Het onderzoek in het artikel is geïnspireerd door de casus 'platooning' uit de Grand Cooperative Driving Challenge. Er is een PreScan®/Sumulink® model opgesteld met daarin twee auto's. De voorste auto volgt een vastgesteld snelheidsprofiel, de tweede auto volgt de eerste auto waarbij de tweede auto de snelheid van de eerste meet met behulp van een AIR-sensor. De besturing van het gaspedaal in beide auto's vindt plaats met Fuzzy Logic Control in plaats van met een klassieke regelaar. Concluderend mag worden gesteld dat in dit verkennend onderzoek gebleken is dat de Fuzzy Logic Control techniek in principe werkt.
This paper presents a multi-layer scheme to control a formation of three mobile robots. Each layer works as an independent module, dealing with a specific part of the problem of formation control, thus giving to the system more flexibility. In order to reduce formation errors, the proposed architecture includes a layer which performs an adaptive dynamic compensation, using a robust updating law, which compensates for each robot dynamics. The controller is able to guide the robots to the desired formation, including the possibility of time-varying position and/or shape. Stability analysis is performed for the closed-loop system, and the result is that the formation errors are ultimately bounded. Finally, simulation results for a group of three unicycle-like mobile robots are presented, which show that system performance is improved when the adaptive dynamic compensation layer is included in the formation control scheme. © 2009 IEEE.
Triggered by recent flood catastrophes and increasing concerns about climate change, scientists as well as policy-makers increasingly call for making long-term water policies to enable a transformation towards flood resilience. A key question is how to make these long-term policies adaptive so that they are able to deal with uncertainties and changing circumstances. The paper proposes three conditions for making long-term water policies adaptive, which are then used to evaluate a new Dutch water policy approach called 'Adaptive Delta Management'. Analysing this national policy approach and its translation to the Rotterdam region reveals that Dutch policy-makers are torn between adaptability and the urge to control. Reflecting on this dilemma, the paper suggests a stronger focus on monitoring and learning to strengthen the adaptability of long-term water policies. Moreover, increasing the adaptive capacity of society also requires a stronger engagement with local stakeholders including citizens and businesses.
In the last decade, the automotive industry has seen significant advancements in technology (Advanced Driver Assistance Systems (ADAS) and autonomous vehicles) that presents the opportunity to improve traffic safety, efficiency, and comfort. However, the lack of drivers’ knowledge (such as risks, benefits, capabilities, limitations, and components) and confusion (i.e., multiple systems that have similar but not identical functions with different names) concerning the vehicle technology still prevails and thus, limiting the safety potential. The usual sources (such as the owner’s manual, instructions from a sales representative, online forums, and post-purchase training) do not provide adequate and sustainable knowledge to drivers concerning ADAS. Additionally, existing driving training and examinations focus mainly on unassisted driving and are practically unchanged for 30 years. Therefore, where and how drivers should obtain the necessary skills and knowledge for safely and effectively using ADAS? The proposed KIEM project AMIGO aims to create a training framework for learner drivers by combining classroom, online/virtual, and on-the-road training modules for imparting adequate knowledge and skills (such as risk assessment, handling in safety-critical and take-over transitions, and self-evaluation). AMIGO will also develop an assessment procedure to evaluate the impact of ADAS training on drivers’ skills and knowledge by defining key performance indicators (KPIs) using in-vehicle data, eye-tracking data, and subjective measures. For practical reasons, AMIGO will focus on either lane-keeping assistance (LKA) or adaptive cruise control (ACC) for framework development and testing, depending on the system availability. The insights obtained from this project will serve as a foundation for a subsequent research project, which will expand the AMIGO framework to other ADAS systems (e.g., mandatory ADAS systems in new cars from 2020 onwards) and specific driver target groups, such as the elderly and novice.
The RAAK Pro MARS4Earth project focuses on the question of whether it is possible to develop a prototype of a modular and autonomous aerial manipulator (drone + robot arm) that can physically interact with a realistic outdoor environment, and what possibilities this creates to several application domains. In essence, the aerial manipulator acts as "arms and hands in the air", which can be used for both active interaction (maintenance of offshore windturbine) and passive interaction (selective plant treatment and firefighting). The modular aerial manipulator consists of four basic building blocks: • Mission-specific interaction module(s); • Intelligent surface exploration; • Adaptive interaction control algorithm(s); • Advanced on-board perception and decision module(s). In the meantime the first version of the aforementioned modular building blocks have been designed and realized by various consortium partners. However, due to the various measure of the COVID 19, consortium partners and researchers were not able to carry out the integration of various modules to realize the complete system. Moreover, it was not possible to conduct thorough tests in the operational environment to evaluate the performance of the first prototype. This is a crucial step tp realize the aerial manipulator with the envisaged modularity and performance. In this RAAK Impulse project, we will conduct integration of the first versions of the modules developed by the various consortium partners. Moreover, we will conduct thorough test in Emshave and Twente safety campus to investigate the functionality and performance of the developed integrated prototype. With this Impulse, we will be able to make up for the delay caused by the COVID -19 measures and conclude the project by realizing the original objectives of the MARS4Earth project.
Het RAAK-mkb project Smart Mobility is uitgevoerd door het lectoraat Automotive Control van Fontys hogeschool Automotive Engineering. Binnen het project is een living lab ontwikkeld voor onderzoek en ontwikkeling op het gebied van autonoom en coöperatief rijden. Omdat het lectoraat in het voorjaar van 2015 is gestopt, is verdere ontwikkeling van dit living lab voor onderwijs en onderzoek moeizaam verlopen. Met dit project is het mogelijk het living lab verder in te zetten voor onderwijsdoeleinden binnen het curriculum van Automotive Engineering en in kaart te brengen van de mogelijkheden voor vervolgonderzoek in samenwerking met de beroepspraktijk bij het lectoraat Future Power Train. Het living lab bestaat uit een auto (Toyota Prius) voorzien van sensoren, instrumentatie en controlesystemen waarmee de autonome en coöperatieve rijfuncties gerealiseerd kunnen worden. Het living lab wordt nu reeds gebruikt als development platform voor een studententeam van HBO en TU studenten (www.ateam.nl). Het Top-up project maakt het mogelijk dit living lab ook in het tweede leerjaar in te zetten als leermiddel.
