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Trajectory Planning for Mission Survivability of Autonomous Vehicles in Moderately to Extremely Uncertain Environments

Paper ID

ATM-2021-017

Conference

USA/Europe ATM R&D Seminar

Year

2021

Theme

Trajectory planning

Project Name

Keywords:

mission robustness, mission survivability, non-cooperative traffic, non-modeled uncertainty, trajectory flexibility, unknown disturbances, urban air mobility

Authors

Fanruiqi Zeng, Husni R. Idris and John-Paul Clarke

DOI

Project Number

Abstract

Trajectory planning is a particularly challenging task for autonomous vehicles when there are moderate to extreme uncertainties in their operating environment, i.e., where the trajectories of hazards are partially known to completely unknown. In this paper, we propose a receding horizon control strategy with novel trajectory planning policies that enable dynamic updating of the planned trajectories of autonomous vehicles. The proposed policies utilize two metrics: (1) the number of feasible trajectories; and (2) the robustness of the feasible trajectories. We measure the effectiveness of the suggested policies in terms of mission survivability, which is defined as the probability that the primary mission is accomplished or, if that is not possible, the vehicle lands safely at an alternative site. We show that a linear combination of both metrics is an effective objective function when there is a mix of partially known and unknown uncertainties. When the operating environment is dominated by unknown disturbances, maximizing the number of feasible trajectories results in the highest mission survivability. These findings have significant implications for achieving safe aviation autonomy.