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arXiv 2024年

作者： Certad, Novel del Re, Enrico Korndörfer, Helena Schröder, Gregory Morales-Alvarez, Walter Tschernuth, Sebastian Gankhuyag, Delgermaa del Re, Luigi Olaverri-Monreal, Cristina IAV GmbH Berlin Germany Institute for Design and Control of Mechatronical Systems Johannes Kepler University Linz Linz4040 Austria the Department Intelligent Transport Systems the Johannes Kepler University Linz Austria

The acquisition and analysis of high-quality sensor data constitute an essential requirement in shaping the development of fully autonomous driving systems. This process is indispensable for enhancing road safety and ensuring the effectiveness of the technological advancements in the automotive industry. This study introduces the Interaction of Autonomous and Manually-controlled Vehicles (IAMCV) dataset, a novel and extensive dataset focused on inter-vehicle interactions. The dataset, enriched with a sophisticated array of sensors such as Light Detection and Ranging, cameras, Inertial Measurement Unit/Global Positioning System, and vehicle bus data acquisition, provides a comprehensive representation of real-world driving scenarios that include roundabouts, intersections, country roads, and highways, recorded across diverse locations in Germany. Furthermore, the study shows the versatility of the IAMCV dataset through several proof-of-concept use cases. Firstly, an unsupervised trajectory clustering algorithm illustrates the dataset’s capability in categorizing vehicle movements without the need for labeled training data. Secondly, we compare an online camera calibration method with the Robot Operating System-based standard, using images captured in the dataset. Finally, a preliminary test employing the YOLOv8 object-detection model is conducted, augmented by reflections on the transferability of object detection across various LIDAR resolutions. These use cases underscore the practical utility of the collected dataset, emphasizing its potential to advance research and innovation in the area of intelligent vehicles. Copyright © 2024, The Authors. All rights reserved.

关键词： Autonomous vehicles

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Synchronized Ecodriving control for Convoys

Synchronized Ecodriving Control for Convoys

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European control Conference (ECC)

作者： Christian Schauer Gunda Obereigner Luigi del Re Institute for Design and Control of Mechatronical Systems Johannes Kepler University Linz Austria

The adoption of an energy aware driving style, often referred to as ecodriving, is a promising way to save, besides of costs, non-renewable fossil fuels. In a previous paper we presented a two-layer control approach for ecodriving which tracks an optimal speed profile resulting from the first layer under the presence of traffic in the second layer. In this paper, we extend the developed control approach to a convoy of vehicles and determine, whether it leads to safe and stable convoys and whether an increasing number of vehicles within the convoy leads to an increased fuel efficiency. Thereby, we focus on two different prediction methods of the preceding vehicle: in the first case we assume perfect knowledge of the future movement of the preceding vehicle, whereas in the second case we assume the current speed of the preceding vehicle to be constant during the prediction horizon. It is shown that the higher the number of vehicles the more fuel saving from the optimal solution can be recovered.

关键词： Costs Europe Prediction methods Lead Fossil fuels Synchronization

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Adaptive Nonlinear Model Predictive control of an Engine Air Path

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IFAC-PapersOnLine 2021年第10期54卷 114-119页

作者： Max Haugeneder Florian Meier Daniel Adelberger Luigi del Re Institute for Design and Control of Mechatronical Systems Johannes Kepler University Linz Altenberger Strasse 69 A-4040 Linz Austria

It is well known that high performing control based on a nominal model may underperform when system parameters change e.g. due to wear. Adaptive controls are a well established way to tackle this problem, but their usage is not trivial, especially when they are used for complex nonlinear systems with constraints like the air path of a combustion engine. In particular, excitation can be insufficient for the update of a model with many parameters. Against this background, we extend and test an approach based on directional forgetting on a production engine, showing that this approach is viable for practical applications.

关键词： automotive control system identification adaptive control predictive control

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Model predictive control of HEVs with exhaust aftertreatment system at low ambient temperatures

Model predictive control of HEVs with exhaust aftertreatment...

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control Technology and Applications (CCTA),

作者： Florian Meier Luigi Del Re Institute for Design and Control of Mechatronical Systems Johannes Kepler University Linz Austria

ISBN: (纸本)9781665436441

Online control of hybrid electric vehicles (HEV) is mostly centered on fuel consumption and battery management while emissions are seldom considered. This is frequently correct, as warmed up exhaust aftertreatment systems show an extremely high conversion efficiency. However, HEVs typically shut off the engine during low load phases, which extends coldstart periods and prevents the aftertreatment to work at the correct temperature. Latest regulations put additional focus on real driving coldstart performance though. Against this background, this paper analyzes the potential relevance and presents a possible solution by considering it explicitly in the control approach. It is shown that an implementable model predictive control (MPC) strategy can recover a large part of the theoretical performance as computed by dynamic programming (DP). Optimal MPC parameter tuning is efficiently performed utilizing available DP solutions from comparable scenarios. A potential saving of up to 40% NOx with equal consumption is shown in this example.

关键词： Temperature measurement Heating systems Optimal control Reservoirs Regulation Hybrid electric vehicles Vehicle dynamics

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Online energy management for intermittent operation of hybrid electric vehicles at low temperatures

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IFAC-PapersOnLine 2021年第20期54卷 393-398页

作者： Florian Meier Luigi del Re Institute for Design and Control of Mechatronical Systems Johannes Kepler University Linz Altenberger Strasse 69 A-4040 Linz Austria

Commonly, the control of hybrid electric vehicles (HEVs) is focused on efficiency maximization by distributing engine and electrical machine power. The only state to be considered in such an optimization is the battery charge. In certain situations such as cold starts in winter additional aspects gain importance. Passenger safety and comfort require sufficient heating of the cabin draining thermal energy from the engine. Moreover, exhaust aftertreatment systems must be heated up fast to comply with emission limits. This becomes even more critical for short-haul cold start scenarios. In this paper, we propose a possible online solution based on model predictive control (MPC) to balance fuel consumption and emission minimization with thermal management showing to provide significant emission reduction compared to purely powertrain centered approaches.

关键词： Automotive systems control design control Applications Optimal control

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Methods for Traffic Data Classification with regard to Potential Safety Hazards ⁎

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IFAC-PapersOnLine 2021年第7期54卷 250-255页

作者： Gunda Obereigner Pavlo Tkachenko Luigi del Re Institute for Design and Control of Mechatronical Systems Johannes Kepler University Linz Altenberger Strasse 69 A-4040 Linz Austria

Traffic data are a key element for setting up scenarios for Advanced Driver Assistant systems (ADAS) safety and performance testing. Testing will thus reflect in some way the data used. However, there is no clear understanding in which way and how to choose the data so that the evaluation results are reliable and comprehensive. Therefore, the important scenarios in a traffic data set in view of safety analysis have to be determined. The paper presents a method with which traffic situations from a given data set are classified into different safety classes according to easily measurable features. It is shown that taking the Time To Collision (TTC) as a measure of safety and a linear Support Vector Machine (SVM) as a classifier, 64.7% of traffic situations of a validation data set were classified to the correct safety class considering only three measurable features. Thus, traffic situations from a data set can be classified fast into different safety categories, providing information to the ADAS tester if the developed device has been tested in a safe or unsafe environment.

关键词： Safety Analysis Machine Learning Classification Datasets Automotive

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The Linear Functional Strategy for Maneuvers Identification Using Elastic Template Matching ⁎

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IFAC-PapersOnLine 2021年第7期54卷 427-432页

作者： Pavlo Tkachenko Christina Schmid Luigi del Re Institute for Design and Control of Mechatronical Systems Johannes Kepler University Linz Altenberger Strasse 69 A-4040 Linz Austria

In a previous work, we have developed a template (or pattern) matching algorithm for maneuver recognition in highway traffic based on the dynamic time warping alignment strategy. The developed method rely on the model set-ups and tuning parameters, in particular, a template, pre-selected during the training phase. However, the selected template is representing to some extent an “in average” good solution, and the other ones performing less well in general, but maybe better for some particular cases, were rejected. In the current paper we are aiming to introduce a Linear Functional Strategy (LFS) to the community which allows to gain from the variety of possible solutions. This technique belongs to the so-called aggregation approaches, where different models are combined into a final estimator. In our case study, the resulting solution not only allows to avoid pre-selecting of a single template, but also outperforms the best single choice. The latter will be illustrated by numerical experiments on maneuver identification based on a big drone dataset of highway driving.

关键词： Linear Functional Strategy Aggregation Identification Template Matching DTW

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Optimal PVB System Sizing and Energy Management for Grid-Connected Households

Optimal PVB System Sizing and Energy Management for Grid-Con...

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IEEE International Conference on systems, Man and Cybernetics

作者： Daniel Adelberger Gunda Obereigner Amit Joshi Luigi Glielmo Institute for Design and Control of Mechatronical Systems Johannes Kepler University Linz Austria University of Sannio Benevento Italy

ISBN: (纸本)9781665442084

Due to the increasingly dominant climate change, "green" energy sources that do not contribute to further damage of the environment play an emerging and relevant role. A big advantage is that this kind of energy can be generated not only on a large scale, such as by wind turbines or hydroelectric power plants, but also by individual households through (among others) so-called Photovoltaic-Battery (PVB) systems which are based on solar energy. Compared with energy from the power grid, such systems naturally involve higher acquisition costs, which can, however, potentially be amortized. This raises the question of how large such systems should be designed, what the optimal strategy of usage is, and how relevant typical sizes of the individual elements available on the market are to the design strategy. Against this background, we investigate the problems addressed, taking into account different pricing strategies, and show, based on a simulation study, that PVB systems can bring major benefits in the long term. Additionally, our results indicate, that – to a certain extent – efficient energy management is able to compensate for limitations in sizing.

关键词： Photovoltaic systems Costs Green products Hydroelectric power generation Solar energy Pricing Power grids

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Tire Particle control with Comfort Bounds for Electric Vehicles

Tire Particle Control with Comfort Bounds for Electric Vehic...

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IEEE Conference on Decision and control

作者： Gunda Singer Daniel Adelberger Robert Shorten Luigi Del Re Institute for Design and Control of Mechatronical Systems Johannes Kepler University Linz Austria Imperial College London United Kingdom

ISBN: (纸本)9781665436601

While it is widely known that electric vehicles will contribute very substantially to the reduction of exhaust emissions, it is less known that the impact of particulates, in particular from tires, will become larger, due to both the weight of these vehicles and the torque profile of electrical machines. In this paper, we use a recently developed tire emissions estimation method to develop a control approach that reduces these emissions. We show in a comprehensive simulation study using real driving data from German highways that the tire particle controller not only reduces tire emissions but at the same time allows to ensure ride comfort. These results illustrate that there is potentially a substantial environmental benefit to be expected especially depending on the presence, type and prediction of a preceding vehicle.

关键词： Road transportation Torque Conferences Atmospheric modeling Estimation Electric vehicles Tires

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Context Aware control of ADAS

Context Aware Control of ADAS

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American control Conference

作者： J. Holzinger P. Tkachenko G. Obereigner L. del Re Institute for Design and Control of Mechatronical Systems Johannes Kepler University Linz Austria

ISBN: (数字)9781538682661

ISBN: (纸本)9781538682678

Variability of traffic conditions is a well known fact. Traditionally, vehicles have been developed to cope with many very different conditions, both in terms of environment and traffic, albeit at the price of, among other, reduced efficiency under many conditions. The progressive increase of on board computational power, sensors and other available information offers new possibilities, in particular, besides achieving their main function, ADAS can be tailored to achieve additional benefits, e.g. reduce fuel consumption or improve driving comfort. However, we may expect that the levels of improvement strongly depend on the specific traffic conditions. To check this hypothesis, in this paper we use measured data to build up clusters of traffic situations, and then analyze by simulation the achievable improvements of fuel consumption vs. comfort at the example of a specific ADAS, both in the case of averages and of single vehicles from the clusters. As the examples confirm, the trade-off is indeed context dependent, and control tuning should be adapted accordingly.

关键词： Fuels Automobiles Data models Acceleration Tuning Computational modeling Sensors

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