Edge Computing Solutions for Autonomous Vehicles

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Question ^*

Which Edge Computing capabilities are most important for your autonomous vehicle applications?

1. Real-time data processing

2. Low-latency communication

3. Enhanced security features

4. Fault tolerance and redundancy

5. Data privacy and compliance

6. Over-the-air (OTA) updates

7. Other (Please specify)

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Question ^*

How would you prioritize the following Edge Computing deployment models for your autonomous vehicle solutions? (Rank from 1 - Most Important to 5 - Least Important)

1. On-Vehicle Edge (integrated directly into the vehicle)

2. Roadside Edge (deployed along roadways)

3. Cloud-Integrated Edge (hybrid cloud/edge architecture)

4. Local Edge (e.g., at parking garages, charging stations)

5. Private Edge (dedicated infrastructure)

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Question ^*

What level of integration and support do you require from an Edge Computing solutions provider?

1. Basic infrastructure provision

2. Turnkey solution with complete integration

3. Customized solution development and integration

4. Ongoing maintenance and support services

5. Other (Please specify)

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Question ^*

What is your primary focus area regarding autonomous vehicle development?

1. Perception and Sensor Fusion

2. Path Planning and Navigation

3. Vehicle Control and Actuation

4. V2X Communication and Collaboration

5. Simulation and Testing

6. Other (Please specify)

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Question ^*

What are the biggest challenges you face with current autonomous vehicle computing infrastructure?

1. Latency in data processing

2. Limited bandwidth for data transfer

3. High power consumption

4. Security vulnerabilities

5. Lack of real-time capabilities

6. Cost

7. Other (Please specify)

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