An Algorithm for Detecting Collision Risk between Trucks and Pedestrians in the Connected Environment
- Title
- An Algorithm for Detecting Collision Risk between Trucks and Pedestrians in the Connected Environment
- Author
- 박준영
- Keywords
- *SUSTAINABLE transportation; *ALGORITHMS; *TRUCKS; *TRANSPORTATION industry; *PEDESTRIANS; *INFORMATION technology
- Issue Date
- 2021-10
- Publisher
- WILEY-HINDAWI
- Citation
- JOURNAL OF ADVANCED TRANSPORTATION, v. 2021, Page. 1-9
- Abstract
- This study develops an algorithm to detect the risk of collision between trucks (i.e., yard tractors) and pedestrians (i.e., workers) in
the connected environment of the port. +e algorithm consists of linear regression-based movable coordinate predictions and
vertical distance and angle judgments considering the moving characteristics of objects. Time-to-collision for port workers
(TTCP) is developed to reflect the characteristics of the port using the predictive coordinates. +is study assumes the connected
environment in which yard tractors and workers can share coordinates of each object in real time using the Internet of +ings
(IoT) network. By utilizing microtraffic simulations, a port network is implemented, and the algorithm is verified using data from
simulated workers and yard trucks in the connected environment. +e risk detection algorithm is validated using confusion
matrix. Validation results show that the true-positive rate (TPR) is 61.5∼98.0%, the false-positive rate (FPR) is 79.6∼85.9%, and the
accuracy is 72.2∼88.8%. +is result implies that the metric scores improve as the data collection cycle increases. +is is expected to
be useful for sustainable transportation industry sites, particularly IoT-based safety management plans, designed to ensure the
safety of pedestrians from crash risk by heavy vehicles (such as yard tractors).
- URI
- https://eds.p.ebscohost.com/eds/detail/detail?vid=0&sid=8916f385-cd15-4b85-b248-acb7150e37bf%40redis&bdata=Jmxhbmc9a28mc2l0ZT1lZHMtbGl2ZQ%3d%3d#AN=153287249&db=a9hhttps://repository.hanyang.ac.kr/handle/20.500.11754/170138
- ISSN
- 0197-6729
- DOI
- 10.1155/2021/9907698
- Appears in Collections:
- COLLEGE OF ENGINEERING SCIENCES[E](공학대학) > TRANSPORTATION AND LOGISTICS ENGINEERING(교통·물류공학과) > Articles
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