The integration of automated vehicle (AV) technology into surface transportation is expected to reduce environmental impacts and enhance the movement of people and goods in the United States. While there has been significant growth in the development of AV, however, issues related to cybersecurity, data privacy, connectivity, and operating system maintenance costs contribute to its complexity and there is great uncertainty about the rate of deployment. Transportation agencies planning for AV implementation need realistic implementation timelines to aid decision-making. They need to identify a range of estimates—from optimistic to conservative—of market introduction and growth profiles for a broad range of the representative automated driving services that account for limiting factors such as rate of advancement in technologies, level of effort needed to expand operational design domains for each AV application, and the time and conditions for users to adopt new technologies.
The objectives of this research were to (1) identify influencing factors and risks that affect the timing of the deployment of the Society of Automotive Engineers (SAE) Level 4 AV technologies, described in SAE J3016, in diverse scenarios; (2) define operational concept and input parameters for a decision-making model that will estimate deployment timeframes; and (3) develop recommendations for how and at what frequency a model and its parameters should be updated.