Open AccessVerifying driver performance for heavy haulage fatigue management
Author(s) -
Vo Son Anh,
Mirowski Luke,
Scanlan Joel,
Turner Paul
Publication year - 2019
Publication title -
iet intelligent transport systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.579
H-Index - 45
eISSN - 1751-9578
pISSN - 1751-956X
DOI - 10.1049/iet-its.2018.5314
Subject(s) - haulage , automotive engineering , transport engineering , computer science , engineering , structural engineering , rope
Working performance of drivers is an important concern of commercial logistics firms as it directly relates to operational efficiency targets. However, in heavy vehicle activity, the enforcement of fatigue management rules by the Australian government can potentially influence this efficiency as the regulation scheme controls maximum work time and minimum rest time of drivers. Therefore, evaluating a driver's performance in the context of fatigue compliance is an essential need that aims to assist transport operators to increase their operational efficiencies. This research proposes a method in assessing how well a driver performs his job by using anomaly detection principles from intrusion detection systems in network security. This approach utilises output data of the logistics fatigue manager application and compliance outcomes of the fatigue compliance verification system to measure the driver's performance. In addition to performance concerns, the system also monitors safety levels based on fatigue conditions of drivers to ensure that the positive evaluation outcomes can be applied standards for the whole fleet in practice. The results highlight the opportunity to monitor driver fatigue levels for verifying fatigue risk within existing fatigue compliance requirements.