Connected Motorized Riders - A Smart Mobility System to Connect Two and Three-wheelers

The Smart Cities Mission has been launched in India in 2015 to develop 100 cities, with smart mobility being one of the main topics in the mission. As urban areas are flooded with two (motorcycles) and three wheelers (auto-rickshaws), introducing smart control of such vehicles may reduce the congestion on the roads and the number of accidents. Indeed, over-speeding and drunken driving are common traffic violations. In this project we propose an IoT-based smart mobility system which tracks data, such as the vehicle location, vehicle speed, alcohol level of the driver, etc. efficiently over the internet. Our system has been conceived with CPAL, a high-level language meant to simulate and execute Cyber Physical Systems including IoT applications. A prototype running on ARM mbed IoT hardware, shows the feasibility of our concept. We believe that more efficient and interactive traffic management, more disciplined driving behaviors, reduction in accident rate, more controlled pollution, increased passenger safety can be achieved if systems like the one prototyped in this work deployed contributing to smarter cities

A Model-Based Development Environment for Rapid-Prototyping of Latency-Sensitive Automotive Control Software

The innovation in the field of automotive embedded systems has been increasingly relying on software-implemented functions. The control laws of these functions typically assume deterministic sampling rates and constant delays from input to output. However, on the target processors, the execution times of the software will depend on many factors such as the amount of interferences from other tasks, resulting in varying delays from sensing to actuating. Three approaches supported by tools, namely TrueTime, T-Res, and SimEvents, have been developed to facilitate the evaluation of how timing latencies affect control performance. However, these approaches support the simulation of control algorithms, but not their actual implementation. In this paper, we present a model interpretation engine running in a co-simulation environment to study control performances while considering the run-time delays in to account. Introspection features natively available facilitate the implementation of self-adaptive and fault-tolerance strategies to mitigate and compensate the run-time latencies. A DC servo controller is used as a supporting example to illustrate our approach. Experiments on controller tasks with injected delays show that our approach is on par with the existing techniques with respect to simulation. We then discuss the main benefits of our development approach that are the support for rapid-prototyping and the re-use of the simulation model at run-time, resulting in productivity and quality gains

A Model-Driven Co-Design Framework for Fusing Control and Scheduling Viewpoints

Model-Driven Engineering (MDE) is widely applied in the industry to develop new software functions and integrate them into the existing run-time environment of a Cyber-Physical System (CPS). The design of a software component involves designers from various viewpoints such as control theory, software engineering, safety, etc. In practice, while a designer from one discipline focuses on the core aspects of his field (for instance, a control engineer concentrates on designing a stable controller), he neglects or considers less importantly the other engineering aspects (for instance, real-time software engineering or energy efficiency). This may cause some of the functional and non-functional requirements not to be met satisfactorily. In this work, we present a co-design framework based on timing tolerance contract to address such design gaps between control and real-time software engineering. The framework consists of three steps: controller design, verified by jitter margin analysis along with co-simulation, software design verified by a novel schedulability analysis, and the run-time verification by monitoring the execution of the models on target. This framework builds on CPAL (Cyber-Physical Action Language), an MDE design environment based on model-interpretation, which enforces a timing-realistic behavior in simulation through timing and scheduling annotations. The application of our framework is exemplified in the design of an automotive cruise control system

Timing-aware Model Based Design with Application to Automotive Embedded Systems

Cyber-Physical System (CPS) are systems piloting physical processes which have become an integral part of our daily life. We use them for many purposes: transportation (cars, planes, trains), space (satellite, spacecrafts), medical application, robotics, energy management, home appliance, manufacturing, and so many other applications. Model-Driven Engineering (MDE) is widely applied in the industry to develop new software functions and integrate them into the existing run-time environment of a Cyber-Physical System (CPS), for instance, the control software for automotive engines, which are deployed on modern multi-core hardware architectures. Such an engine control system consists of different sub-systems, ranging from an air system to the exhaust system. Each of these sub-systems, again, consists of software functions which are necessary to read from the sensors and write to the actuators. In this setting, MBD provides indispensable means to model and implement the desired functionality, and to validate the functional, the non-functional, and in particular the real-time behavior against the requirements. Current industrial practice in model-based development completely relies on generative MBD, i.e., on code generation to bridge the gap between model and implementation. An alternative approach, although not yet used in the automotive domain is model interpretation. In this thesis, in the place of code generation, we investigate the applicability of model interpretation to automotive software development with a help of a control function design. We present the benefits compared to the existing code-generation practice. The control laws of these software functions typically assume deterministic sampling rates and constant delays from input to output. However, on the target processors, the execution times of the software will depend on many factors such as the amount of interferences from other tasks, resulting in varying delays from sensing to actuating. The literature approaches support the simulation of control algorithms, but not their actual implementation. Further in the thesis, we present the CPAL model interpretation engine running in a co-simulation environment to study control performances while taking the run-time delays into account. The main advantage is that the model developed for simulation can be re-used on the target processors. Additionally, the simulations performed at design phase can be made realistic in the timing dimension through the use of timing annotations inserted in the models to capture the delays on the actual hardware. Introspection features natively available facilitate the implementation of self-adaptive and fault-tolerance strategies to mitigate and compensate the run-time latencies. Experiments on controller tasks with injected delays show that our approach is on-par with the existing techniques with respect to simulation. We then discuss the main benefits of our development approach which are the support for rapid-prototyping and the re-use of the simulation model at run-time, resulting in productivity and quality gains. As the processing power is increasingly available with today's hardware, other concerns than execution performance such as simplicity and predictability become important factors towards functional safety objective. The motivation towards predictable execution behavior, we revisited FIFO scheduling with o set and strictly periodic task activations. The execution order in this case is uniquely and statically determined. This means that whatever the execution platform and the task execution times, be it in simulation mode in a design environment or at run-time on the actual target, the task execution order will remain identical. Beyond the task execution order, the reading and writing events that can be observed outside the tasks occur in the same order. This property, leveraged by our MBD environment CPAL design flow provides a form of timing equivalent behavior between development phase and run-time phase which eases the implementation of the application and the verification of its timing correctness. Thus, the proposed development environment facilitates where also the non-experts are able to quickly model and deploy complex embedded systems without having to master real-time scheduling and resource-sharing protocols. In practice, the design of a software component involves designers from various viewpoints such as control theory, software engineering, safety, etc. In practice, while a designer from one discipline focuses on the core aspects of the field, he / she neglects or considers less importantly the other engineering aspects (for instance, real-time software engineering or energy efficiency). This may cause some of the functional and non-functional requirements not to be met satisfactorily. In the thesis, we present a model-driven co-design framework based on the timing tolerance contract to address such design gaps between control and real-time software engineering. The framework consists of three steps: controller design, verified by jitter margin analysis along with co-simulation, software design veri fied by a novel schedulability analysis, and the run-time verification by monitoring the execution of the models on target. This framework builds on earlier mentioned CPAL design environment, which enforces a timing-realistic behavior in simulation through timing and scheduling annotations. Through various case studies, we show that our tool enables not only to automate the analysis process at design time but also to enhance the design process by systematically combining models and analyses

Poster Abstract: An Optimizing Framework for Real-Time Scheduling

Scheduling is crucial in real-time applications. For any real-time system, the desired scheduling policy can be selected based on the scheduling problem itself and the underlying system constraints. This paper discusses a novel optimization framework which automates the selection and configuration of the scheduling policy. The objective is to let designer state the permissible timing behavior of the system in a declarative manner. The system synthesis step involving both analysis and optimization then generates a scheduling solution which at runtime is enforced by the execution environment

Software Architecture Modeling of AUTOSAR-Based Multi-Core Mixed-Critical Electric Powertrain Controller

In this paper, we present a transition journey of automotive software architecture design from using legacy approaches and toolchains to employing new modeling capabilities in the recent releases of Matlab/Simulink (M/S). We present the seamless approach that we have employed for the software architecture modeling of a mixed-critical electric powertrain controller which runs on a multi-core hardware platform. With our approach, we can achieve bidirectional traceability along with a powerful authoring process, implement a detailed model-based software architecture design of AUTOSAR system including a detailed data dictionary, and carry out umpteen number of proof-of-concept studies, what-if scenario simulations and performance tuning of safety software. In this context, we discuss an industrial case study employing valuable lessons learned, our experience reports providing novel insights and best practices followed