Why Are Self-Driving Cars Taking So Long? | Summary and Q&A

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May 24, 2018
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Why Are Self-Driving Cars Taking So Long?

TL;DR

Self-driving cars face challenges in perception, prediction, and planning, making widespread adoption difficult.

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Questions & Answers

Q: What are some challenges with perceiving the environment for self-driving cars?

Self-driving cars rely on a variety of sensors, but interpreting and separating objects can be difficult, especially in crowded scenarios. Mistaken identities can lead to potentially dangerous situations.

Q: How does prediction play a role in self-driving cars?

Prediction involves understanding the future actions of pedestrians and other drivers. This is challenging as it requires recognizing subtle cues and negotiating in real-time to ensure safety.

Q: What are the two main strategies programmers use for self-driving cars?

One approach is to have the car assume others' actions depend on its own, but this can lead to overly aggressive behavior. Another method is to treat the car as just one more vehicle and make decisions based on the situation.

Q: Are self-driving cars ready for widespread use?

Self-driving cars may be suitable for specific situations without complex scenarios, but there are still significant challenges that need to be overcome before they can be used for general-purpose driving.

Summary & Key Takeaways

  • Self-driving cars are not yet available for general-purpose driving and are currently limited to specific uses like long-haul trucking or taxis on designated streets.

  • The perception stage is crucial for self-driving cars to understand their surroundings, but there are difficulties in separating objects and identifying certain items.

  • Prediction is complex as it involves understanding the intentions of other drivers and negotiating with them for safe navigation.

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