  In this paper, we focus on developing driver-in-the loop fuel economic
control strategy for multiple connected vehicles. The control strategy is
considered to work in a driver assistance framework where the controller gives
command to a driver to follow while considering the ability of the driver in
following control commands. Our proposed method uses vehicle-to-vehicle (V2V)
communication, exploits traffic lights' Signal Phase and Timing (SPAT)
information, models driver error injection with Markov chain, and employs
scenario tree based stochastic model predictive control to improve vehicle fuel
economy and traffic mobility. The proposed strategy is decentralized in nature
as every vehicle evaluates its own strategy using only local information.
Simulation results show the effect of consideration of driver error injection
when synthesizing fuel economic controllers in a driver assistance fashion.
