New-Tech Europe Digital Magazine | Feb 2016

Who’s the Better Decision-Maker: Self- Driving Car or Human?

Christine Young, Cadence

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ill self-driving cars be able to react better than a person can

of the equation. Just as important are the sophisticated algorithms that bring intelligence to the aggregated data and the DSPs to do all of the processing. At Cadence, there’s a team of engineers in the IP Group that spends its time defining and developing such algorithms and DSPs for ADAS and communications applications. Recently, I had the opportunity to chat with two of the team members: Pierre- Xavier Thomas, design engineering group director, whose team develops software product collateral for Cadence Tensilica DSPs, such as DSP libraries, application use cases, and software signal processing example kernels; and Pushkar Patwardhan, design engineering architect. Aggregating Data: in the Cloud or in the Car? Now, while advances in algorithms

and DSP and sensor technology have been impressive, the act of aggregating and then extracting useful insights from collected data remains a work in progress. According to Patwardhan, who leads development in radar algorithms, automotive electronics engineers are trying various approaches. “One of the main challenges for ADAS functions is to decide how to distribute the processing and data aggregation between the vehicle and the cloud,” he said. “In one school of thought, more data aggregation and processing are done in the vehicle, with lesser data communications overhead. Another approach is a more cloud-centric mechanism, with the vehicle requiring more communications with the cloud to obtain information about the environment, with lesser processing done within the vehicle itself. It’s not clear yet which approach is a winner.”

when something unforeseen happens on the road? That’s just one of many questions that auto manufacturers and the electronics industry will need to address in the coming years. Sensors are essential technology for making it possible for vehicles to act independently. Automakers are now integrating into their systems a variety of key sensor types: LiDAR for generating 3D maps of the environment, sonar for short- range sensing, cameras for short-/ mid-range sensing, and radar for mid-/long-range sensing. For many advanced driver assistance systems (ADAS) functions, decisions are made by fusing or aggregating data from multiple sensors. For instance, an obstacle or pedestrian detection function will typically fuse data from cameras as well as radar sensors. But, of course, sensors are only a part

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