A novel methodological approach for understanding the complex relationship between compensation methods and fatigue among heavy-vehicle drivers
Investigations of heavy vehicle crashes have predominantly taken a reductionist view of accident causation. However, there is growing recognition that broader economic factors play a significant role in producing conditions that promulgate increased crash risk, especially in the area of fatigue. The aim of this study was to determine the utility of using agent-based modelling to understand how driver payment methods may influence driver fatigue, crash-risk, and the response of enforcement agencies to major heavy-vehicle crashes. Results showed that manipulation of payment methods within agent-based models can produce similar patterns of driving behaviour among simulated drivers as that observed in real world studies. Drivers operating under simulated ‘per-km’ and ‘per-trip’ piece rate incentive systems were significantly more likely to drive while fatigued and subsequently incur all associated issues (loss of license, increased crash risk, increased fines) than those paid under flat-rate ‘per hour’ methods. Further, the pattern of enforcement response required under ‘per-km’ and ‘per-trip’ systems was significantly higher in response to greater numbers of major crashes than in flat-rate, per hour regimes. Agent-based models may be a useful means of determining the potential effect of economic policy settings within freight or other transport systems ahead of policy implementation or change.