  The complexity is increasing rapidly in many areas of the automotive
industry. The design of an automobile involves many different engineering
disciplines, e. g., mechanical, electrical, and software engineering. The
software of a vehicle comprises millions of lines of code. Further, the
manufacturing, logistics, distribution, and sales of a vehicle are highly
complex. There is an immense need for solving simulation problems, e. g., in
battery chemistry, an essential enabler for technological advancements for
electric vehicles. In all these domains, myriads of optimization, simulation,
and machine learning problems arise. Quantum computing-based approaches promise
to overcome some of the inherent scalability limitations of classical
approaches. This article investigates quantum computing applications across the
automotive value chain and identifies several high-value problems that will
benefit from quantum-enhanced solutions.
