Systematic trade-off strategies for balancing survivability and mobility in vehicle design

Over the last decade, the systems engineering research community has spent significant effort targeting improvements in approaches for designers interested in trading between multiple competing objectives, such as mobility and survivability. Methods such as set-based design and tradespace exploration now leverage advanced optimization and analysis techniques, reducing computational and cognitive burdens on designers and analysts, while enabling the consideration of large potential design spaces. Making sense of the resulting large datasets is made possible through targeted use of abstraction, analysis, and automation. The degree of automation that can and should be leveraged when making tradeoffs varies based on the nature of uncertainties facing a given case. Acknowledging the power of an adaptive capability, instead of using a one-size fits all automated tradeoff approach, we propose an approach that can be tailored across an automation spectrum. Such tailoring allows for discovery of the impact different methods for combining and trading metrics have on the recommendation of best designs. Our proposed approach and tool, the Tailorable Tradespace Analysis of Mobility and Survivability for Ground Vehicles (TTAMS-GV), will provide new insights to ground vehicle designers that are robust to variations in mission needs, technologies, and priorities, common uncertainties faced during early design decision-making.