Jennifer Ogle

Simulator sickness during driving simulation studies.

While driving simulators are a valuable tool for assessing multiple dimensions of driving performance under relatively safe conditions, researchers and practitioners must be prepared for participants that suffer from simulator sickness. This paper describes multiple theories of motion sickness and presents a method for assessing and reacting to simulator sickness symptoms. Results showed that this method identified individuals who were unable to complete a driving simulator study due to simulator sickness with greater than 90% accuracy and that older participants had a greater likelihood of simulator sickness than younger participants. Possible explanations for increased symptoms experienced by older participants are discussed as well as implications for research ethics and simulator sickness prevention.

Smoothing Methods to Minimize Impact of Global Positioning System Random Error on Travel Distance, Speed, and Acceleration Profile Estimates

The Georgia Institute of Technology is evaluating the feasibility and effectiveness of mileage-based pricing programs as transportation control measures. Incentives were provided to study participants who change driving behavior in response to cent per mile pricing (fixed pricing and pricing as a function of congestion level). In-vehicle Global Positioning System (GPS) devices were used to estimate distance traveled and driver behavior (e.g., speed and acceleration profiles). The accuracy of estimated mileage accrual speeds by road classification, and acceleration rates used in pricing algorithms, is paramount. Various data-smoothing techniques were applied to the instrumented vehicle GPS speed data, and performance of the algorithms was evaluated in minimizing the impact of GPS random error on speed, acceleration, and distance estimates. The conventional discrete Kalman filter algorithm was modified to enhance its ability to control GPS random errors. Each smoothing method produces different second-by-se...

Effect of Wireless Communication and Entertainment Devices on Simulated Driving Performance

An analysis of the effect of wireless telephone communication using text and voice modalities as well as an Apple iPod on lane keeping, speed, speed variability, lateral speed, and lane position variability was conducted with a driving simulator. Participants (young adult licensed drivers) drove in an unusually curvy simulated driving environment while using wireless devices, controlling an iPod, and participating in conversations and word games. As expected on the basis of previous research, lane-keeping performance was robust for voice communication tasks; however, the text messaging and iPod tasks that required significant manual manipulation of the device resulted in significant decrements in lane-keeping performance. In addition, all wireless communication tasks and the iPod task resulted in significant increases in speed variability throughout the driving scenario. Lateral speed increases occurred for all wireless communication tasks other than the cellular phone conversation as well as the iPod task. Increases in lane position variability were observed for the text messaging conditions. In addition to establishing the dramatic performance decrement caused by text messaging tasks, this experiment suggests that driving performance may be affected by distraction in ways not captured by lane-keeping measures alone and explores potential alternative measures of driving performance that may be useful for identifying and quantifying the effects of distracted driving.

ACCURACY OF GLOBAL POSITIONING SYSTEM FOR DETERMINING DRIVER PERFORMANCE PARAMETERS

Global Positioning System (GPS) technology can continuously monitor the time and location of vehicle usage. By recording and analyzing detailed vehicle activity data, researchers can analyze the safety and environmental implications of driver behavior and trip-making patterns. In 2000, NHTSA awarded the Georgia Institute of Technology a contract to equip 1,100 vehicles with a GPS-enhanced device to collect speed and location data. The objective was to acquire more accurate information on the role of excessive speed on crash frequency and severity. GPS technology allows the researcher to continuously measure driver speed, acceleration, and location. When merged with roadway characteristics within a geographic information system (GIS) environment, determinations of driver risk-taking behavior can be made. Second, continuous logging of GPS data allows researchers to capture high-resolution vehicle activity immediately before a crash event, reducing the potential error and bias introduced during determination of precrash speed estimates. Until May 1, 2000, the military degraded the position accuracy of GPS signals for commercial use, known as selective availability. For researchers, life without selective availability is a great improvement. Travel routes can clearly be discerned without the addition of differential correction units. The accuracy of speed, acceleration, and position data obtained from GPS signals for use in determining driver performance parameters without selective availability were tested. The test included four GPS packages, both corrected and uncorrected, simultaneously validated against a distance-measuring instrument. Equipment configuration, data collection methods, and sources of error are reported. The results suggested that non-corrected data can be used to obtain data within a reasonable range of the application requirements. Even without selective availability, GPS accuracy is still problematic in urban canyons and under heavy tree canopies. Although filtering for urban canyon outliers is labor intensive in a continuous monitoring situation, improvements in GIS hold promise for automation of this task.

Normal Deceleration Behavior of Passenger Vehicles at Stop Sign–Controlled Intersections Evaluated with In-Vehicle Global Positioning System Data

Deceleration characteristics of passenger cars are often used in traffic simulation, vehicle fuel consumption and emissions models, and intersection and deceleration-lane design. Most previous studies collected spot speed data with detectors or radar guns. Because of the limitations of the data collection methods, these studies could not determine when and where drivers began to decelerate. Therefore, the studies may not provide an accurate estimation of deceleration time and distance. Furthermore, most previous studies are based on outdated and limited data, and their conclusions may not be applicable to the current vehicle fleet and drivers. The normal deceleration behavior of current passenger vehicles is evaluated at stop sign-controlled intersections on urban streets on the basis of in-vehicle Global Positioning System data. This study determined that drivers with higher approach speeds decelerated over a longer time and distance. Higher initial deceleration rates were also associated with higher app...

Development and Evaluation of Speed-Activated Sign to Reduce Speeds in Work Zones

Excessive speed is one of the most significant factors contributing to work zone crashes, which, along with work zone fatalities, have increased substantially in the past decade. From the beginning of 2000 to the end of 2003, the number of work zone crashes in South Carolina nearly tripled. In 2005, the South Carolina Department of Transportation initiated a research project to evaluate speed reduction measures in work zones. Through an in-depth literature review of speed control techniques for work zones, it was found that innovative technologies are often too expensive and thus impractical for large-scale implementation. There is a need for less-expensive technologies that are effective in reducing speeds in work zones. Development and evaluation of a speed-activated sign are discussed. Data were collected in work zones on two-lane primary and secondary highways in South Carolina, and the effectiveness of the speed-activated sign was evaluated on the basis of changes in mean speeds, 85th-percentile speeds, and percentages of vehicles exceeding the speed limit. Mean speed reductions ranged from 2 to 6 mph (3.2 to 9.7 km/h) with an average reduction of 3.3 mph (5.3 km/h). This average reduction improved to 4.1 mph (6.6 km/h) at sites where more than 50% of the vehicles were speeding before a sign was introduced. Further research was conducted with two speed-activated signs on a multilane divided highway and an Interstate freeway where similar speed reductions were experienced. From this study, researchers recommend that the speed-activated sign be used in short-term work zones.

Day-to-Day Travel Variability in the Commute Atlanta, Georgia, Study

Traditional travel diary surveys collect 1 or 2 days of travel data from participant households. Although useful in determining the overall average travel behavior of a regional population, cross-sectional travel diary surveys provide little insight into intrahousehold and intraperson trip variability. Longitudinal surveys are generally preferred for examining travel variability. The objective of the research is to examine the intrahousehold travel variability in the Commute Atlanta, Georgia, study, a Global Positioning System–based instrumented-vehicle monitoring study that collected vehicle trips from approximately 500 vehicles in 260 representative households. The research effort uses 2004 travel data collected for the Commute Atlanta study, in which the average variability or deviation in the number of trips by a household was 3 trips/day. Demographic variables (e.g., household size, household income, vehicle ownership, number of children, number of workers, and number of students) significantly affect the day-to-day variability in the total number of household trips per day. The variability due to seasonal effects is controlled by separately analyzing travel data during specific months in spring, summer, and fall. Results indicate that demographic variables have a significant effect on the day-to-day variability of the household number of trips when the variability associated with seasonal effects is excluded. Vehicles identified by participants as being used always or occasionally for business or commercial purposes have travel patterns different from those of other vehicles, and their presence in the sample will significantly bias analytical results in the analysis of longitudinal data. Commercial use vehicles are excluded from travel variability analysis, and the argument is made that households with such vehicles must be treated as an independent sample in future travel diary data collection and longitudinal studies.

Decision Support System for Predicting Traffic Diversion Impact Across Transportation Networks Using Support Vector Regression

This paper describes follow-up research to a previous study by the authors that used case-based reasoning (CBR) and support vector regression (SVR) to evaluate the likely impacts of implementing diversion strategies in response to incidents on highway networks. In the previous study, the training and testing of the CBR and SVR tools were performed on a single transportation network from South Carolina, which limited the applicability of the developed tool to the specific network for which it was developed. To address this limitation, the current study investigates the feasibility of developing a generic decision support system (DSS) capable of predicting traffic diversion impacts for new transportation networks that the tool has not previously seen. In such cases, users need only to input the geometric and traffic variables, via a graphical user interface, and the tool, which uses a SVR model, will predict the benefits of diverting traffic for a specific incident on the new site. To illustrate the feasibility of developing such a tool, two different highway networks covering portions of I-85 and I-385 in South Carolina were used to train the SVR model, which was then tested on a third network covering portions of I-89 in Vermont. The study found only a 15% difference between the predictions of the SVR model and those of a detailed simulation counterpart, demonstrating the feasibility of developing a generic DSS. Adding more sites and parameters to train the software is also expected to improve the prediction accuracy of the DSS.

Estimating Interstate Highway Capacity for Short-Term Work Zone Lane Closures: Development of Methodology

Defining and understanding traffic flow parameters within short-term Interstate work zones are crucial in developing effective policies to manage construction and maintenance work conducted on the nations heavily traveled freeways. The South Carolina Department of Transportation (DOT) initiated a research study to develop a methodology for use in determining an updated lane closure policy for Interstate highway work zones. Phase 1 of the research was completed in May 2003, and findings identified threshold volumes for two-to-one lane closure work zone configurations. Phase 2 of the research further expanded numerically derived relationships and contained analysis of other short-term lane closure configurations including three-to-two and three-to-one lane closures. Both research phases concentrated on methods to determine the number of vehicles per lane per hour that can pass through short-term Interstate work zone lane closures with minimum or acceptable levels of delay as defined by South Carolina DOT. ...

Methodology for Developing Transit Bus Speed-Acceleration Matrices for Load-Based Mobile Source Emissions Models

An emissions model for transit bus based on road load estimates emissions as a function of transit bus power demand for given transit bus activities and environmental conditions. Transit bus speed and acceleration rates are key activity parameters and are the most important parameters in the estimation of transit bus power demand, also known as engine load. Once the transit bus engine load is calculated for a given speed and acceleration, emissions in grams per vehicle hour can be calculated with grams per brake-horsepower hour emission rates. However, collecting speed and acceleration data on various road types and times of day requires extensive efforts for use in load-based mobile source emissions models. To quantify Atlanta regional transit bus speed and acceleration rates, the Georgia Institute of Technology research team installed trip data in a transit bus operated by the Metropolitan Atlanta Rapid Transit Authority. The team collected second-by-second speed and location data for 3 weeks on a varie...