Reginald R. Souleyrette

Pavement Marking Retroreflectivity: Analysis of Safety Effectiveness

Previous research has shown that greater longitudinal pavement marking retroreflectivity levels increase drivers’ visibility and detection distance. However, increased visibility may cause drivers to feel too comfortable during nighttime conditions, and drivers may then pay less attention, operate their vehicles at unsafe speeds, or both. Before-and-after studies have been conducted on a pavement marking improvement such as repainting stripes or changing to a more durable marking material. Studies have also used models to estimate the retroreflectivity on the basis of the date of installation and vehicle exposure or have assumed a linear reduction in retroreflectivity over time. Only two studies have related field-measured pavement marking retroreflectivity to safety performance (crash data). One study analyzed the relationship between 3 years of pavement marking retroreflectivity data collected by the Iowa Department of Transportation on all state primary roads and corresponding crash and traffic data. The other study developed a spatial–temporal database by using measured retroreflectivity data to account for the deterioration of pavement markings over time, along with a statewide crash database to attempt to quantify a relationship between crashes and the quality (measured by retroreflectivity) of pavement marking. Three sets of data were analyzed: the complete database, records for two-lane roads, and records with retroreflectivity values less than or equal to 200 mcd/m2/lx only. The distributions and models of the entire database and the two-lane records did not show that poor pavement marking retroreflectivity correlated to a higher crash probability. However, when only records with retroreflectivity values of 200 mcd/m2/lx or less were examined, a statistically significant, albeit weak, relationship was determined.

Application of Light Detection and Ranging Technology to Highway Safety

An application of light detection and ranging (LIDAR) technology to highway intersection safety is presented. LIDAR can be used to collect information about a surface by reflecting thousands of light beams per second off the surface and measuring the return time of the beams. The surface profile is collected as a digital signature that can be used in a variety of applications. Collection of information on the surface profile of the earth in the form of elevation data is one of several LIDAR applications that have been used for mapping and contouring. The focus of the described application is use of LIDAR elevation data to obtain information on intersection geometry that can lead to the discovery of potential obstructions in driver sight lines. After appropriate transformations, LIDAR elevation data were used in line-of-sight analysis to obtain information on sight-line obstructions at six intersections on the IA-1 corridor in Iowa. Intersection crash frequency and data availability were considerations in the selection of the six intersections. Results from the line-of-sight analysis were validated by visits to the intersections in the field and verification of the existence of obstructions detected during the analysis. Sixty-six lines of sight were blocked during the line-of-sight analysis, of which 62 (89.8%) were confirmed during the validation process. Four (5.8%) sight-line obstructions were not confirmed during the validation. At least three (4.4%) potential sight-line obstructions discovered during validation were not detected during the line-of-sight analysis. The intersection with the highest crash frequency was correctly found to have obstructions located within the intersection sight triangles. It can be concluded that LIDAR elevation data can be used successfully for identifying potential sight-distance problems at intersections. Identified potential problems can be verified and rectified in the field. LIDAR is a relatively costly data source, and a single application, such as this one, cannot justify the high cost of LIDAR data acquisition. Other potential highway safety enhancing applications of LIDAR must be investigated to offset the high data-acquisition cost. Suggestions for other highway safety applications are provided.

Investigating the Use of 3D Graphics, Haptics (Touch), and Sound for Highway Location Planning

Planning of transportation infrastructure requires analyzing combinations of many different types of geospatial information (maps). Conventional Geographic Information Systems (GIS) or Computer Aided Design systems limit the planners ability to perceive and effectively use multiple data layers together. To improve the planners ability to interact with multiple layers of disparate spatial information, this article presents a novel computer system, which combines vision with haptics (touch) and sound. In this new form of Multi-Sensory Information System (MSIS), visual information is augmented by a 3-D haptic device (PHANToM) and by sound (sonification). In a recent study, it was investigated how engineering students used this multi-sensory GIS for planning the location (the alignment) of a new road. The results indicate that certain forms of vision, haptics, and audio were used preferentially to represent certain types of spatial data. A generalization of such a multi-sensory approach could provide researchers with the basis for further development and, eventually, the augmentation of established procedures with the MSIS in highway location planning and related areas.

Impact of 65-mph Speed Limit on Iowa's Rural Interstate Highways: Integrated Bayesian Forecasting and Dynamic Modeling Approach

In 1987, a provision of the Surface Transportation and Uniform Relocation Assistance Act allowed states to raise speed limits on rural Interstates to 65 mph (104.6 km/h). By 1995, nearly all states had done so. Several studies have investigated the safety impacts of these increases. Methodologies varied from analysis of variance to simple before and after comparison and have included time series procedures, with and without intervention variables. In general, these studies have produced contradictory findings. An integrated Bayesian forecasting and dynamic modeling approach used to determine the impact of the increased speed limit on rural Interstates of Iowa is reported. The approach is used to verify that raising the speed limit to 65 mph (104.6 km/h) led to an increase in fatal accidents on rural Interstates of Iowa. Comparison of fatal accident data on rural Interstates of Iowa and New Jersey yields similar results. Although this conclusion was anticipated, the study further demonstrates that a Bayesian/dynamic approach is more robust than the standard time series model.

Pseudo-Dynamic Travel Model Application to Assess Traveler Information

This paper reports an effort to estimate potential benefits of Advanced Traveler Information Systems (ATIS) by combing regional travel demand and microscopic simulation models. The approach incorporates dynamic features not yet available in the commercial software market. The suggested technique employs data that are readily available to most urban planning organizations, and is straightforward in its application. The key reported measure of effectiveness is corridor and local system delay, and is sensitive to both the level of penetration of traveler information and the pre-trip and en-route choices drivers make based on this information. The technique is demonstrated on an urban freeway corridor in a medium sized mid-west city.

Identifying and Measuring Horizontal Curves and Related Effects on Highway Safety

Although crash rates on U.S. highways have decreased in recent years, nearly 34,000 fatalities were reported for 2009. Many of these deaths occur on high-speed rural roads, where crashes at curves are particularly likely. To analyze and systematically mitigate risk on highway curves, the curves must first be located and measured. This article presents a hybrid manual-computer method that uses a geographic information system (GIS)-based procedure, global positioning system (GPS) road data, circular regression, chord equations, and line simplification to identify and measure curves. Measures are validated with “as-built” design plans, and predicted safety-performance sensitivity to measurement errors is tested using Highway Safety Manual functions. Results indicate predicted performance is more sensitive to curve parameter errors for short tight curves and to errors in length than to errors in radius. The length measurement–induced errors may be reduced by analyzing tangents and curves as a whole. The impact of radius-measurement error is shown to be dependent on curve length. Although the ability of the method to measure curve parameters over a wide range of length and radius is limited, the curve identification strategy provides an efficient means to identify curves for implementation of low-cost safety improvement measures.

Integration of light detection and ranging technology with photogrammetry in highway location and design

Surface terrain information is needed to economically site new or relocate existing infrastructure facilities and make final design plans. Field surveying and photogrammetric mapping are the methods most widely used to acquire these data. However, these methods are time- and resource-intensive, as significant data collection and reduction are needed to provide the level of detail necessary for facility location and design. Light detection and ranging (LIDAR) is a relatively new alternative technology for obtaining terrain information more efficiently. With LIDAR, data can be collected under a variety of environmental conditions, including low sun angle, cloudy skies, and even darkness, resulting in expanded windows for data collection. Although less accurate than photogrammetric mapping, LIDAR can help expedite the highway location and design process by providing designers with preliminary terrain information earlier in the process. Presented is a proposed methodology for using LIDAR in conjunction with photogrammetric mapping to speed up highway location and design activities, including estimates of time and cost savings.

Optimizing the Alignment of Inspection Data from Track Geometry Cars

Track geometry car inspections play a vital role in assessing railroad track quality and scheduling track maintenance. Effective use of inspection data depends on accurate location measurement. Field surveys reveal that measured milepoint positions can be off by up to 200 m. Previous efforts to correct milepoint errors resulted in the development of the Key Equipment Identification model, which reduces errors to below 5 m and in most cases to below 1 m for new inspections. However, analysis of track segment deterioration requires the alignment of historical inspection data. This article presents an improved method for aligning these historical inspections. The core of the approach is an optimization model termed Dynamic Sampling Position Matching (DSPM). DSPM overcomes limitations of existing methods and their assumptions that milepoint shifts between inspections are constant and that no track maintenance is carried out between inspections. A case study is presented using inspection data from the Jinan Bureau of China Railways demonstrating improved performance over two widely used inspection alignment models. Results indicate that DSPM better tolerates noisy measurements and that inspections processed by DSPM align precisely. And it takes the developed model 2.82 seconds on average to align inspection data for a track segment of 1 km.

Determining Vehicle Operating Speed and Lateral Position Along Horizontal Curves Using Linear Mixed-Effects Models

Objective: Despite recent improvements in highway safety in the United States, serious crashes on curves remain a significant problem. To assist in better understanding causal factors leading to this problem, this article presents and demonstrates a methodology for collection and analysis of vehicle trajectory and speed data for rural and urban curves using Z-configured road tubes. Methods: For a large number of vehicle observations at 2 horizontal curves located in Dexter and Ames, Iowa, the article develops vehicle speed and lateral position prediction models for multiple points along these curves. Linear mixed-effects models were used to predict vehicle lateral position and speed along the curves as explained by operational, vehicle, and environmental variables. Behavior was visually represented for an identified subset of “risky” drivers. Results: Linear mixed-effect regression models provided the means to predict vehicle speed and lateral position while taking into account repeated observations of the same vehicle along horizontal curves. Conclusions: Speed and lateral position at point of entry were observed to influence trajectory and speed profiles. Rural horizontal curve site models are presented that indicate that the following variables were significant and influenced both vehicle speed and lateral position: time of day, direction of travel (inside or outside lane), and type of vehicle.

Validation of U.S. Road Assessment Program Star Rating Protocol: Application to Safety Management of U.S. Roads

The U.S. Road Assessment Program, in cooperation with road assessment programs in other countries, has developed a protocol to assign ratings to roads on the basis of the presence or absence of key design features related to safety. This protocol rates roads by assigning them one to five stars according to approximately 20 key roadway safety features. A recently developed web-based software tool uses the roadway inventory data on which the star ratings are based to identify cost-effective safety improvement programs for the road networks covered by the ratings. The research results are presented to validate the relationship between the star ratings and crash rates for selected roadways. The research developed star ratings for approximately 3,000 mi of rural and urban roadways of various types in Iowa and Washington State and compared the star ratings with crash rates for the same roads. Relationships between star ratings and crash rates were found for two-lane undivided highways, four-lane undivided highways, and four-lane divided nonfreeways. No clear relationships could be demonstrated for freeways because the design characteristics of freeways are very uniform.