DASA:an open-source design, analysis and simulation framework for automotive image-based control systems

Image-Based Control (IBC) systems are a class of data-intensive feedback control systems whose feedback is provided by image-based sensing using a camera. IBC has become popular with the advent of efficient image processing systems and low-cost CMOS cameras with high resolution. The combination of the camera and image processing (sensing) gives necessary information on parameters such as relative position, geometry, relative distance, depth perception and tracking of the object-of-interest. This enables the effective use of low-cost camera sensors to enable new functionality or replace expensive sensors in cost-sensitive industries like automotive.The state-of-the-art design, analysis, and simulation of IBC assumes that the sensing algorithm is executing correctly with an assumed or estimated worst-case delay. The sensing algorithm is simulated and validated using static pre-captured image streams and is normally decoupled from the control algorithm. However, in reality, the camera is fixed to the vehicle body and any steering change would affect the region captured by the image. This dynamism cannot be captured in a static image stream and a dynamic image stream that considers the change in vehicle dynamics due to IBC actuation is needed.We present an open-source design, analysis, and simulation framework for automotive IBC systems that can consider the change in vehicle dynamics in real-time and produces real-time dynamic image stream as per the control algorithm. Our framework models the 3D environment in 3ds Max, simulates the vehicle dynamics, camera position, environment and traffic in V-REP and computes the control output in Matlab. Our framework runs Matlab as a server and V-REP as a client in synchronous mode. We show the effectiveness of our framework using a vision-based lateral control system.<br/

Re-engineering cyber-physical control applications for hybrid communication protocols

In this paper, we consider a cyber-physical architecture where multiple control applications are divided into multiple tasks, spatially distributed over various processing units that communicate over a bus implementing a hybrid communication protocol, i.e., a protocol with both time-triggered and event-triggered communication schedules (e.g., FlexRay). In spite of efficient utilization of communication bandwidth (BW), event-triggered protocols suffer from unpredictable temporal behavior, which is exactly the opposite in the case of their time-triggered counterparts. In the context of communication delays experienced by the control-related messages exchanged over the shared communication bus, we observe that a distributed control application is more prone to performance deterioration in transient phases compared to in the steady-state. We exploit this observation to re-engineer control applications to operate in two modes, in order to optimally exploit the bi-modal (time- and event-triggered) characteristics of the underlying communication medium. Depending on the state (transient or steady) of the system, both, the control inputs and the communication schedule are now switched. Using a FlexRay-based case study, we show that such a design provides a good trade-off between control performance and bus utilization

Co-design of cyber-physical systems via controllers with flexible delay constraints

In this paper, we consider a cyber-physical architecture where control applications are divided into multiple tasks, spatially distributed over various processing units that communicate via a shared bus. While control signals are exchanged over the communication bus, they have to wait for bus access and therefore experience a delay. We propose certain (co-)design guidelines for (i) the communication schedule, and (ii) the controller, such that stability of the control applications is guaranteed for more flexible communication delay constraints than what has been studied before. We illustrate the applicability of our design approach using the FlexRay dynamic segment as the communication medium for the processing units

Relaxing signal delay constraints in distributed embedded controllers

Embedded systems often involve transmitting feedback signals between multiple control tasks that are implemented on different electronic control units communicating via a shared bus. For ensuring stability and control performance, such designs require all control signals to be delivered within a specified deadline, which is ensured through appropriate timing or schedulability analysis. In this brief, we study controller design that allows control feedback signals to occasionally miss their deadlines. In particular, we provide analytical bounds on deadline misses such that the control loop retains its stability and meets its control performance requirements. We argue that such relaxation allows us to 1) use lower quality communication resources (e.g., event-triggered instead of time-triggered communication) and 2) provide more flexibility-e.g., use simulation-in communication timing analysis since analytical worst-case delay bounds for real-life communication protocols are often pessimistic. We illustrate this approach using the FlexRay communication protocol for distributed automotive control systems

Evaluation platform of platoon control algorithms in complex communication scenarios

Cooperative Adaptive Cruise Control (CACC) extends the Adaptive Cruise Control technology with additional information exchange between vehicles over vehicle-to-everything (V2X) communications in an ad-hoc network at 5.9 GHz band (ITS-G5) in Europe. Using beyond line-of-sight information provided by V2X, the platoon control algorithms realize a shorter safe inter-vehicle distance. Nevertheless, the platoon performance (e.g., the allowable inter-vehicle distance) may be impacted by the imperfectness of wireless communications. Specifically, in congested traffic scenarios, a Decentralized Congestion Control method that regulates message rate based on congestion level (Transmit Rate Control (TRC)), may significantly reduce the platoon performance. In this work, we propose an evaluation platform for platoon control algorithms based on industrial V2X nodes operating in the ITS-G5 channels. The real car is simulated by a longitudinal vehicle dynamic model. The model-in-the-loop test results demonstrate that the performance of CACC goes down significantly when the message rate is restricted and reduced by TRC. Our evaluation results further conclude that the effect of such complex communication scenarios imposed by the existing standards should be explicitly modelled in the future platoon control algorithms

Time-triggered implementations of mixed-criticality automotive software

We present an automatic schedule synthesis framework for applications that are mapped onto distributed time-triggered automotive platforms where multiple Electronic Control Units (ECUs) are synchronized over a FlexRay bus. We classify applications into two categories (i) safety-critical control applications with stability and performance constraints, and (ii) time-critical applications with only deadline constraints. Our proposed framework can handle such mixed constraints arising from timing, control stability, and performance requirements. In particular, we synthesize schedules that optimize control performance and respects the timing requirements of the real-time applications. An Integer Linear Programming (ILP) problem is formulated by modeling the ECU and bus schedules as a set of constraints for optimizing both linear or quadratic control performance functions

Robust co-synthesis of embedded control systems with occasional deadline misses

\u3cp\u3eFeedback control applications are robust to occasional deadline misses. This opens up the possibility of saving scarce (computation and communication) resources on embedded platforms. Stability and performance requirements of a control loop impose restrictions on acceptable patterns of deadline misses (e.g., not too many misses in a row). Such requirements are captured by (m,k)-firmness conditions. That is, at least m control computation jobs must meet deadlines in any k consecutive jobs. (m,k)-firm design requires (i) representation of stability and performance requirements in terms of (m,k)-firm deadlines (ii) controller synthesis taking into account the (m,k)-firmness parameters (iii) schedule analysis to verify guarantees on meeting the firmness conditions. We present a co-synthesis framework for these three design components and illustrate its applicability with examples.\u3c/p\u3

QoC-oriented efficient schedule synthesis for mixed-criticality cyber-physical systems

Cyber-physical systems (CPS) are characterized by a tight interaction between computational resources and physical systems. Such systems typically consist of a mix of time-critical real-time tasks and safety-critical control tasks. Time-critical applications are normally associated with hard real-time constraints which need to be guaranteed by the system. On the other hand, control applications are not strictly related to deadlines but rather to quality of control (QoC). Traditional scheduling policies such as Deadline Monotonic can guarantee timing constraints, however, they do not allow for QoC optimized schedules. Optimizing overall QoC while guaranteeing all deadlines constitutes a challenging scheduling problem which is increasingly attracting attention. In this paper, we present an efficient schedule synthesis algorithm for such mixed-criticality systems. The proposed algorithm has a polynomial complexity and ensures all hard real-time constraints while maximizing overall QoC for all control applications

DASA:an open-source design, analysis and simulation framework for automotive image-based control systems

Image-Based Control (IBC) systems are a class of data-intensive feedback control systems whose feedback is provided by image-based sensing using a camera. IBC has become popular with the advent of efficient image processing systems and low-cost CMOS cameras with high resolution. The combination of the camera and image processing (sensing) gives necessary information on parameters such as relative position, geometry, relative distance, depth perception and tracking of the object-of-interest. This enables the effective use of low-cost camera sensors to enable new functionality or replace expensive sensors in cost-sensitive industries like automotive.\u3cbr/\u3e\u3cbr/\u3eThe state-of-the-art design, analysis, and simulation of IBC assumes that the sensing algorithm is executing correctly with an assumed or estimated worst-case delay. The sensing algorithm is simulated and validated using static pre-captured image streams and is normally decoupled from the control algorithm. However, in reality, the camera is fixed to the vehicle body and any steering change would affect the region captured by the image. This dynamism cannot be captured in a static image stream and a dynamic image stream that considers the change in vehicle dynamics due to IBC actuation is needed.\u3cbr/\u3e\u3cbr/\u3eWe present an open-source design, analysis, and simulation framework for automotive IBC systems that can consider the change in vehicle dynamics in real-time and produces real-time dynamic image stream as per the control algorithm. Our framework models the 3D environment in 3ds Max, simulates the vehicle dynamics, camera position, environment and traffic in V-REP and computes the control output in Matlab. Our framework runs Matlab as a server and V-REP as a client in synchronous mode. We show the effectiveness of our framework using a vision-based lateral control system.\u3cbr/\u3