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The Road to Autonomous Driving Transforming Vision into Reality Page 6 TE AUTOMOTIVE /// Trend Paper | The Road to Autonomous Driving There are six key enablers to meeting these challenges: Architecture New vehicles soon will have architectures that organize high-performance clusters in functional domains, as seen below in Figure 2. These domains are connected hierarchically via a central gateway in a high- speed data backbone structure and group sensors and actuators. Autonomous driving will increasingly demand more and more reliable network-based structures, requiring redundant, real-time architectures. High-Speed Data High-performance computers and an increasing number of ADAS sensors, such as high-res- olution stereo and/or mono cam- eras, RADAR, and LIDAR; as well as future human-machine inter- faces (HMIs), such as large 4K/ 8K screens or head-up displays (HUDs), will multiply the number of high-speed data nodes. The increase in nodes will lead to growing net data payloads for each link which will vary depending on the data through- put requirements of each node. In addition, multiple parallel and bidirectional data streams will need to be managed in switched net- works while providing sufficient safety margin. Manufacturers should therefore plan on designing flexible architectures that accommodate continuously increasing bandwidths for point-to-point data pipes and distributed network structures.TE anticipates that by 2020, in-vehicle connectivity will require data rates far beyond 12Gbps. External Connectivity As previously mentioned, a key requirement of autonomous driving is the ability to capture correct and complete data about the surrounding environment. For example, a vehicle autopilot could only execute actions such as braking or accelerating correctly when all necessary information about the vehicle sur- roundings is available. In addition to sensor technology, which determines the vehicle's immediate sur- roundings, additional information from beyond the driver's field of vision is required. V2X (Vehicle-to-Everything) communication relies on radio-based exchange of information between vehicles and between the vehicle and traffic infrastructure such as lights, signs, and tolls. Instead of the vehicle attempting to identify the surroundings, sensors around the car communicate their state. It is therefore possible, at an early stage, for an autonomous car to detect dangerous traffic situations such as stationary vehicles at the back of a traffic jam or approaching rescue vehicles and initiate appropriate countermeasures. A crucial prerequisite for safe autonomous driving is the real-time transmission of data. Only then it is possible for the driver or autopilot to respond to potential hazards in time. Current cellular radio stan- dards such as LTE have a latency of 30 to 40 milliseconds. As a consequence, they are not sufficient to support this requirement. For fully autonomous driving, developers are focusing on the next generation mobile communications - 5G and beyond. 5G will be characterized by higher data rates of up to 10 Gbps and considerably lower latency. 5G is expected to be available for deployment starting in 2019. Figure 2: Potential system architecture for connected vehicles

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