  Current technologies are unable to produce massively deployable, fully
autonomous vehicles that do not require human intervention. Such technological
limitations are projected to persist for decades. Therefore, roadway scenarios
requiring a driver to regain control of a vehicle, and vice versa, will remain
critical to the safe operation of semi-autonomous vehicles for the foreseeable
future. Herein, we adopt a comprehensive perspective on this problem taking
into account the operational design domain, driver and environment monitoring,
trajectory planning, and driver intervention performance assessment. Leveraging
decision analysis and Bayesian forecasting, both the support of driving mode
management decisions and the issuing of early warnings to the driver are
addressed. A statistical modeling framework is created and a suite of
algorithms are developed to manage driving modes and issue relevant warnings in
accordance with the management by exception principle. The efficacy of these
developed methods are then illustrated and examined via a simulated case study.
