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The design flow of camera-based steering assistance algorithms usually begins with their implementation in floating-point on a PC or workstation. This abstraction from all implementation effects allows an exploration of the algorithm space. Memory, throughput and word-length requirements may not be important issues for offline implementation of the algorithms, but they can become critical issues for real-time implementations on embedded processors. The implementation of driver assistance systems is faced with practical constraints because these algorithms usually need to run in real-time on fixed point digital signal processors (DSPs) to reduce total hardware cost. In this paper we first evaluate numerical requirements for implementation of camera-based lateral position detection algorithms, such as lane keep assistant and lane departure warning. We then present methods that address the challenges and requirements of fixed-point design process. The flow proposed is targeted at converting C/C++ code with floating-point operations into C code with integer operations that can then be fed through the native C compiler for a fixedpoint DSP. We demonstrate the flow on tracking example (extended Kalman filter) using synthetically generated data, and we analyze trade-offs for algorithm implementation in fixed-point arithmetic.