@article{song_kim_williams_rouphail_list_2020, title={Crash Classification by Congestion Type for Highways}, volume={10}, ISSN={["2076-3417"]}, url={https://doi.org/10.3390/app10072583}, DOI={10.3390/app10072583}, abstractNote={Effective management of highway networks requires a thorough understanding of the conditions under which vehicular crashes occur. Such an understanding can and should inform related operational and resource allocation decisions. This paper presents an easily implementable methodology that can classify all reported crashes in terms of the operational conditions under which each crash occurred. The classification methodology uses link-based speed data. Unlike previous secondary collision identification schemes, it neither requires an a priori identification of the precipitating incident nor definition of the precipitating incident’s impact area. To accomplish this objective, the methodology makes use of a novel scheme for distinguishing between recurrent and non-recurrent congestion. A 500-crash case study was performed using a 274 km section of the I-40 in North Carolina. Twelve percent of the case study crashes were classified as occurring in non-recurrent congestion. Thirty-seven percent of the crashes in non-recurrent congestion classified were identified within unreported primary incidents or crashes influence area. The remainder was classified as primary crashes occurring in either uncongested conditions (84%) or recurrent congestion (4%). The methodology can be implemented in any advanced traffic management system for which crash time and link location are available along with corresponding archived link speed data are available.}, number={7}, journal={APPLIED SCIENCES-BASEL}, publisher={MDPI AG}, author={Song, Tai-Jin and Kim, Sangkey and Williams, Billy M. and Rouphail, Nagui M. and List, George F.}, year={2020}, month={Apr} }
 @article{kim_hajbabaie_williams_rouphail_2016, title={Dynamic Bandwidth Analysis for Coordinated Arterial Streets}, volume={20}, ISSN={["1547-2442"]}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-84941243905&partnerID=MN8TOARS}, DOI={10.1080/15472450.2015.1074575}, abstractNote={A commonly used strategy for improving mobility along signalized arterials is to coordinate neighboring intersections to minimize vehicle stops by maximizing the duration of green bands, otherwise known as arterial bandwidth. Signal coordination has been researched, developed, and refined for five decades. In lieu of traditional methods that are based on the analysis of programmed green times (which assume all phases operate at their maximum settings), a dynamic bandwidth analysis method is presented that reproduces actual dynamic bandwidth durations using closed loop signal data. The analysis is intended to help assess the performance of semi-actuated coordinated signal systems on arterial streets. In addition, the study highlights the arterial progression benefits that result from changing coordinated intersection offsets based on optimizing the dynamic, rather than the programmed, bandwidths. Detailed analysis at three arterial sites revealed that coordinated green phase time distributions are complex and multimodal and cannot be represented by a single-valued statistic. Dynamic bandwidth analysis confirmed that programmed green bandwidth consistently underestimates the size of the actual dynamic bandwidth, and exhaustive search results highlighted the potential for further improvements in coordination. Future research will include field and simulation comparative studies and the development of efficient methods for dynamic bandwidth optimization.}, number={3}, journal={JOURNAL OF INTELLIGENT TRANSPORTATION SYSTEMS}, author={Kim, Sangkey and Hajbabaie, Ali and Williams, Billy M. and Rouphail, Nagui M.}, year={2016}, pages={294–310} }
 @article{kim_song_rouphail_aghdashi_amaro_goncalves_2016, title={Exploring the association of rear-end crash propensity and micro-scale driver behavior}, volume={89}, ISSN={["1879-1042"]}, DOI={10.1016/j.ssci.2016.05.016}, abstractNote={The relationship between driver behavior at the tactical level and crash experience is a long sought association that has been elusive to explore. The availability of in-vehicle sensing devices capable of capturing and documenting micro-scale dynamic driver behavior offers the opportunity to begin such an exploration. This study integrates rear-end crash data experienced on a 63-mile section of I-40 in North Carolina over a four-year period with three months of micro-scale driving behavioral data gathered by an in-vehicle sensing system (i2D) that records and dispatches second by second vehicle dynamics data to a central database. The information collected by the i2D devices came from a fleet of about 20 vehicles driven by volunteers in their naturalistic driving environment. Additionally all crash and driver data were geo-located onto a link-based GIS environment. The objective of this study is to explore the association of crash propensity and micro-scale driving behavior. The initial findings of this research are promising. First, over 85% of all rear-end crashes occurred on 30 segments extending from 2000 feet upstream of an on-ramp to the on-ramp itself. Secondly, on those segments with high crash rates we have detected a high propensity of drivers to decelerate at high rates (4 m/s2 or more). We have also tested and confirmed that the sharp deceleration phenomenon is not confined to a few drivers, but appears to be common for the high-crash segments, using trip-based analyses. Language: en}, journal={SAFETY SCIENCE}, author={Kim, SangKey and Song, Tai-Jin and Rouphail, Nagui M. and Aghdashi, Seyedbehzad and Amaro, Ana and Goncalves, Goncalo}, year={2016}, month={Nov}, pages={45–54} }
 @article{kim_warchol_schroeder_cunningham_2016, title={Innovative Method for Remotely Fine-Tuning Offsets Along a Diverging Diamond Interchange Corridor}, ISSN={["2169-4052"]}, DOI={10.3141/2557-04}, abstractNote={Diverging diamond interchanges (DDIs) are relatively new in the United States, and signal coordination between the crossovers and adjacent intersections is challenging. This paper provides a method for remotely fine-tuning offsets for a DDI and its adjacent intersections. The proposed method uses the dynamic bandwidth analysis tool (DBAT). The tool uses actuated phase times from the signal controller to optimize the dynamic bandwidth on the basis of that entry data set. Four performance measures evaluated the proposed method: delay, stop severity index, maximum queue, and vehicle trajectory plots. The test results confirmed that DBAT provided a better offset solution than other bandwidth optimization tools that generally optimized programmed bandwidth only and did not account for early return to green caused by skipped or gapped-out movements. Under the DBAT offsets, delay for the through movements on the corridor decreased by 52.8% for northbound vehicles and 46.83% for southbound vehicles. The average delay reduction over all measured paths for uncongested and congested scenarios was 13.88% and 3.50%, respectively. The proposed method and workflow can significantly reduce the offset retiming work process. Normally, this manual process takes more than a day, but the proposed method can be completed in less than an hour without visiting the study site. Furthermore, the proposed method can coordinate any set of movements, as well as multiple travel paths. The authors believe that the proposed method and workflow will significantly help both retiming and new timing of arterial signal coordination along DDI corridors and other signal systems.}, number={2557}, journal={TRANSPORTATION RESEARCH RECORD}, author={Kim, SangKey and Warchol, Shannon and Schroeder, Bastian J. and Cunningham, Christopher}, year={2016}, pages={33–43} }
 @article{chase_williams_rouphail_kim_2012, title={Comparative Evaluation of Reported Speeds from Corresponding Fixed-Point and Probe-Based Detection Systems}, ISSN={["0361-1981"]}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-84874037734&partnerID=MN8TOARS}, DOI={10.3141/2308-12}, abstractNote={Point-based traffic sensors, such as microwave radar and acoustic sensors, provide the valuable capability of sampling the entire traffic stream. However, full network coverage with point sensors requires a significant initial capital investment and ongoing maintenance expenditures. Probe-based sensors can cover an extensive roadway network at a much lower cost because roadway-based field equipment is not required. Decisions regarding the relative level of point sensor- versus probe-based deployment for traffic monitoring involve evaluating the trade-off between the value of comprehensive detection versus total system costs. An essential step in evaluating this trade-off involves directly comparing collocated point sensor and probe vehicle systems to understand how the derived traffic stream measures from the two approaches differ. This study compared 5-min speeds from microwave radar and acoustic sensors with link speeds from Global Positioning System (GPS) probes for both directions at five freeway locations. Systematic differences were found at one location. Floating car GPS runs were performed to confirm that the systematic error lay in the point speeds. The speed differences at all sites were normally distributed, with three locations indicating a mean speed difference greater than 5 mph. Nonsystematic speed differences were identified; the difference was more than 1.5 standard deviations lower than the mean difference. This difference may indicate inherent inaccuracies in reported GPS speeds under heavy congestion, including instances of time lag in recovering from congested speeds.}, number={2308}, journal={TRANSPORTATION RESEARCH RECORD}, author={Chase, R. Thomas and Williams, Billy M. and Rouphail, Nagui M. and Kim, SangKey}, year={2012}, pages={110–119} }