vehicles (lead and following vehicles). Nested logit models were calibrated to estimate the probabilities of the four rear-end crash configurations as a function of driver's age, gender, vehicle type, vehicle maneuver, light conditions, driver's visibility and speed. Results showed that driver's visibility and inattention in the following (striker) vehicle have the largest effect on being involved in a rear-end collision of configuration CarTrk (a regular passenger car striking an LTV). Possibly, indicating a sight distance problem. A driver of a smaller car following an LTV, have a problem seeing the roadway beyond the LTV, and therefore would not be able to adjust his/her speed accordingly, increasing the probability of a rear-end collision. Also, the probability of a CarTrk rear-end crash increases in the case that the lead vehicle stops suddenly.

Accidents, Traffic↗

PubMed2004

Analysis and prediction of traffic fatalities resulting from angle collisions including the effect of vehicles' configuration and compatibility.

Although the rapid growth in light truck vehicle (LTV) sales, including minivans, sports utility vehicles (SUVs), and light-duty trucks, has not been associated with an overall increase in collisions or traffic deaths in the US, there is a need for a research program to determine whether particular types of collisions have become more frequent or injurious because of the increase in the percent of LTVs in traffic. This paper presents an analysis of the effect of the increasing number of LTV registrations on fatal angle collision trends in the US. The analysis investigates the number of annual fatalities that result from angle collisions as well as collision configuration (car-car, car-LTV, LTV-car, and LTV-LTV). The analysis uses the Fatality Analysis Reporting System (FARS) crash databases covering the period 1975-2000. Results showed that death rates differ based on the collision configuration. Time series modeling results showed that fatalities in angle collisions will increase in the next 10 years, and that they are affected by the expected increase in the percentage of LTVs in traffic. Forecast showed that the total number of annual deaths is expected to reach 6300 deaths by the year 2010 (an increase of 12% over 2000). Analysis into the configuration of the collision indicated the seriousness of angle collisions involving an LTV striking a common passenger car (LTV-car). A time series model illustrated the significance of time lag and percent of LTVs in traffic on the increase of this type of fatal collisions. Forecasts from the time series model indicated a 32% increase in deaths due to this type of collisions in the next 10 years.

Accidents, Traffic↗

PubMed2003

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.

Accidents, Traffic↗