Abstract: Methods and apparatus relating to heterogeneous compute architecture hardware/software co-design for autonomous driving are described. In one embodiment, a heterogeneous compute architecture for autonomous driving systems (also interchangeably referred to herein as Heterogeneous Compute Architecture or “HCA” for short) integrates scalable heterogeneous processors, flexible networking, benchmarking tools, etc. to enable (e.g., system-level) designers to perform hardware and software co-design. With HCA system engineers can rapidly architect, benchmark, and/or evolve vehicle system architectures for autonomous driving. Other embodiments are also disclosed and claimed.

Abstract: Systems and techniques for simulated vehicle operation modeling with real vehicle profiles are described herein. In an example, a simulated vehicle modeling system is adapted to obtain a vehicle performance fingerprint, such as from a vehicle performance fingerprint that includes vehicle performance data collected from a unique vehicle while experiencing real world driving conditions. The simulated vehicle modeling system may be further adapted to present, in a driving simulator, a simulated driving experience with a simulated vehicle, such as for a simulated vehicle that is constructed based on the vehicle performance fingerprint. The simulated vehicle modeling system may be further adapted to update a set of driving directives for an autonomous vehicle based on the simulated driving experience and upload the set of driving directive to an autonomous vehicle.

Abstract: Methods and apparatus relating to heterogeneous compute architecture hardware/software co-design for autonomous driving are described. In one embodiment, a heterogeneous compute architecture for autonomous driving systems (also interchangeably referred to herein as Heterogeneous Compute Architecture or “HCA” for short) integrates scalable heterogeneous processors, flexible networking, benchmarking tools, etc. to enable (e.g., system-level) designers to perform hardware and software co-design. With HCA system engineers can rapidly architect, benchmark, and/or evolve vehicle system architectures for autonomous driving. Other embodiments are also disclosed and claimed.

Abstract: In one example a system for emotional adaptive driving policies for automated driving vehicles, comprising a first plurality of sensors to detect environmental information relating to at least one passenger in a vehicle and a controller communicatively coupled to the plurality of sensors and comprising processing circuitry, to receive the environmental information from the first plurality of sensors, determine, from the environmental information, an emotional state of the at least one passenger, and implement a driving policy based at least in part on the emotional state of the at least one passenger. Other examples may be described.

Abstract: Systems and techniques for simulated vehicle modeling with real vehicle profiles are described herein. In an example, a simulated vehicle modeling system is adapted to obtain a vehicle performance fingerprint, such as from a vehicle performance fingerprint that includes vehicle performance data collected from a unique vehicle while experiencing real world driving conditions. The simulated vehicle modeling system may be further adapted to present, in a driving simulator, a simulated driving experience with a simulated vehicle, such as for a simulated vehicle that is constructed based on the vehicle performance fingerprint. The simulated vehicle modeling system may be further adapted to update a set of driving directives for an autonomous vehicle based on the simulated driving experience and upload the set of driving directive to an autonomous vehicle.

Abstract: Systems and methods for detecting rogue vehicles within a plurality of vehicles connected via a vehicular ad-hoc network (VANET) are provided. Sensors on each VANET vehicle provide host vehicle data and data associated with other nearby vehicles. Each VANET vehicle multicasts information that includes location, velocity, and preferred future travel path to the other VANET vehicles. Using data from sensors and data received from other VANET vehicles the host vehicle generates a dynamic set of safe vehicle operating behaviors. Nearby vehicles that do not comply with the determined safe vehicle operating behaviors or perform illegal/unsafe acts are identified as rogue vehicles. Data associated with identified rogue vehicles is transmitted to all VANET vehicles.

Abstract: Systems and techniques for simulated vehicle modeling with real vehicle profiles are described herein. In an example, a simulated vehicle modeling system is adapted to obtain a vehicle performance fingerprint, such as from a vehicle performance fingerprint that includes vehicle performance data collected from a unique vehicle while experiencing real world driving conditions. The simulated vehicle modeling system may be further adapted to present, in a driving simulator, a simulated driving experience with a simulated vehicle, such as for a simulated vehicle that is constructed based on the vehicle performance fingerprint. The simulated vehicle modeling system may be further adapted to update a set of driving directives for an autonomous vehicle based on the simulated driving experience and upload the set of driving directive to an autonomous vehicle.

Abstract: Systems and methods for detecting rogue vehicles within a plurality of vehicles connected via a vehicular ad-hoc network (VANET) are provided. Sensors on each VANET vehicle provide host vehicle data and data associated with other nearby vehicles. Each VANET vehicle multicasts information that includes location, velocity, and preferred future travel path to the other VANET vehicles. Using data from sensors and data received from other VANET vehicles the host vehicle generates a dynamic set of safe vehicle operating behaviors. Nearby vehicles that do not comply with the determined safe vehicle operating behaviors or perform illegal/unsafe acts are identified as rogue vehicles. Data associated with identified rogue vehicles is transmitted to all VANET vehicles.

Abstract: Methods and apparatus relating to heterogeneous compute architecture hardware/software co-design for autonomous driving are described. In one embodiment, a heterogeneous compute architecture for autonomous driving systems (also interchangeably referred to herein as Heterogeneous Compute Architecture or “HCA” for short) integrates scalable heterogeneous processors, flexible networking, benchmarking tools, etc. to enable (e.g., system-level) designers to perform hardware and software co-design. With HCA system engineers can rapidly architect, benchmark, and/or evolve vehicle system architectures for autonomous driving. Other embodiments are also disclosed and claimed.

Abstract: In one example a system for emotional adaptive driving policies for automated driving vehicles, comprising a first plurality of sensors to detect environmental information relating to at least one passenger in a vehicle and a controller communicatively coupled to the plurality of sensors and comprising processing circuitry, to receive the environmental information from the first plurality of sensors, determine, from the environmental information, an emotional state of the at least one passenger, and implement a driving policy based at least in part on the emotional state of the at least one passenger. Other examples may be described.