The design of automotive electronic systems needs to address a variety of important objectives, including safety, performance, fault tolerance, reliability, security, extensibility, etc. To obtain a feasible design, timing constraints must be satisfied and latencies of certain functional paths should not exceed their deadlines. From functionality perspective, soft errors caused by transient or intermittent faults need to be detected and recovered with fault tolerance techniques. Moreover, during the lifetime of a vehicle design or even the same car, updates are often needed to add new features or fix bugs in existing ones. It is therefore critical to improve the design extensibility for accommodating such updates without incurring major redesign and re-verification cost. In this work, we discuss the metrics for measuring latency, fault tolerance and extensibility, and present a simulated annealing based algorithm to search the design space with respect to them. Experimental results on industrial and synthetic examples demonstrate clear trade-offs among these objectives, and hence the importance of quantitatively analyzing such trade-offs and exploring the design space with automation tools.