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Our ability to produce human-scale biomanufactured organs is limited by inadequate vascularization and perfusion. For arbitrarily complex geometries, designing and printing vasculature capable of adequate perfusion poses a major hurdle. We introduce a model-driven design platform that demonstrates rapid synthetic vascular model generation alongside multifidelity computational fluid dynamics simulations and three-dimensional bioprinting. Key algorithmic advances accelerate vascular generation 230-fold and enable application to arbitrarily complex shapes. We demonstrate that organ-scale vascular network models can be generated and used to computationally vascularize >200 engineered and anatomic models. Synthetic vascular perfusion improves cell viability in fabricated living-tissue constructs. This platform enables the rapid, scalable vascular model generation and fluid physics analysis for biomanufactured tissues that are necessary for future scale-up and production. 

This paper presents ModelMap, a model-based multi-domain application development framework for DriveOS, our in-house centralized vehicle management software system. DriveOS runs on multicore x86 machines and uses hardware virtualization to host isolated RTOS and Linux guest OS sandboxes. In this work, we design Simulink interfaces for model-based vehicle control function development across multiple sandboxed domains in DriveOS. ModelMap provides abstractions to: (1) automatically generate periodic tasks bound to threads in different OS domains, (2) establish cross-domain synchronous and asynchronous communication interfaces, and (3) handle USB-based CAN I/O in Simulink. We introduce the concept of a nested binary, for the deployment of ELF binary executable code in different sandboxed domains. We demonstrate ModelMap using a combination of synthetic benchmarks, and experiments with Simulink models of a CAN Gateway and HVAC service running on an electric car. ModelMap eases the development of applications, which are shown to achieve industry-target performance using a multicore hardware platform in DriveOS. 

Modern automotive systems feature dozens of electronic control units (ECUs) for chassis, body and powertrain functions. These systems are costly and inflexible to upgrade, requiring ever increasing numbers of ECUs to support new features such as advanced driver assistance (ADAS), autonomous technologies, and infotainment. To counter these challenges, we propose DriveOS, a safe, secure, extensible, and timing-predictable system for modern vehicle management in a centralized platform. DriveOS is based on a separation kernel, where timing and safety-critical ECU functions are implemented in a real-time OS (RTOS) alongside non-critical software in Linux or Android. The system enforces the separation, or partitioning, of both software and hardware among different OSes. DriveOS runs on a relatively low-cost embedded PC-class platform, supporting multiple cores and hardware virtualization capabilities. Instrument cluster, in-vehicle infotainment and advanced driver assistance system services are implemented in a Yocto Linux guest, which communicates with critical real-time services via secure shared memory. The RTOS manages a real-time controller area network (CAN) interface that is inaccessible to Linux services except via well-defined and legitimate communication channels. In this work, we integrate three Qt-based services written for Yocto Linux, running in parallel with a real-time longitudinal controller task and multiple CAN bus concentrators, for vehicular sensor data processing and actuation. We demonstrate the benefits and performance of DriveOS with a hardware-in-the-loop CARLA simulation using a real car dataset.