Essam Radwan

Preliminary Validation of Driving Simulator Based on Forward Speed

This research was a preliminary step in the process of determining whether the driving simulator at the University of Central Florida (UCF) provides a realistic driving experience. Thirty volunteers from the driving population were asked to drive an instrumented car along a section of road on the UCF campus. A distance measurement instrument provided a log of instantaneous speed, cumulative distance, and elapsed time at designated points along the route for subsequent analysis. The second phase of the research entailed driving in the UCF driving simulator, which consists of a complete vehicle cab with a wraparound screen for displaying computer-generated images of a synthetic road and surroundings. Computer-generated imagery of the identical campus road and environment was viewable to the subjects in the simulator. Drivers were asked to perform the same task in the simulator as they did in the real driving environment. Identical information was acquired during field testing and the simulation runs. Speed data from the field and simulator were analyzed using conventional statistical tests to determine whether drivers responded differently in the simulator compared with their response during the real driving experience. Preliminary results of the statistical analysis indicated that the drivers behaved similarly at 10 of 16 designated locations along the road. Confidence intervals for the difference between the simulator and the field mean speeds indicated a tendency of drivers to travel at slower speeds in the simulator. These results, along with qualitative feedback from the subjects concerning the handling characteristics of the simulator, are being studied to determine the necessary simulator refinements and upgrades required before additional validation testing.

Heuristic Priority Ranking of Emergency Evacuation Staging to Reduce Clearance Time

Hazardous events, both natural and human-made, present tremendous risks to communities throughout the world. These events typically necessitate the evacuation of local or regional populations to safe destinations or shelters and have warning times ranging from minutes to hours or even days. The size and scope of these events present a challenge to the emergency management or agency personnel who must see to the health and safety of those living or working in their jurisdiction. This study evaluated various heuristic strategies to improve evacuation of an at-risk region by using a representative traffic roadway network. Finding evacuation strategies that reduce clearance time would lead to saving lives, time, and money. For the given test network, population density, or total number of trips, has an effect on overall clearance times; as densities (trips) increase, a greater potential for improved clearance time is indicated. Six different shift strategies were evaluated, each strategy based on origin-to-de...

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.

Assessment of I-4 Contraflow Plans: Microscopic Versus Mesoscopic Simulation

Better use of the available road network is critical to improving the evacuation operation during a disaster. Contraflow operations help increase the capacity of the available network by reversing the direction of inbound lanes to outbound lanes. This helps improve the outflow from a region threatened by disaster. One of the major issues associated with contraflow operations is determining the locations for access to the contraflow lanes from the normal-flow lanes. These accesses are also referred to as crossovers. Four different strategies with different crossover locations were tested on the I-4 evacuation route from Tampa to Orlando, Florida. It was found that the provision of two crossovers, one after Tampa and another after Plant City, performed the best but was only marginally better than the provision of one crossover after Tampa. Therefore, considering the cost and personnel needed to provide a crossover, the provision of one crossover after Tampa was found to be a more logical choice than the provision of two crossovers. It was observed that the time required to run the microscopic simulation to arrive at the results was extremely long. To overcome this drawback, the cell transmission model (CTM) was calibrated and run for the same four strategies. It was observed that the results were extremely close to the results from the microscopic simulation. The robustness and speed of CTM make it ideal for use as part of a decision support system to help determine the best strategies in real time. This will help emergency management officials make real-time decisions in the event of unforeseen drops in capacities because of incidents or vehicle breakdowns.

Understanding the Impact of a Recent Hurricane on Mobilization Time During a Subsequent Hurricane

It is not uncommon for a region to be affected by multiple hurricanes in a span of a few weeks. The behavior of the evacuees during a subsequent hurricane in the same season is affected by the damage to the infrastructure and to the vehicles and assets belonging to evacuees, as well as by the psychological impact of the preceding hurricane. One such behavioral aspect that affects traffic-loading rates during a hurricane is the evacuation delay or mobilization time. In this study, “mobilization time for an evacuee” is defined as the difference between the time at which the decision to leave is made and the actual time of departure. This paper proposes a methodology that can be used to understand the factors associated with the mobilization time during a subsequent hurricane while accounting for the effects of the preceding hurricane. The effects of the preceding hurricane were accounted for by modeling mobilization times simultaneously with an ordinal variable representing evacuation participation levels during Hurricane Charley. The data from a survey conducted with the evacuees of Hurricane Frances, which made landfall 3 weeks after Hurricane Charley, were used in this study. The errors for the two simultaneously estimated models were significantly correlated. The results showed that home ownership, the number of individuals in the household, income levels, and the level or the risk of a surge were significant in the model and explained the mobilization times for households. Pet ownership and the number of children in households, known to increase mobilization times during isolated hurricanes, were not found to be significant in the model. The implications of these findings for the demand S-curve are briefly discussed.

New Model for Evaluation of Traffic Operations at Electronic Toll Collection Plazas

Traffic simulation models are used to enhance planning, design, operation, and management of transportation facilities. A discrete-event stochastic object-oriented microscopic simulation model is presented that was specifically developed to evaluate the operational performance of toll plazas. Traffic behavior is represented using a set of mathematical and logic algorithms that control the conflicts among vehicles within the toll plaza area. Modified versions of car-following and lane-changing algorithms and a new toll-lane selection algorithm are integrated into this new model to simulate traffic operation at toll plazas. The model output includes measures of effectiveness (MOEs) that can be used to evaluate the performance of existing and future individual toll lanes and the entire toll plaza system. Real-world data collected at the busiest toll plaza in the Orlando–Orange County Expressway Authority system were used to validate the developed model. Statistical tests indicate that there is no significant difference at the 95 percent confidence level between MOEs obtained from the model and those collected in the real world. Sensitivity analysis of market penetration of the electronic toll collection (ETC) system indicates that an increase in ETC subscription rate improves the efficiency of toll plaza operation. The benefits of ETC depend on the specific plaza configuration. One of the most interesting results of this study is that for all plaza configurations simulated with manual payment lanes operating over capacity, total plaza delay can be reduced by half if only 10 percent of the users switch from manual payment lanes to ETC lanes.

Using a traffic simulation model (VISSIM) with an emissions model (MOVES) to predict emissions from vehicles on a limited-access highway

The Intergovernmental Panel on Climate Change (IPCC) estimates that baseline global GHG emissions may increase 25–90% from 2000 to 2030, with carbon dioxide (CO2) emissions growing 40–110% over the same period. On-road vehicles are a major source of CO2 emissions in all the developed countries, and in many of the developing countries in the world. Similarly, several criteria air pollutants are associated with transportation, for example, carbon monoxide (CO), nitrogen oxides (NOx), and particulate matter (PM). Therefore, the need to accurately quantify transportation-related emissions from vehicles is essential. The new U.S. Environmental Protection Agency (EPA) mobile source emissions model, MOVES2010a (MOVES), can estimate vehicle emissions on a second-by-second basis, creating the opportunity to combine a microscopic traffic simulation model (such as VISSIM) with MOVES to obtain accurate results. This paper presents an examination of four different approaches to capture the environmental impacts of vehicular operations on a 10-mile stretch of Interstate 4 (I-4), an urban limited-access highway in Orlando, FL. First (at the most basic level), emissions were estimated for the entire 10-mile section “by hand” using one average traffic volume and average speed. Then three advanced levels of detail were studied using VISSIM/MOVES to analyze smaller links: average speeds and volumes (AVG), second-by-second link drive schedules (LDS), and second-by-second operating mode distributions (OPMODE). This paper analyzes how the various approaches affect predicted emissions of CO, NOx, PM2.5, PM10, and CO2. The results demonstrate that obtaining precise and comprehensive operating mode distributions on a second-by-second basis provides more accurate emission estimates. Specifically, emission rates are highly sensitive to stop-and-go traffic and the associated driving cycles of acceleration, deceleration, and idling. Using the AVG or LDS approach may overestimate or underestimate emissions, respectively, compared to an operating mode distribution approach. Implications: Transportation agencies and researchers in the past have estimated emissions using one average speed and volume on a long stretch of roadway. With MOVES, there is an opportunity for higher precision and accuracy. Integrating a microscopic traffic simulation model (such as VISSIM) with MOVES allows one to obtain precise and accurate emissions estimates. The proposed emission rate estimation process also can be extended to gridded emissions for ozone modeling, or to localized air quality dispersion modeling, where temporal and spatial resolution of emissions is essential to predict the concentration of pollutants near roadways.

Emergency Evacuation Planning and Preparedness of Transit Facilities: Traffic Simulation Modeling

The growing need for evacuation planning is addressed by using a computer-based model of traffic simulation. The VISSIM traffic simulation tool was used to evaluate a current plan and alternative plans for the deployment of transit during an emergency situation in a transit facility such as a bus depot. Different strategies were simulated to study the effect of evacuation on the surrounding traffic network as well as to help the local transit company (LYNX) evaluate its evacuation plan and consider different possibilities without the risk and cost of actual evacuation drills. Nine evacuation scenarios were simulated and analyzed to reach the best evacuation strategy for the LYNX companys main bus depot. Evacuation strategies evaluated include traffic diversion, bus signal optimization, access restriction, different destinations, and evacuation of pedestrians. Total network delay for each scenario was compared with the base case, and results indicate that pedestrian evacuation was better than using buses. Traffic rerouting also could potentially reduce delays and evacuation clearance time.

Analysis of Red Light Running Crashes Based on Quasi-Induced Exposure and Multiple Logistic Regression Method

According to recent national statistics, red light running crashes represent a significant safety problem at signalized intersections. To examine the overall characteristics of red light running crashes, this study used the 1999 to 2001 Florida crash database to investigate the crash propensity related to traffic environments, driver characteristics, and vehicle types. The quasi-induced exposure concept and multiple logistic regression technique were used to perform this analysis. The results showed that traffic factors including number of lanes, crash time, weather, highway character, day of week, urban or rural location, speed limit, driver age, alcohol or drug use, physical defect, driver residence, and vehicle type were significantly associated with the risk of red light running crashes. Furthermore, it confirmed that there were significant interaction effects between the risk factors, including crash time and highway character, number of lanes and urban or rural location, weather condition and driver age, driver age and gender, alcohol or drug use and gender, and type of vehicle and gender.

A rear-end collision risk assessment model based on drivers' collision avoidance process under influences of cell phone use and gender: a driving simulator based study

Drivers collision avoidance performance has a direct link to the collision risk and crash severity. Previous studies demonstrated that the distracted driving, such as using a cell phone while driving, disrupted the drivers performance on road. This study aimed to investigate the manner and extent to which cell phone use and drivers gender affected driving performance and collision risk in a rear-end collision avoidance process. Forty-two licensed drivers completed the driving simulation experiment in three phone use conditions: no phone use, hands-free, and hand-held, in which the drivers drove in a car-following situation with potential rear-end collision risks caused by the leading vehicles sudden deceleration. Based on the experiment data, a rear-end collision risk assessment model was developed to assess the influence of cell phone use and drivers gender. The cell phone use and drivers gender were found to be significant factors that affected the braking performances in the rear-end collision avoidance process, including the brake reaction time, the deceleration adjusting time and the maximum deceleration rate. The minimum headway distance between the leading vehicle and the simulator during the rear-end collision avoidance process was the final output variable, which could be used to measure the rear-end collision risk and judge whether a collision occurred. The results showed that although cell phone use drivers took some compensatory behaviors in the collision avoidance process to reduce the mental workload, the collision risk in cell phone use conditions was still higher than that without the phone use. More importantly, the results proved that the hands-free condition did not eliminate the safety problem associated with distracted driving because it impaired the driving performance in the same way as much as the use of hand-held phones. In addition, the gender effect indicated that although female drivers had longer reaction time than male drivers in critical situation, they were more quickly in braking with larger maximum deceleration rate, and they tended to keep a larger safety margin with the leading vehicle compared to male drivers. The findings shed some light on the further development of advanced collision avoidance technologies and the targeted intervention strategies about cell phone use while driving.