As the technology matures, self-driving car makers are all jockeying to figure out how many sensors, which sensors, and which combination of sensors make sense for a self-driving car. More sensors, more data, more to process, more cost of hardware. Less sensors, less data, less to process, lower cost of hardware. And of course, without compromising safety!
What are the various options available and what does the future hold?
Learn more about this important to the automotive issue, with this exclusive report written by Automotive IQ on the topic of: "Intelligent Sensor Fusion for Smart Cars".
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Engineers have been installing the building blocks for modern autonomous vehicles since the 1980s. Now, as engineers tie these components together, along with lidar, radar and highdefinition mapping, the car is basically becoming a thinking machine that is aware of its place in the world.
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The presentation covers the following:
- Assisted driving on the way to semi-autonomous driving: Accuracy, consistency, partitioning, security, evidence
- Market demands: Scalability, operational availability, worldwide availability
- Business models: Data and service quality pushes business value
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What is the Apollo project and who is involved? What part of Apollo is open source and how can one participate in it? What kind of license does it adopt? What is the roadmap for Apollo?
Expand your knowledge within this area, with this exclusive free interview with Wesley Shao, Principal Architect at Baidu Inc. in the USA on the topic of the Apollo project.
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One of the main questions in the self-driving car industry currently discussed is whether: “deep learning really the solution for everything?” How is deep learning used and what are its advantages? What are the shortcomings and challenges of deep learning?
Expand your knowledge on this area, with this exclusive report, written by Automotive IQ on the topic of "Deep Learning Really The Solution for Everything in Self-Driving Cars?".
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