@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_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.}, 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{song_park_oh_2016, title={Field experiment for exploring the effects of in-vehicle warning information on driver's responsive behaviour}, journal={Journal of Engineering-JOE}, author={Song, T. J. and Park, S. and Oh, C.}, year={2016} }
 @article{chung_song_yoon_2014, title={Injury severity in delivery-motorcycle to vehicle crashes in the Seoul metropolitan area}, volume={62}, ISSN={["1879-2057"]}, DOI={10.1016/j.aap.2013.08.024}, abstractNote={More than 56% of motorcycles in Korea are used for the purpose of delivering parcels and food. Since such delivery requires quick service, most motorcyclists commit traffic violations while delivering, such as crossing the centerline, speeding, running a red light, and driving in the opposite direction down one-way streets. In addition, the fatality rate for motorcycle crashes is about 12% of the fatality rate for road traffic crashes, which is considered to be high, although motorcycle crashes account for only 5% of road traffic crashes in South Korea. Therefore, the objective of this study is to analyze the injury severity of vehicle-to-motorcycle crashes that have occurred during delivery. To examine the risk of different injury levels sustained under all crash types of vehicle-to-motorcycle, this study applied an ordered probit model. Based on the results, this study proposes policy implications to reduce the injury severity of vehicle-to-motorcycle crashes during delivery.}, journal={ACCIDENT ANALYSIS AND PREVENTION}, author={Chung, Younshik and Song, Tai-Jin and Yoon, Byoung-Jo}, year={2014}, month={Jan}, pages={79–86} }