Evaluation of Section Speed Enforcement System Using Empirical Bayes Approach and Turning Point Analysis

Speeding is a major risk factor for traffic-related injuries. As a countermeasure against speeding, automated speed enforcement systems (ASES) have been deployed in many countries. However, drivers’ awareness of enforcement locations allows themselves to adjust vehicle speeds in the vicinity of the...

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Bibliographic Details
Published inJournal of advanced transportation Vol. 2020; no. 2020; pp. 1 - 11
Main Authors Chung, Sungbong, Park, Shin Hyoung, Kwon, Oh Hoon, Shim, Jisup, Jang, Kitae
Format Journal Article
LanguageEnglish
Published Cairo, Egypt Hindawi Publishing Corporation 2020
Hindawi
John Wiley & Sons, Inc
Hindawi Limited
Hindawi-Wiley
Subjects
Avoidance behavior
Bayesian analysis
Comparative analysis
Empirical analysis
Enforcement
Health risks
Injury analysis
Installation
Reduction
Risk analysis
Risk factors
Sensors
Speed limits
Studies
Traffic accidents
Traffic safety
Traffic speed
Transportation
Travel
Vehicles
Velocity
United Kingdom
South Korea
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Summary:Speeding is a major risk factor for traffic-related injuries. As a countermeasure against speeding, automated speed enforcement systems (ASES) have been deployed in many countries. However, drivers’ awareness of enforcement locations allows themselves to adjust vehicle speeds in the vicinity of the enforcement locations. This enforcement avoidance behavior leads to a criticism of the effectiveness of ASES, in which the system promotes abrupt changes in vehicle speed near enforcement locations, increasing crash risk as a side effect. To address this issue, the section speed enforcement system (SSES), which enforces overspeeding vehicles by their average travel speed over a section, has been devised. In this study, we evaluate traffic speed and safety data that were collected from sections with SSES on Korean expressways. The speed analysis showed that the vehicles reduced their speeds inside the enforcement section, and this reduction in speed variations across vehicles was also noticeable, signifying that the risk of traffic crash should be lower. In view of this, we have performed before and after comparative analysis using the empirical Bayes method with the comparison group. The outcomes estimate 43% reduction in crash occurrence after installation of SSES. Furthermore, turning point analysis confirmed that the reduction in crash occurrence ensued immediately after installation of SSES.
ISSN:0197-6729
2042-3195
DOI:10.1155/2020/9461483