SHPbench – a smart hybrid prototyping based environment for early testing, verification and (user based) validation of advanced driver assistant systems of cars

Statistical analysis show that more than 90 percent of all car accidents result from human mistakes. Advanced Driver Assistant Systems (ADAS) are intended to support and assist the car driver, and therefore contribute significantly to the reduction of accidents. ADAS become more and more complex and demanding regarding hard- and software fulfilling the requirements applied onto assistant systems nowadays and in the future. They have to be considered as multi-functional multi-domain mechatronic systems. Smart Hybrid Prototyping (SHP) is a by now proven approach for handling ADAS’ demands during and to the development process, specifically for early integrated component and system testing, its verification and validation with the focus on the interaction with the driver can only be reasonably and economically met by utilizing the SHP technology. For those mentioned purposes the SHPbench, an integrated development and validation environment, has been recently developed. The SHPbench's architecture and specification is presented and evaluated by applying a representative use case of an ADAS development process. This paper documents the use case setup, process steps and test results

A new model-free design for vehicle control and its validation through an advanced simulation platform

A new model-free setting and the corresponding "intelligent" P and PD controllers are employed for the longitudinal and lateral motions of a vehicle. This new approach has been developed and used in order to ensure simultaneously a best profile tracking for the longitudinal and lateral behaviors. The longitudinal speed and the derivative of the lateral deviation, on one hand, the driving/braking torque and the steering angle, on the other hand, are respectively the output and the input variables. Let us emphasize that a "good" mathematical modeling, which is quite difficult, if not impossible to obtain, is not needed for such a design. An important part of this publication is focused on the presentation of simulation results with actual and virtual data. The actual data, used in Matlab as reference trajectories, have been obtained from a properly instrumented car (Peugeot 406). Other virtual sets of data have been generated through the interconnected platform SiVIC/RTMaps. It is a dedicated virtual simulation platform for prototyping and validation of advanced driving assistance systems. Keywords- Longitudinal and lateral vehicle control, model-free control, intelligent P controller (i-P controller), algebraic estimation, ADAS (Advanced Driving Assistance Systems).Comment: in 14th European Control Conference, Jul 2015, Linz, Austria. 201

A Hardware-in-the-Loop Facility for Integrated Vehicle Dynamics Control System Design and Validation

Due to the increased number and the complexity of the embedded systems in today’s vehicle, there is ever increasing pressure to reduce the development cost and time to market of such systems. In recent years, Model based Development (MBD) is becoming a main stream in the development of automotive embedded systems, and Hardware-in-the-Loop (HiL) testing is one of the key steps toward the implementation of MBD approach. This paper presents the recent HiL facility that has been developed at Cranfield University. The HiL setup includes real steering and brake smart actuator, high fidelity validated vehicle model, complete rapid control prototyping tool chain, and driver-in-the-loop capability. The applications of HiL setup are including but not limited to: smart actuators system identification; rapid control development and early validation of standalone and/or integrated vehicle dynamics control systems. Furthermore, the facility can be employed for investigation on driver-vehicle interaction at the presence of standalone active steering and/or brake systems as well as various Advanced Driver Assist Systems (ADAS), such as lane keeping or adaptive cruise control systems. The capability of the HiL facility for validation of a several newly developed vehicle dynamics control systems is presente

Towards a Common Software/Hardware Methodology for Future Advanced Driver Assistance Systems

The European research project DESERVE (DEvelopment platform for Safe and Efficient dRiVE, 2012-2015) had the aim of designing and developing a platform tool to cope with the continuously increasing complexity and the simultaneous need to reduce cost for future embedded Advanced Driver Assistance Systems (ADAS). For this purpose, the DESERVE platform profits from cross-domain software reuse, standardization of automotive software component interfaces, and easy but safety-compliant integration of heterogeneous modules. This enables the development of a new generation of ADAS applications, which challengingly combine different functions, sensors, actuators, hardware platforms, and Human Machine Interfaces (HMI). This book presents the different results of the DESERVE project concerning the ADAS development platform, test case functions, and validation and evaluation of different approaches. The reader is invited to substantiate the content of this book with the deliverables published during the DESERVE project. Technical topics discussed in this book include:Modern ADAS development platforms;Design space exploration;Driving modelling;Video-based and Radar-based ADAS functions;HMI for ADAS;Vehicle-hardware-in-the-loop validation system

Radar Target Simulation for Vehicle-in-the-Loop Testing

Automotive radar sensors play a vital role in the current development of autonomous driving. Their ability to detect objects even under adverse conditions makes them indispensable for environment-sensing tasks in autonomous vehicles. As their functional operation must be validated in-place, a fully integrated test system is required. Radar Target Simulators (RTS) are capable of executing end-of-line, over-the-air validation tests by looping back a received and afterward modified radar signal and have been incorporated into existing Vehicle-in-the-Loop (ViL) test beds before. However, the currently available ViL test beds and the RTS systems that they consist of lack the ability to generate authentic radar echoes with respect to their complexity. The paper at hand reviews the current development stage of the research as well as commercial ViL and RTS systems. Furthermore, the concept and implementation of a new test setup for the rapid prototyping and validation of ADAS functions is presented. This represents the first-ever integrated radar validation test system to comprise multiple angle-resolved radar target channels, each capable of generating multiple radar echoes. A measurement campaign that supports this claim has been conducted

MINARGUS: Test tool for User Experience measurement and parameter modification within ADAS simulation

Advanced Driver Assistance Systems play a leading role in the revolution of vehicles; it has become a high priority for automotive industry and meanwhile is used in all automotive segments. In this paper, a tool is introduced, which allows capturing User Experience (UX) on the Model-in-the-Loop level (where only abstract models exist): MINARGUS. This solution allows direct feedback to other partners in the development process and, hence, allows a more efficient work relationship between system development engineers and test & validation engineers. The tool allows a connection between a simulation model and the measurement of physiological data in one environment. The Traffic Jam Assist system is used as an ADAS example in this paper

Towards a Common Software/Hardware Methodology for Future Advanced Driver Assistance Systems

The European research project DESERVE (DEvelopment platform for Safe and Efficient dRiVE, 2012-2015) had the aim of designing and developing a platform tool to cope with the continuously increasing complexity and the simultaneous need to reduce cost for future embedded Advanced Driver Assistance Systems (ADAS). For this purpose, the DESERVE platform profits from cross-domain software reuse, standardization of automotive software component interfaces, and easy but safety-compliant integration of heterogeneous modules. This enables the development of a new generation of ADAS applications, which challengingly combine different functions, sensors, actuators, hardware platforms, and Human Machine Interfaces (HMI). This book presents the different results of the DESERVE project concerning the ADAS development platform, test case functions, and validation and evaluation of different approaches. The reader is invited to substantiate the content of this book with the deliverables published during the DESERVE project. Technical topics discussed in this book include:Modern ADAS development platforms;Design space exploration;Driving modelling;Video-based and Radar-based ADAS functions;HMI for ADAS;Vehicle-hardware-in-the-loop validation system

Data-Driven User Behavior Evaluation

Automotive Original Equipment Manufacturers (OEMs) compete worldwide to stand out with new trends and technologies. Automated Driver Assistance Systems (ADAS) are an example of advanced solutions where a lot of effort is put into the development and utilization of vehicle data. ADAS systems range from different types of information/warning systems to adaptive functions designed to assist the driver in the driving tasks and ensure more efficient and comfortable driving. These types of systems have become standard at many OEMs, including Tesla, Cadillac, BMW, Mercedes, Volvo Cars, and others. Volvo Cars is well-known for the development of such ADAS functions as ACC (Adaptive Cruise Control) and PA (Pilot Assist). These functions offer lateral and/or longitudinal support, but leave the driver in full control and with responsibility for the driving task.The ADAS systems are not fully automated. These systems have a number of limitations related to the context where they can operate. Previous studies have demonstrated that the drivers’ understanding and adoption of these systems is not definite and may vary from full technology acceptance to complete ignorance. Therefore, in-depth understanding and interpretation of driver behavior and needs regarding the use of ADAS can significantly help developers to reflect on and improve the systems to meet the users’ expectations. Recently, the availability of data coming from the in-vehicle sensors network has increased significantly. The amount of received data potentially enables the in-depth quantitative driver behavior evaluation in a time-efficient and reliable way. Moreover, the ability of vehicle sensors and actuator data to synchronize the driver and system performance and assess the driving conditions in the moment of driver-system interaction can contribute to the comprehensive context-aware ADAS evaluation.\ua0 Developing methods for objective assessment of driver behavior is a task with a high level of complexity. This process requires (i) investigation of the driver behavior assessment area where vehicle data can be useful; (ii) identification of the influencing factors for evaluating ADAS functions; (iii) definition of the relevant data for the data-driven driver behavior evaluation; (iv) investigation of the ways to improve the feasibility of vehicle data. The research presented in this thesis focuses on the understanding of vehicle data applicability in user-related studies. The core of this research is the methodology for objective ADAS evaluation and a mixed-method approach that helps to integrate the quantitative methodologies into existing, mainly qualitative, evaluation practices.The conducted research revealed that vehicle data offers the possibility to determine individual user behavior, and to describe, categorize, and compare this to the average within a group. All of the above mentioned makes the applicability of vehicle data for user-related studies meaningful