O.J. Gietelink

Bio: O.J. Gietelink is an academic researcher from Delft University of Technology. The author has contributed to research in topics: Advanced driver assistance systems & Cooperative Adaptive Cruise Control. The author has an hindex of 8, co-authored 15 publications receiving 482 citations.

Development of advanced driver assistance systems with vehicle hardware-in-the-loop simulations

Abstract: This paper presents a new method for the design and validation of advanced driver assistance systems (ADASs). With vehicle hardware-in-the-loop (VEHIL) simulations, the development process, and more specifically the validation phase, of intelligent vehicles is carried out safer, cheaper, and is more manageable. In the VEHIL laboratory, a full-scale ADAS-equipped vehicle is set up in a hardware-in-the-loop simulation environment, where a chassis dynamometer is used to emulate the road interaction and robot vehicles to represent other traffic. In this controlled environment, the performance and dependability of an ADAS is tested to great accuracy and reliability. The working principle and the added value of VEHIL are demonstrated with test results of an adaptive cruise control and a forward collision warning system. On the basis of the 'V' diagram, the position of VEHIL in the development process of ADASs is illustrated.

Pre-crash system validation with PRESCAN and VEHIL

Abstract: This paper presents the tools for design and validation of pre-crash systems: the software tool PRE-crash SCenario ANalyzer (PRESCAN) and the VEhicle-Hardware-In-the-Loop (VEHIL) facility. PRESCAN allows to investigate a pre-crash scenario in simulation. This scenario can then be compared with tests performed in the VEHIL facility for validation of the real sensor and controller of the pre-crash system. Using PRESCAN and VEHIL the development process and more specifically the validation of intelligent vehicles can be carried out safer, cheaper, and more reliable.

Design and validation of advanced driver assistance systems

Abstract: This thesis presents new tools and methods for the design and validation of advanced driver assistance systems (ADASs). ADASs aim to improve driving comfort and traffic safety by assisting the driver in recognizing and reacting to potentially dangerous traffic situations. A major challenge in designing these systems is to guarantee high performance and dependability under all possible combinations of traffic scenarios, operating conditions, and failure modes. These stringent requirements necessitate fault-tolerant control techniques and a thorough validation of the system. A microscopic traffic simulation within the simulation environment PreScan supports the initial system design. In addition, a unique tool for the design and validation of ADASs is presented and evaluated: vehicle hardware-in-the-loop (VeHIL) simulation. The VeHIL laboratory allows an ADAS-equipped vehicle to be tested in an artificial environment, where surrounding traffic is emulated by robot vehicles. VeHIL enables repeatable, safe, and accurate testing, complementary to human-in-the-loop test drives. The use of these three tools (PreScan, VeHIL, and test drives) is combined in a methodology for probabilistic validation of ADASs, based on randomized algorithms. This methodology is more efficient than conventional simulation techniques and the current practice of trial-and-error test drives. It results in a test schedule definition with a minimum number of simulations and test runs, such that the performance and dependability of an ADAS can be guaranteed, given a desired level of accuracy and confidence. The added value of the methodology is demonstrated with three case studies, involving a driver information and warning system, a fault-tolerant system for cooperative adaptive cruise control, and a pre-crash system.

Preliminary design of an application for communication based longitudinal control in the CARTALK2000 project

Abstract: The objective of the IST 5th Framework EC project CarTALK2000 is to design, test and evaluate co-operative driver assistance systems to improve the overall traffic safety and to increase driving comfort and transport efficiency. Inter-vehicle communication is a key technology in the development of these systems. An example of safe and comfortable driving, as one of the goals of the project, is presented in this paper. It is meant to be a preliminary application feasibility assessment to explore inter-vehicle communication functionality in order to support further CarTALK work. At TNO a co-operative collision warning and avoidance system is developed to support the driver in longitudinal control of the vehicle. Warnings based on acceleration, velocity and inter-vehicle headway data are generated to trigger both driver and automatic vehicle actions. Inter-vehicle control algorithms are designed and evaluated in a conditioned experimental set-up with test vehicles using line-of-sight infrared communication. Preliminary results indicate a gain in response time and anticipative vehicle control capabilities. In the ongoing project the partners will further develop applications, radio communication technology and in-vehicle architecture. Standardization and socio-economic technology assessment are issues of concern to support market introduction. For the covering abstract see ITRD E122427.

Digital Twin: Values, Challenges and Enablers From a Modeling Perspective

Abstract: Digital twin can be defined as a virtual representation of a physical asset enabled through data and simulators for real-time prediction, optimization, monitoring, controlling, and improved decision making. Recent advances in computational pipelines, multiphysics solvers, artificial intelligence, big data cybernetics, data processing and management tools bring the promise of digital twins and their impact on society closer to reality. Digital twinning is now an important and emerging trend in many applications. Also referred to as a computational megamodel, device shadow, mirrored system, avatar or a synchronized virtual prototype, there can be no doubt that a digital twin plays a transformative role not only in how we design and operate cyber-physical intelligent systems, but also in how we advance the modularity of multi-disciplinary systems to tackle fundamental barriers not addressed by the current, evolutionary modeling practices. In this work, we review the recent status of methodologies and techniques related to the construction of digital twins mostly from a modeling perspective. Our aim is to provide a detailed coverage of the current challenges and enabling technologies along with recommendations and reflections for various stakeholders.

MDDV: a mobility-centric data dissemination algorithm for vehicular networks

Abstract: There has been increasing interest in the exploitation of advances in information technology in surface transportation systems. One trend is to exploit on-board sensing, computing and communication capabilities in vehicles, e.g., to augment and enhance existing intelligent transportation systems. A natural approach is to use vehicle-to-vehicle communications to disseminate information. In this paper, we propose MDDV, a mobility-centric approach for data dissemination in vehicular networks designed to operate efficiently and reliably despite the highly mobile, partitioned nature of these networks. MDDV is designed to exploit vehicle mobility for data dissemination, and combines the idea of opportunistic forwarding, trajectory based forwarding and geographical forwarding. We develop a generic mobile computing approach for designing localized algorithms in vehicular networks. Vehicles perform local operations based on their own knowledge while they collectively achieve a global behavior. We evaluate the performance of the MDDV algorithm using realistic simulation of the vehicle traffic in Atlanta area.

Vehicle Detection Techniques for Collision Avoidance Systems: A Review

Abstract: Over the past decade, vision-based vehicle detection techniques for road safety improvement have gained an increasing amount of attention. Unfortunately, the techniques suffer from robustness due to huge variability in vehicle shape (particularly for motorcycles), cluttered environment, various illumination conditions, and driving behavior. In this paper, we provide a comprehensive survey in a systematic approach about the state-of-the-art on-road vision-based vehicle detection and tracking systems for collision avoidance systems (CASs). This paper is structured based on a vehicle detection processes starting from sensor selection to vehicle detection and tracking. Techniques in each process/step are reviewed and analyzed individually. Two main contributions in this paper are the following: survey on motorcycle detection techniques and the sensor comparison in terms of cost and range parameters. Finally, the survey provides an optimal choice with a low cost and reliable CAS design in vehicle industries.

Development of advanced driver assistance systems with vehicle hardware-in-the-loop simulations

Abstract: This paper presents a new method for the design and validation of advanced driver assistance systems (ADASs). With vehicle hardware-in-the-loop (VEHIL) simulations, the development process, and more specifically the validation phase, of intelligent vehicles is carried out safer, cheaper, and is more manageable. In the VEHIL laboratory, a full-scale ADAS-equipped vehicle is set up in a hardware-in-the-loop simulation environment, where a chassis dynamometer is used to emulate the road interaction and robot vehicles to represent other traffic. In this controlled environment, the performance and dependability of an ADAS is tested to great accuracy and reliability. The working principle and the added value of VEHIL are demonstrated with test results of an adaptive cruise control and a forward collision warning system. On the basis of the 'V' diagram, the position of VEHIL in the development process of ADASs is illustrated.

A systematic review of perception system and simulators for autonomous vehicles research

Abstract: This paper presents a systematic review of the perception systems and simulators for autonomous vehicles (AV). This work has been divided into three parts. In the first part, perception systems are categorized as environment perception systems and positioning estimation systems. The paper presents the physical fundamentals, principle functioning, and electromagnetic spectrum used to operate the most common sensors used in perception systems (ultrasonic, RADAR, LiDAR, cameras, IMU, GNSS, RTK, etc.). Furthermore, their strengths and weaknesses are shown, and the quantification of their features using spider charts will allow proper selection of different sensors depending on 11 features. In the second part, the main elements to be taken into account in the simulation of a perception system of an AV are presented. For this purpose, the paper describes simulators for model-based development, the main game engines that can be used for simulation, simulators from the robotics field, and lastly simulators used specifically for AV. Finally, the current state of regulations that are being applied in different countries around the world on issues concerning the implementation of autonomous vehicles is presented.