Siddartha Khastgir

Identifying a gap in existing validation methodologies for intelligent automotive systems: Introducing the 3xD simulator

Recently there has been a growth in the incorporation of autonomous features within vehicles. From being perceived as a comfort feature, autonomous features in vehicles have now become a safety feature which are foreseen to reduce accidents. This has led to a new trend within the automotive industry of focussing on autonomous features for driver safety, which might ultimately lead to fully autonomous vehicles. Considering the fact that most of the accidents on UK roads occur due to driver error, driver-less vehicles would prove to be a benefit. However with automation, an even greater challenge of system validation in all scenarios needs to be addressed. For this, various methods of validation have been developed by different research organizations and manufacturers, but a standardized process still evades the industry. Some of the existing methods have been discussed in this paper to critically compare their quality of results and ease of execution. Subsequently, a new test platform has been proposed using the 3xD driving simulator which encompasses most requirements of a general testing method. A standardized process which would benefit the industry both in terms of reducing costs of having varied processes, and by increasing customer confidence can be developed using a non-invasive platform like the 3xD driving simulator. The novelty of the 3xD simulator is the ability to drive-in any vehicle (production/prototype) and develop testing methodologies in an immersive wireless environment.

Calibrating trust to increase the use of automated systems in a vehicle

While accident data show that human error is the cause of most of the on-road accidents, the move towards assisting or replacing the human driver with an automated system is not a straightforward one. Industries like aerospace, manufacturing, process etc. have a high penetration of automated systems; however, the automotive industry provides new challenges due to different and more dynamic interactions between the actors (driver, vehicle and environment). To reap benefits from the automated systems, drivers have to use the automated systems. Drivers’ trust in automated systems is one of the most important factors influencing drivers’ use of automated systems. Trust on automated systems is a dynamic construct, which can change with experience. While discussing various factors which influence drivers’ trust on automated systems, this paper discusses the changing nature of trust, i.e., calibration of trust and the possible interventions to calibrate trust on automated systems to an appropriate level.

Development of a Drive-in Driver-in-the-Loop Fully Immersive Driving Simulator for Virtual Validation of Automotive Systems

This paper gives an overview of the new Drive-in Driver-in-Loop simulator at WMG, University of Warwick, UK, which has been conceptualized to serve as a standard platform for virtual verification and validation of autonomous features. This front loading approach is key to the development of some of the upcoming technologies which have been lagging behind in terms of mass acceptance due to lack of proper simulation environment for testing. One of the key areas for the simulator is the study of driver acceptance of autonomous features in cars. Additionally, the simulator would help in the development of a validation methodology for autonomous systems keeping in mind the industry safety regulations and standards. The drive-in component on this scale adds to the novelty of the simulator, as its a first of its kind. This enhances the challenge of making the communication interfaces of the simulator general, in order to communicate with any vehicle driving into the simulator. In order to achieve this, emphasis was laid on software architecture to enable modularity and re-configuration. A brief about various applications of the simulator has been provided in this paper.

Incorporating ISO 26262 Concepts in an Automated Testing Toolchain Using Simulink Design Verifier

The introduction of ISO 26262 concepts has brought important changes in the software development process for automotive software. While making the process more robust by introducing various additional methods of verification and validation, there has been a substantial increase in the development time. Thus, test automation and front loading approaches have become important to meet product timelines and quality. This paper proposes automated testing methods using formal analysis tools like Simulink Design Verifier™ (SLDV) for boundary value testing and interface testing to address the demands of ISO 26262 concepts at unit and component level. In addition, the method of automated boundary value testing proposed differs from the traditional methods and the authors offer an argument as to why the traditional boundary value testing is not required at unit (function) level. There are two aspects of the proposed method: automated test case generation and automated test case execution. The paper discusses the benefits of automatic test case execution when combined with automatic test case generation. Traditional test automation implements the former and has limited advantages. One of the challenges with traditional application of the formal analysis tool is the time taken by the tool to reach to a conclusive decision for the triggered activity, i.e., the execution time of the tool. This shortcoming is overcome by an automated setup where the test framework is triggered during out of office hours, which saves developer’s work time. As a work product of the automated test execution, the developers receive test documentation which provides them with an overview of the results and specific test vectors for further analysis.

Effect of Knowledge of Automation Capability on Trust and Workload in an Automated Vehicle: A Driving Simulator Study

For the appropriate design of Advanced Driver Assistance Systems (ADAS) and Automated Driving (AD) systems, it is important to understand the process of driver-automation interaction and the factors affecting this interaction. In order to develop a part of this understanding, an exploratory driving simulator study with fifteen participants was conducted. The study design divided the participants into two groups: low capability automated system and high capability automated system. The study showed that providing knowledge about the capability of the automated system to the participants increased their overall trust in the automated system. However, it also increased their workload during the driving task. Increase in workload with knowledge was lower for high capability automated systems as compared to low capability automated systems. Therefore, while there is a need to inform the driver about the true capabilities of the system, there is a need to increase the capability of the systems to avoid increasing drivers’ workload too much.