TY  - JOUR
PY  - 2024//
TI  - Development of computer vision informed container crane operator alarm methods
JO  - Transportmetrica A: transport science
A1  - Yan, Ran
A1  - Tian, Xuecheng
A1  - Wang, Shuaian
A1  - Peng, Chuansheng
SP  - e2145862
EP  - e2145862
VL  - 20
IS  - 2
N2  - To reduce the extra work, the operation cost, and the risk of cargo delay induced by the unloading of wrong containers, this study first develops a container color detection model to predict the color of the container being unloaded. The prediction results are then used to develop two crane operator alarm methods. <br><br>METHOD 1 alerts the crane operator if the detected color of a container is not in compliance with the correct container color. <br><br>METHOD 2 constructs a decision problem to decide whether to alert the operator. The results of numerical experiments show that methods 1 and 2 are better than the benchmark. Specifically, method 1 can save the expected annual total cost by about 82% while method 2 can save the expected annual total cost by about 85%. Extensive sensitivity analysis is also conducted to verify the methods performance and robustness.<p />  <p>Language: en</p>
LA  - en
SN  - 2324-9935
UR  - http://dx.doi.org/10.1080/23249935.2022.2145862
ID  - ref1
ER  -