Development of Fatigue Failure Criterion for Hot - Mix Asphalt Based on Dissipated Energy and Stiffness Ratio

Fatigue in hot-mix asphalt is the accumulation of damage under the effect of repeated loading. Flexural beam fatigue testing in the laboratory has been used for several decades and is expected to be an integral part of the new superpave advanced characterization procedure. Current fatigue failure criteria are based on a simple relation between the tensile strain in the beam versus the number of load repetitions to failure. Failure in the beam has relied on an arbitrary criterion such as 50 percent reduction of stiffness. This method does not provide a consistent indication of the onset of failure when different modes of loading are used. The dissipated energy approach is a promising technique for fatigue characterization, since it provides a consistent indication of the level of deterioration in the specimen in terms of behavior, accumulated damage or remaining life. As a part of the superpave advanced characterization research, a new fatigue failure criterion for flexure fatigue test was developed in this study using the dissipated energy approach. This approach makes it possible to predict the fatigue behavior of hot-mix asphalt in the laboratory over a wide range of conditions from the results of a few simple fatigue tests. A fundamental energy-based fatigue failure criteria methodology was developed using the dissipated energy approach, which is independent of the type of load control, temperature and mix and binder type

Traffic Accidents Prediction Models to Improve Traffic Safety in Greater Amman Area

Highway related accidents are considered one of the most serious problems in the modern world. Traffic accidents cause serious threat to human life worldwide. According to the World Health Organization (WHO), more than 1.2 million people die each year in motor vehicle accidents and more than 50 millions are injured each year worldwide. Jordan, as one of the developing countries, has high level of traffic accidents. In Jordan, traffic accidents have caused more than 13000 fatalities between the years 1989-2012. The main objectives of this study are: to develop traffic accidents regression prediction models in Amman Greater Area. These models relate accident numbers, as a dependent variable, with possible causes of accidents that are related to driver behavior, as independent variables. Also, to propose effective countermeasures to reduce the frequency and severity of traffic accidents in Jordan. Accident data were collected from the General Security Directorate and from the Jordan Traffic Institute for the selected areas inside Greater Amman Area in Jordan. These data were analyzed and used in the regression models. Several regression prediction models were formed and the best models were chosen. The intersections and road segments, under this study, were arranged according to the traffic accidents severity. The most dangerous and hazardous streets and intersections were located in the study areas. Proper treatments and improvements are needed to reduce the number and severity of accidents in these areas. Preventive countermeasures were recommended to enhance traffic safety in Jordan specially Amman Area. Key Words: Traffic Accidents, Traffic Safety, Driver Behavior, Countermeasures, Regression Models, Jordan Traffic Institute.

Evaluation of Driver Behavior Mistakes and Their Effects on Improving Traffic Safety in Jordan

Causes of accidents are of special concern to researchers in traffic safety, since such research would be aimed not only at prevention of accidents but also at reduction of their frequency and severity. Motor vehicle accidents are a major cause of death among Jordanians. Roughly 700 people died in 2011 in car accidents according to the Jordan traffic institute out of a total population of about 6 million people.The main objectives of this study are: to identify driving behaviors and mistakes that drivers make; based on a questionnaire, which may cause traffic accidents in Jordan and highlight their effect on traffic safety. Also, to develop traffic accidents regression prediction models. Also, to propose effective countermeasures to reduce the frequency and severity of traffic accidents. The analysis is based on the questionnaire by using SPSS software to predict accident rates and compare the results with the model reports developed in Jordan and Amman area.The data for this study was collected from a survey questionnaire which was distributed to a sample of drivers in Amman Area and in some Jordan Universities.  The data from the survey questionnaire were analyzed and used in forming the regression models. It was found that the drivers' behavior is considered aggressive, according to the first part which represents the participant's opinion weather they listed the behavior as aggressive or not, and the other part which represent weather the participants conducted this behavior or not. Also, there was a strong direct relationship between the driver behaviors and their exposure to accidents. In conclusion, the aggressive behavior increases the chance of exposure to accidents.From this study, it was concluded that the main causes of traffic accidents, injuries, and fatalities that are related to driver behavior. Preventive countermeasures were recommended to enhance traffic safety in Jordan. Keywords: Traffic Accidents, Traffic Safety, Driver Behavior, Driver Mistakes, Aggressive driving, Countermeasures, Regression Models

Evaluation of Pedestrian Bridges and Pedestrian Safety in Jordan

Car accidents represent a major problem in Jordan. It is the second major cause of death. More than 30% of all car accidents in Jordan involve pedestrians, a percentage considered very high compared to other countries such as the UK and USA. The main objectives of this study are to collect data, analyze, and evaluate the pedestrian bridges and pedestrian safety in the greater Amman area. In addition, to develop regression prediction models that relate the percentage use of pedestrian bridges with possible factors that affecting the use of pedestrian bridges. A sample of pedestrian bridges and tunnels were chosen for this study. Detailed data were collected from the location of each pedestrian bridge. The collected data was analyzed and used in forming the regression models. Several regression prediction models were formed and the best models were chosen. Also, a questionnaire survey was prepared and distributed to a random sample of pedestrians at the selected locations. Also, personal one-to-one interviews were conducted to collect more data from a random sample of pedestrian on the selected sites in order to study the pedestrian behavior and attitude in the area of a pedestrian bridge. It was concluded that pedestrian bridges have a positive impact and have great potential of reducing number of pedestrian fatalities. The main factors that affecting the use of pedestrian bridges are: the posted speed limit, the overall width of the cross walkway, and the existence of median barrier. Key Words: Pedestrian Safety, Pedestrian Bridges, Traffic Accidents, Traffic Safety, Regression Models, Amman, Jordan

Development of Traffic Accident Prediction Models to Improve Traffic Safety and to Reduce Traffic Accident Severity and Rate in Jordan

In the past few years traffic accidents have become an epidemic. They cause the death of over one million people per year worldwide including those walking and riding bikes. Recent studies have shown that Jordan suffers massive human and economical losses as well as social and emotional effects from traffic accidents every year. Despite the efforts of the public and private sectors, traffic accidents are still increasing and exhaust Jordan’s resources at the price of other areas of development and construction.The main objectives of this study are: to analyze traffic accidents in Jordan and their main causes; to reduce the number of traffic accidents and their severity. Also, to study the effect of driver behavior mistakes on traffic accidents and their severity. In addition, to determine and build prediction statistical regression models, which relates the number of accidents (dependent variable), with drivers behavior mistakes (independent variable) by using the Statistical Package for Social Sciences (SPSS) computer software.The study was conducted based on accident data provided by the Jordan Traffic Institute from the year 2000 to year 2010. The study investigates 394188 total accidents during the period of the study with five independent variables (close following, lane violation, speeding or violation of speed limit, wrong passing and red light violation).Regression techniques were used to analyze the collected data and to create four models .The models were developed by SPSS statistical package computer program. The first developed predicted model was for the total accident, the result indicated that the close following and lane violation are the most causes of accidents .The second developed model was for the fatal accidents, and the results indicated that the violation of speed limit and the lane violation are the most causes of the fatalities. The third and fourth models were developed for the slight and sever injuries; the result showed that the same independent variables causes of fatalities are applicable for injuries.The accident prediction model can be used to develop warrants and standards for law enforcement, geometric design, and traffic operation and to improve the required countermeasures in order to reduce the traffic accidents especially fatal and injury accidents. Keywords: World Health Organization, Healthcare, Fatality, Injury, Severity, Human losses, Social and Emotional Effects, Traffic Accidents, Traffic Safety, Speed Limit, Speeding, Driver Behavior, Countermeasures, Regression Models.

Cracking Characteristic of Asphalt Rubber Mixtures

The Arizona Department of Transportation (ADOT) has used Asphalt Rubber (AR) modified binders since the early 1970’s. The primary purpose for using AR is to reduce reflective cracking in Hot Mix Asphalt (HMA) rehabilitation overlays. The AR mixtures have also performed well in cold climate conditions. This research study had the primary objective of conducting a laboratory experimental program to obtain typical cracking properties for asphalt rubber mixtures used in Arizona and comparing the performance of these AR mixtures to other conventional asphalt mixtures. Gap and open graded mixtures were subjected to fatigue and indirect tensile cracking tests. All test specimens in this study were prepared using hot mix AR mixtures that were collected during construction. Fatigue testing of AR specimens was conducted at different test temperatures using the beam fatigue apparatus proposed by the Strategic Highway Research Program (SHRP). The indirect tensile strength and creep tests were carried out at three temperatures according to the procedures described in the draft indirect tensile test protocol developed for the new 2002 Design Guide. The results from the fatigue tests indicated that the AR mixtures would have longer fatigue life compared with the ADOT conventional dense graded mixtures. For the indirect tensile strength tests, the analysis for strains measured at failure showed that the AR mixtures have higher values than the conventional mixes. AR mixtures exhibiting higher strains at failure would have higher resistance to thermal cracking. The fracture energy results indicated that the AR mixtures are not as greatly affected by the decrease in temperature as compared to the conventional mixes. This relative insensitivity for changes in temperature makes the AR mixtures better resisting to thermal cracking in the field

Development of Statistical Prediction Models to Reduce Fatal and Injury Traffic Accidents

Recent studies have shown that Jordan suffers massive human and economical losses as well as social and emotional effects from traffic accidents every year. Despite the efforts of the public and private sectors, traffic accidents are still increasing and exhaust Jordan’s resources at the price of other areas of development and construction. The main objectives of this study are: to analyze traffic accidents in Jordan and their main causes; to reduce the number of traffic accidents and their severity. Also, to study the effect of driver behavior mistakes on traffic accidents and their severity. In addition, to determine and build prediction statistical regression models, which relates the number of accidents (dependent variable), with drivers behavior mistakes (independent variable) by using the Statistical Package for Social Sciences (SPSS) computer software. The study was conducted based on accident data provided by the Jordan Traffic Institute from the year 2000 to year 2010. The study investigates 394188 total accidents during the period of the study with five independent variables (close following, lane violation, speeding or violation of speed limit, wrong passing and red light violation). Regression techniques were used to analyze the collected data and to create four models .The models were developed by SPSS statistical package computer program. The first developed predicted model was for the total accident, the result indicated that the close following and lane violation are the most causes of accidents .The second developed model was for the fatal accidents, and the results indicated that the violation of speed limit and the lane violation are the most causes of the fatalities. The third and fourth models were developed for the slight and sever injuries; the result showed that the same independent variables causes of fatalities are applicable for injuries. The accident prediction model can be used to develop warrants and standards for law enforcement, geometric design, and traffic operation and to improve the required countermeasures in order to reduce the traffic accidents especially fatal and injury accidents. Keywords: World Health Organization, Healthcare, Fatality, Injury, Severity, Human losses, Social and Emotional Effects, Traffic Accidents, Traffic Safety, Speed Limit, Speeding, Driver Behavior, Countermeasures, Regression Models

Evaluation and Improvement of Signalized Intersections in Amman City in Jordan

The main objective of this study is to evaluate and improve the traffic operations at the signalized intersections in Amman city in Jordan. Wadi-Saqra signalized intersection was chosen for this study. This intersection is located in the western central part of Amman the capital of Jordan. It has heavy traffic volume, with higher delay and heavy congestion traffic more than any other similar intersections in Amman. In this study, the intersection is analyzed as an isolated signalized intersection by using HCM (Highway Capacity Manual) and HCS (Highway Capacity System) computer program. Synchro computer program is also used for improvement through optimization process. The geometric, traffic and signalized data were collected during the morning and afternoon peak time periods. The results indicated that the current delay is 473 sec/veh with Level of Service F (LOS-F). Four alternatives are recommended to solve the current and future problems. The recommended alternatives are: Prohibit left turning at all approaches.Optimization of the existing traffic signals.Construct one through overpass for one direction.Construct two overpasses or one overpass and tunnel for two directions. The first three alternatives will not be able to reduce the level of service significantly.  On the other hand, the fourth alternative will reduce the level of service from LOS F with (473 sec/veh) delay to level of service LOS C with (27 sec/veh) delay and will change the cycle length from 190 seconds to 90 seconds. The estimated initial cost of constructing two overpasses is about thirty million Jordan Dinars JD with annual saving of more than eight million JD. If alternative four was selected to solve the existing situation the following advantages can be attained: reducing the congestion on the signalized intersection especially during peak hours, reducing the cost of traveling for the public, increasing the efficiency of the road network, increasing safety, reducing the maintenance cost of the roads, improving traffic flow and traffic operations, and reducing air pollution and preserving the environment. Key Words:  Environment, Air Pollution, Traffic Safety, Traffic Flow, Capacity, Level of Service, Signalized Intersections, Intersection Delay, Traffic Control, Intersection Design

Framework for Level-I Alligator Cracking Methodology for Use in the Mechanistic-Empirical (M-E) Pavement Design Guide.

The recently published Mechanistic-Empirical Pavement Design Guide (MEPDG) includes a global flexure fatigue model that can be used for Level 3 material input. This paper develops a typical framework for highway agencies to follow to calibrate their laboratory results and determine Level 1 flexure fatigue input for use in the design guide. An extensive flexure fatigue testing program was carried out on six hot-mix asphalt (HMA) materials typically used by the Arizona Department of Transportation. General fatigue models are developed using both constant strain and constant stress modes of loading. The general fatigue lab models were then calibrated to the global fatigue model in the MEPDG to be used as an input to Level 1 design. Shift factors were developed for each mix used and for different thicknesses of asphalt layers. The shift factor decreased from 20 at a 1-in. layer to 9 at a 4-in. layer, after which it remained constant. The procedure used in this paper serves as a guide for other agencies to follow to obtain Level 1 fatigue data input for the M-E Pavement Design Guide

The Effect of Driver Behavior Mistakes on Traffic Safety

The main objectives of this study are: to identify driving behaviors and mistakes that drivers make; based on a questionnaire, which may cause traffic accidents in Jordan and highlight their effect on traffic safety. Also, to develop traffic accidents regression prediction models. Also, to propose effective countermeasures to reduce the frequency and severity of traffic accidents. The analysis is based on the questionnaire by using SPSS software to predict accident rates and compare the results with the model reports developed in Jordan and Amman area. The data for this study was collected from a survey questionnaire which was distributed to a sample of drivers in Amman Area and in some Jordan Universities.  The data from the survey questionnaire were analyzed and used in forming the regression models. It was found that the drivers' behavior is considered aggressive, according to the first part which represents the participant's opinion weather they listed the behavior as aggressive or not, and the other part which represent weather the participants conducted this behavior or not. Also, there was a strong direct relationship between the driver behaviors and their exposure to accidents. In conclusion, the aggressive behavior increases the chance of exposure to accidents. From this study, it was concluded the main causes of traffic accidents, injuries, and fatalities that are related to driver behavior. Preventive countermeasures were recommended to enhance traffic safety in Jordan. Key Words: Traffic Accidents, Traffic Safety, Driver Behavior, Driver Mistakes, Aggressive driving, Countermeasures, Regression Models