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An efficient development environments such as Software-in-the-Loop Simulation (SILS) and Rapid Control Prototyping (RCP) have been widely used to reduce the development time and cost of real-time ECUs. However, conventional SILS does not consider temporal behaviors caused by computation time, task scheduling, network-induced delays, and so on. As a result, the control performance of ECU is likely to be degraded after implementation. To overcome this problem, SILS/RCP which considers the temporal behaviors was suggested in the previous research. In this study, we validated the proposed SILS/RCP environments which are used to design an Electronic Stability Control (ESC) system which is one of the hard real-time control systems. The proposed SILS/RCP environments make it possible to realize ECUs in the early design phase by considering temporal behaviors.

FlexRay is a deterministic and fault-tolerant in-vehicle network(IVN) protocol. It is expected to become a practical standard for automotive communication systems. According to the FlexRay protocol specifications, there are about 60 configurable parameters which should be determined in the design phases. The parameters increase the complexities of FlexRay-based control system development. In this study, we are suggesting a formal design process for FlexRay-based control systems, which is focused on network parameter optimization. We introduce design phases from functional system models to implementations. These phases present formal ways for task allocation, node assignment, network configuration, and implementations. In the network configuration phase, two FlexRay core parameters are selected to optimize network design. Optimal methods of the core parameters provide concise guide lines for optimal communication cycle length and optimal static slot length.

Electromechanical relays that are coupled with fuses have been used for controlling electrical loads in vehicles. In the past decade, semiconductor power switches have been developed for overcoming the physical limits of relays and fuses. Semiconductor power switches can not only replace relays and fuses but can also improve a system's reliability and efficiency. In this study, we introduce the Smart Automotive Switch (SAS), which is a smart high side power switch of Fairchild Korea semiconductor. Functional capabilities, such as power switching, protection and self-diagnosis of SASs are presented in case studies involving, for example, headlights, glow plugs, and fuel pump control systems. Through these experimental studies, the suitability of SASs is validated for designing improved automotive electronic control systems.

This paper presents a preliminary study of a sampling period decision for robust control of a distributed control system based on an in-vehicle network with three types of data (real-time synchronous data, real-time asynchronous data, and nonreal-time asynchronous data). The architecture of automotive systems is currently changing from a number of standalone electronic control units (ECUs) to a functionally integrated distributed system which is linked by a network. The control performance of the integrated networked control system can be changed by the characteristics of time delays among the application ECUs. A basic parameter for a scheduling method of the networked control systems, a maximum allowable delay bound is used, which guarantees stability of the networked control system, and it is derived from the characteristics of the given plant using presented theorems.

This paper presents the Matlab/Simulink-based Software-in-the-Loop Simulation (SILS) tool which is the co-simulator for temporal and functional simulations of control systems. The temporal behavior of a control system is mainly dependent on the implemented software and hardware such as the real-time operating system, target CPU and communication protocol. In this research, the SILS components with temporal attributes are specified as tasks, task executions, real-time schedulers, and real-time networks. Methods for realizing these components in graphical block representations are investigated with Matlab/Simulink, which is the most commonly used tool for designing and simulating control algorithms in control engineering. These components are modeled in graphical blocks of Matlab/Simulink.

In the extremely cost-sensitive and competitive automotive industry, manufacturers and suppliers are constantly searching for means to reduce both time-to-market and development costs. As a kind of solution to satisfy these requirements, Rapid-control prototyping (RCP) has established itself as viable technology, albeit not everywhere yet. One big gap in the development process, however, is the transfer form RCP to a target implementation with all its limitations. This paper presents a new RCP platform, which aims to provide a consistent environment both at the RCP step and at the target code implementation step. To achieve this goal, the proposed prototyping system is designed very similar to the real production ECU as much as possible, and it supports all the features, which are needed in the RCP.

An evidential theory is widely used for 2D grid-based localization in a robotics field because the theory has benefits to consider additional states such as 'unknown' and 'conflict'. However, there are some problems such as computational limitation and excessive resource share when the localization system is expanded from 2D grid to 3D voxel. In order to overcome the problems, this paper proposes the parallelized particle filter based localization system using 3D evidential voxel maps. A many-core processor based parallel computing framework with optimization techniques is applied to accelerate the computing power. Experiments were performed to evaluate the performance of the localization system in a complex environment, and to compare the computational time and resources between various types of processing units. The experimental results show that the proposed parallel particle filter is much more efficient than particle filter without parallel computing regarding computational cost.

Human drivers navigate by continuously predicting the intent of road users and interacting with them. For safe autonomous driving, research about predicting future trajectory of vehicles and motion planning based on these predictions has drawn attention in recent years. Most of these studies, however, did not take into account driver’s intentions or any interdependence with other vehicles. In order to drive safely in real complex driving situations, it is essential to plan a path based on other driver’s intentions and simultaneously to estimate the intentions of other road user with different characteristics as human drivers do. We aim to tackle the above challenges on highway merge scenario where the intention of other road users should be understood. In this study, we propose an intention aware motion planning method using finite state machine and model predictive control without any vehicle-to-vehicle (V2V) or vehicle-to-infrastructure (V2I) communications.