A5026376066- Traffic and Road Safety
- Occupational Health and Safety Research
- Traffic Prediction and Management Techniques
- Transportation Planning and Optimization
- Musculoskeletal pain and rehabilitation
- Ergonomics and Musculoskeletal Disorders
- Risk and Safety Analysis
- Human-Automation Interaction and Safety
- Effects of Vibration on Health
- Vehicle emissions and performance
- Occupational Health and Safety in Workplaces
- Autonomous Vehicle Technology and Safety
- Automotive and Human Injury Biomechanics
- Point processes and geometric inequalities
Auburn University
2018-2023
Job rotation is an organisational strategy that can be used, in part, to reduce occupational exposure physical risk factors associated with work-related musculoskeletal disorders (MSDs). Recent studies, however, suggest job schedules may increase the overall of injury workers included scheme. We describe a novel optimisation framework evaluating effectiveness scheme using fatigue failure model MSD development and case study real data. Results effect highly-dependent on composition pool,...
We aim to study the potential of job rotation schemes improve worker safety. To this end, we developed a novel optimization framework based on recently proposed fatigue-failure model for musculoskeletal disorder (MSD) risk evaluation. then employed it conduct an illustrative case study. demonstrate that effect is highly dependent composition pool. Namely, if pool contains high-risk tasks (e.g., those carrying greater than 90% probability developing disorder), may be impossible observe any...
Quality in the trucking industry involves several facets, including on-time performance and safety. In largest naturalistic driving study to-date, with 496 drivers 13 M miles driven, we address two safety questions: (a) does occurrence of critical events increase during a shift? (b) what is effect rest breaks on incidence those events? To these questions, adopt point process models, commonly used to assess reliability repairable systems, model occurrence/likelihood events. account for driver...
With more and data related to driving, traffic, road conditions becoming available, there has been renewed interest in predictive modeling of traffic incident risk corresponding factors. New machine learning approaches particular have recently proposed, with the goal forecasting occurrence either actual incidents or their surrogates, estimating driving over specific time intervals, segments, both. At same time, as evidenced by our review, prescriptive literature (e.g., routing truck...