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Cyclists and pedestrians account for a disproportionate amount of the world's 1.3 million road deaths every year. This is a growing problem in the United Sates where bicyclist and pedestrian fatalities have increased steadily since 2009. A large body of research suggests vehicle speeds are a key contributing factor for crashes. However, few studies of bicycle or pedestrian crash probability incorporate detailed vehicle speed data. This study uses probe vehicle speed data to examine the impact of vehicle speeds on bicycle and pedestrian crashes on the state of Georgia's network of major arterial roadways. The analysis examines 7000 road segments throughout the state in 2017. A Negative Binomial model relates annual crash and speed data on each segment. Models using speed percentiles (85th, 50th and 15th) are contrasted with models using speed differences (85th-50th and 50th-15th percentile). A small set of covariates are included: segment length, number of lanes, Average Annual Daily Traffic, and urbanicity. Results indicate that larger differences in high-end speed percentiles are positively associated with bicycle and pedestrian crash frequency on Georgia arterials. Furthermore, the coefficients on the high end of the speed distribution, measured by the difference in 85th and 50th percentile speeds, have greater magnitude and statistical significance than the low end of the distribution. This research shows a negative relationship between speed and crashes may be flawed, as it does not account for the distributions of speed. The findings in this study suggest that planners and engineers should identify areas with large speed distributions, especially at the high vehicle speeds, and work to reduce the fastest speeds on these roadways. To do so, differences in speed percentiles measured using probe vehicle speeds can be used to determine where high risk areas are located., (Copyright © 2021. Published by Elsevier Ltd.)

Based on requirements under the Clean Air Act Amendments of 1990, most state vehicle inspection and maintenance (I/M) programs have, since 2002, replaced the tailpipe emission testing with the on-board diagnostic (OBD) II testing for 1996 model and newer vehicles. This test relies on the OBD II system to give the pass or fail result, depending on certain conditions that might cause the vehicle to emit pollution 1.5 times higher than the regulated standard. The OBD II system is a computer and sensors installed in the vehicle to monitor the emission control units and signal if there is any malfunction. As a vehicle ages, its engine, pollution control units, and OBD II system deteriorate. Because the OBD II system's durability directly influences the test outcome, it is important to examine the fleetwide trend in the OBD II test results in comparison with an alternative measure of identifying high emitting vehicles. This study investigates whether the validity and reliability of the OBD II test is related to the age of the OBD II system installed in the fleet. Using Atlanta's I/M testing records and remote sensing device (RSD) data collected during 2002-2005, this research establishes the convergent validity and interobserver reliability criteria for the OBD II test based on on-road emissions measured by RSDs. The study results show that older vehicles exhibit significantly lower RSD-OBD II outcome agreement than newer vehicles. This suggests that the validity and reliability of the OBD II test may decline in the older vehicle fleets. Explanations and possible confounding factors for these findings are discussed.

The research presented in this paper employs the Step Method of Inspection/Maintenance (I/M) program evaluation to estimate the emissions reduction for an Atlanta I/M program. Stedman et al. (Stedman, D. H.; Bishop, G. A.; Aldrete, P.; Slott, R. S. Environ. Sci. Technol. 1997, 31, 927-931) introduced the Step Method of evaluation when they presented the results of a 1995 Denver I/M program evaluation. The research presented here replicates the original Denver Step Method analysis for a 1997 Atlanta I/M program. This evaluation was conducted separately for the nine outlying Atlanta counties and the four counties that are closest to the center of the city. The results of the analysis are similar to those found by Stedman et al. in Denver. While the Denver carbon monoxide (CO) weighted program benefit was 6.9%, the Atlanta area CO weighted program benefit is found to be 11.5% and 4.9% for the nine-county and four-county Atlanta areas, respectively. We conclude that the 1997 I/M program change in Atlanta yielded a noteworthy and observable change in fleet emissions.

On-road remote sensing data is an increasingly popular source of evaluation information for vehicle inspection/maintenance (I/M) programs. This article conducts one such remote sensing data evaluation for the Atlanta, Georgia, I/M program. The reference method involves comparing emissions differences in I/M and non-I/M fleet vehicles with those predicted by a regulatory computer model. Assuming that on-road emissions differences represent observed effectiveness and model-predicted emissions differences represent effectiveness goals, the Atlanta enhanced I/M program appears to be achieving 83% of its targeted emissions reductions. The method compares favorably with other remote sensing evaluation methods in its ability to be applied over time and its relatively small sample size requirement. The chief limitation to the approach is its reliance on a representative non-I/M fleet, which may differ in characteristics for which controls are difficult to locate. Such potential confounding factors include discrepancies in maintenance trends, socioeconomic conditions, and vehicle quality.