Quantifying automated vehicle benefits in reducing driving stress: a simulation experiment approach - Khattak, Zulqarnain H.; Lin, Zhenhong (Frontiers in Future Transportation, 2023)
Driving is a stressful phenomenon due to the mental workload required for maneuvering a vehicle in certain travel contexts such as congested traffic, multi-modal local streets requiring complex interaction with surrounding vehicles and aggressive driving. Autonomous vehicles (AVs) on the other hand can reduce the mental workload by performing most driving tasks and providing a comfortable ride to users. This study develops a pathway model to relate different health determinants including travel reliability, safety, driving comfort, and value of time to AV driving and studies their impact on the value of driving stress. A case study example of AV simulation is used to determine the impact of these health determinants. The value of driving stress in AVs is estimated as a function of value of these individual health determinants. The results show that perception of safe or unsafe driving with AVs is the major contributing factor in changing the perception of driving stress in AVs. Likewise, perception of comfortable ride with AVs and reduced workload with higher value of time also reduces the driving stress in AVs. These results allow AV adoption models to explicitly consider driving stress reduction as a benefit and can improve understanding of AV adoption, which may require quantitative analysis of underlying motivating benefits including driving stress reduction.