Log truck drivers represent a high-risk yet understudied worker population. Logging, more generally, is known to be one of the most dangerous industries in the country, but little is known about injury and fatality rates among log truck drivers specifically. Using data from the Motor Carrier Management Information System (MCMIS), this study aims to characterize log truck crashes in Washington, Oregon, Idaho, and Montana. Using multiple logistic regression, we estimated the odds of a crash resulting in an injury or fatality by environmental and structural conditions at the time of each crash. Results indicate that the presence of a positive median barrier is strongly associated with a decreased odds of injury or fatality for log truck crashes (Odds Ratio (OR) = 0.45, p = 0.03). An increased number of vehicles involved in the crash was significantly associated with an increased odds of injury or fatality (OR = 1.32, p = 0.01). Crashes occurring in Washington or Oregon had significantly decreased odds of resulting in an injury or fatality, in comparison to Idaho and Montana (OR = 0.14, p < 0.001; OR = 0.53, p = 0.01, respectively). These results indicate that the presence of highway safety measures and a state-approved OSHA plan may be beneficial in decreasing the odds of injury or fatality in log truck crashes.

Current cable-road layouts for timber harvesting in steep terrain are often based on either manual planning or automated layouts generated from low-resolution GIS data, limiting potential benefits and informed decision-making. In this paper, we present a novel approach to improve cable-road design using multi-objective optimization based on realistic cable-road representations. We systematically compare the effectiveness of single-objective and multi-objective optimization methods for generating layouts using these representations. We implement and evaluate the performance of a weighted single-objective approach, the AUGMECON2 and NSGA-II multi-objective methods in comparison to a layout manually created by a forestry expert, taking into account installation costs, harvesting volumes, residual stand damage and lateral yarding workload. In addition to implementing the first linear programming multi-objective optimization for realistic cable-road representations by adapting AUGMECON2, we also present the first implementation of a multi-objective genetic algorithm (NSGA-II) with simulated annealing for this purpose and evaluate their respective strengths. We find that the use of multi-objective optimization provides advantages in terms of cost-effective, balanced and adaptable cable-road layouts while allowing economic and environmental considerations to be incorporated into the design phase.