title: Enforcement avoidance behavior near automated speed enforcement areas in Korean expressways.
abstract: Automated speed enforcement system (ASES) has been deployed as a safety countermeasure on Korean roadways to reduce speeding-related traffic crashes; information on ASES locations is mandated to be open to the public. However, because drivers are alerted about enforcement via on-board navigation systems and roadside signs, they can avoid enforcement by momentarily reducing their speeds near ASES locations. This enforcement avoidance behavior (EAB) can induce sudden changes in speed near the enforcement locations and thereby increase risk of crash occurrence. In light of this situation, the present study evaluates the effects of ASES on traffic behavior and safety. An analysis of traffic data shows that drivers indeed diminish their speeds near enforcement locations, and accelerate shortly after passing the locations. To investigate how this behavior affects safety performance, this study, by using Empirical Bayes analysis with comparison groups, compares crash occurrences along a certain section before and after the installation of ASES. The comparative analysis shows that overall crash occurrence dropped by 7.6% on average near the enforcement locations, although the reduction was not significant. However, an average 11% non-significant increase in crash occurrence is also observed in the upstream segment, where enforcement is announced to drivers and traffic starts to diminish speed. The findings suggest that the sudden changes in traffic speed induced by EAB substantially negate the benefits of ASES. Therefore, modification of the design of current ASES is required to mitigate EAB and further improve the effectiveness of ASES.
authors.affiliation: The Cho Chun Shik Graduate School for Green Transportation, Korea Advanced Institute of Science and Technology, 291 Daehak-ro, Yuseong-gu, Daejeon 305-701, South Korea. Electronic address: gisup89@kaist.ac.kr.
authors.forename: Jisup
authors.initials: J
authors.lastname: Shim
authors.affiliation: Department of Transportation Engineering, College of Engineering, Keimyung University, 1095 Dalgubeol-daero, Dalseo-gu, Daegu 704-701, South Korea. Electronic address: shpark@kmu.ac.kr.
authors.forename: Shin Hyoung
authors.initials: SH
authors.lastname: Park
authors.affiliation: Graduate School of Railroads, Seoul National University of Science & Technology, 232 Gongneung-ro, Nowon-gu, Seoul 139-743, South Korea. Electronic address: sbchung@snut.ac.kr.
authors.forename: Sungbong
authors.initials: S
authors.lastname: Chung
authors.affiliation: The Cho Chun Shik Graduate School for Green Transportation, Korea Advanced Institute of Science and Technology, 291 Daehak-ro, Yuseong-gu, Daejeon 305-701, South Korea. Electronic address: kitae.jang@kaist.ac.kr.
authors.forename: Kitae
authors.initials: K
authors.lastname: Jang
mesh_terms: D000063:Accidents, Traffic / Q000706:statistics & numerical data*; D001334:Automobile Driving / Q000331:legislation & jurisprudence* / Q000523:psychology*; D001362:Avoidance Learning; D001499:Bayes Theorem; D006801:Humans; D035846:Law Enforcement; D010781:Photography / Q000295:instrumentation; D056910:Republic of Korea; D012449:Safety
keywords: Automated speed enforcement; Empirical Bayesian analysis; Enforcement avoidance behavior; Safety