Integral image computation algorithm for GPUenabled automotive platforms Nowadays, automotive industry is shapeshifting towards utilization of solutions in which software and algorithms are the dominant concern. Autonomous driving functions require processingintensive decision algorithms which involve a lot of image manipulation software techniques. CPUs cannot meet such a demand; therefore, hardware acceleration again becomes mandatory in any design. GPUs have become great candidates for image processing in automotive algorithms, due to large number of cores. However, efficient porting of traditional image processing algorithms to GPUs is still a challenge. In this paper, we present an improvement of integral image computation on the GPU in an automotive context. The main benefit of the proposed improvement is reduced computational complexity and consequently speedup of execution time. Therefore, frame rate in an image processing algorithm is increased, which is necessary in modern automotive industry. Furthermore, we address specific challenges such as data dependency, resolution and optimization of arithmetic. Finally, we evaluate the approach utilizing NVIDIA CUDA for a Xavierbased automotive electronic control unit.

Development Environment Proposal for Automotive VisionBased Algorithms Next generation autonomous driving functions heavily depend on various computationally intensive algorithms based on machine vision. Design and development of such algorithms is challenging, requiring engagement of a wider community and the availability of appropriate, costeffective tooling. Setting up a hardware and software environment that would both reflect actual automotive requirements and facilitate development and prototyping, is an uneasy task. In this paper, we analyze the available development platforms which could be utilized in automotive machine vision, with specific regard to new algorithm requirements, such as the utilization of AI, hardware acceleration and low latency. We give a proposal of an affordable and scalable development setup consisting of heterogeneous, visionenabled SoCs and automotive interfaces.