Modeling trucking industry perspective on the adoption of connected and autonomous trucks
Abstract
This paper predicts the future adoption of Connected Autonomous Truck (CAT) among freight transportation organizations by incorporating the distance decay function-based phenomenon of peer effects into an integrated choice and latent variable model (ICLV). We surveyed 400 freight transportation organizations operating within the United States to capture their preferences and perceptions towards adopting level-3 CATs. By analyzing the responses, we are able to generate a prediction for how quickly freight transportation organizations will choose to test and adopt CATs. Through ICLV, the authors captured the impact of organizations' optimistic attitudes towards their inclination to adopt CATs. The results showed that organizations with an optimistic attitude towards CATs, having members advocating CATs and nationwide coverage, are more likely to adopt CATs. In contrast, organizations with an average trip length of regular trucks of >500 miles are more likely to reject CATs. The peer effect results imply that the future adoption rate of level-3 CATs will be doubled (29%) or quadrupled (57%) from 13% based on the different peer effect coefficient values varying from 0.70 to 0.90. This study will provide key takeaways and policy inputs to planners, policymakers, and researchers to frame and implement plans to bolster the organizational adoption of innovations like autonomous technology.
Publication Title
Research in Transportation Business and Management
Recommended Citation
Simpson, J., Sharma, I., & Mishra, S. (2022). Modeling trucking industry perspective on the adoption of connected and autonomous trucks. Research in Transportation Business and Management, 45 https://doi.org/10.1016/j.rtbm.2022.100883
