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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Nikolic, Z. |
| Copyright Year | 2008 |
| Description | Author affiliation: DSP Vision Syst. Group, Texas Instrum. Inc., Stafford, TX (Nikolic, Z.) |
| Abstract | 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. |
| Starting Page | 697 |
| Ending Page | 702 |
| File Size | 242844 |
| Page Count | 6 |
| File Format | |
| ISBN | 9781424425686 |
| ISSN | 19310587 |
| DOI | 10.1109/IVS.2008.4621140 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2008-06-04 |
| Publisher Place | Netherlands |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Vehicles |
| Content Type | Text |
| Resource Type | Article |
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