Automated Author ProfileSullivan, John M.
Sullivan, John M.
Current S-Index
Sum of Dataset Indices for all datasets
Average Dataset Index per Dataset
Average Dataset Index per dataset
Total Datasets
Total datasets for this author
Average FAIR Score
Average FAIR Score per dataset
Total Citations
Total citations to the author's datasets
Total Mentions
Total mentions of the author's datasets
S-Index Interpretation
The S-Index (Sharing Index) is a comprehensive metric that represents the cumulative impact of all your datasets. It is calculated as the sum of Dataset Index scores across all your claimed datasets.
What it means:
- A higher S-index indicates greater overall impact of your datasets relative to typical datasets in their fields of research
- The S-Index grows as you add more datasets or as existing datasets gain more citations and mentions
- It provides a single number to track your research data impact over time
Current S-Index: 1.1 (sum of 2 datasets Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
Cumulative Mentions Over Time
Datasets
Objective: The few observational studies of the prevalence of high beam use indicate the rate of high beam use is about 25% when vehicles are isolated from other vehicles on unlit roads. Recent studies were limited to 2-lane rural roads and used measurement methods that likely overestimated use. The current study examined factors associated with the rate of high beam use of isolated vehicles on a variety of roadways in the Ann Arbor, Michigan area. Methods: Twenty observation sites were categorized as urban, rural, or on a rural/urban boundary and selected to estimate the effects of street lighting, road curvature, and direction of travel relative to the city on high beam use. Sites were selected in pairs so that a majority of traffic passing one site also passed through the other. Measurement of high beams relied on video data recorded for 2 nights at each site, and the video data also were used to derive a precise measure of the proximity of other traffic. Nearly 3,200 isolated vehicles (10 s or longer from other vehicles) were observed, representing 1,500-plus vehicle pairs. Results: Across the sample, 18% of the vehicles used high beams. Seventy-three percent of the 1,500-plus vehicle pairs used low beams at each paired site, whereas 9% used high beams at both sites. Vehicles at rural sites and sites at the boundaries of Ann Arbor were more likely to use high beams than vehicles at urban sites, but use in rural areas compared with rural/urban boundary areas did not vary significantly. Rates at all sites were much lower than expected, ranging from 0.9 to 52.9%. High beam use generally increased with greater time between subject vehicles and leading vehicles and vehicles in the opposing lane. There were mixed findings associated with street lighting, road curvature, and direction of travel relative to the city. Conclusion: Maximizing visibility available to drivers from headlights includes addressing the substantial underuse of high beam headlamps. Advanced technologies such as high beam assist, which switches automatically between high and low beam headlamps depending on the presence of other traffic, can help to address this problem.
Authors
- Reagan, Ian J. ;
- Brumbelow, Matthew L. ;
- Flannagan, Michael J. ;
- Sullivan, John M.
Objective: The few observational studies of the prevalence of high beam use indicate the rate of high beam use is about 25% when vehicles are isolated from other vehicles on unlit roads. Recent studies were limited to 2-lane rural roads and used measurement methods that likely overestimated use. The current study examined factors associated with the rate of high beam use of isolated vehicles on a variety of roadways in the Ann Arbor, Michigan area. Methods: Twenty observation sites were categorized as urban, rural, or on a rural/urban boundary and selected to estimate the effects of street lighting, road curvature, and direction of travel relative to the city on high beam use. Sites were selected in pairs so that a majority of traffic passing one site also passed through the other. Measurement of high beams relied on video data recorded for 2 nights at each site, and the video data also were used to derive a precise measure of the proximity of other traffic. Nearly 3,200 isolated vehicles (10 s or longer from other vehicles) were observed, representing 1,500-plus vehicle pairs. Results: Across the sample, 18% of the vehicles used high beams. Seventy-three percent of the 1,500-plus vehicle pairs used low beams at each paired site, whereas 9% used high beams at both sites. Vehicles at rural sites and sites at the boundaries of Ann Arbor were more likely to use high beams than vehicles at urban sites, but use in rural areas compared with rural/urban boundary areas did not vary significantly. Rates at all sites were much lower than expected, ranging from 0.9 to 52.9%. High beam use generally increased with greater time between subject vehicles and leading vehicles and vehicles in the opposing lane. There were mixed findings associated with street lighting, road curvature, and direction of travel relative to the city. Conclusion: Maximizing visibility available to drivers from headlights includes addressing the substantial underuse of high beam headlamps. Advanced technologies such as high beam assist, which switches automatically between high and low beam headlamps depending on the presence of other traffic, can help to address this problem.
Authors
- Reagan, Ian J. ;
- Brumbelow, Matthew L. ;
- Flannagan, Michael J. ;
- Sullivan, John M.