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  • Transport Research
  • 2018-2022
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Berenike Masing; Niels Lindner; Ralf Borndörfer;

    We consider the line planning problem in public transport in the Parametric City, an idealized model that captures typical scenarios by a (small) number of parameters. The Parametric City is rotation symmetric, but optimal line plans are not always symmetric. This raises the question to quantify the symmetry gap between the best symmetric and the overall best solution. For our analysis, we formulate the line planning problem as a mixed integer linear program, that can be solved in polynomial time if the solutions are forced to be symmetric. The symmetry gap is provably small when a specific Parametric City parameter is fixed, and we give an approximation algorithm for line planning in the Parametric City in this case. While the symmetry gap can be arbitrarily large in general, we show that symmetric line plans are a good choice in most practical situations.

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ arXiv.org e-Print Ar...arrow_drop_down
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    image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
    Transportation Research Part B Methodological
    Article . 2022 . Peer-reviewed
    License: Elsevier TDM
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    https://doi.org/10.48550/arxiv...
    Article . 2022
    License: arXiv Non-Exclusive Distribution
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ arXiv.org e-Print Ar...arrow_drop_down
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      image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
      Transportation Research Part B Methodological
      Article . 2022 . Peer-reviewed
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      Article . 2022
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Landt-Hayen, Marco; Kröger, Peer; Claus, Martin; Rath, Willi;

    Artificial neural networks (ANNs) are known to be powerful methods for many hard problems (e.g. image classification, speech recognition or time series prediction). However, these models tend to produce black-box results and are often difficult to interpret. Layer-wise relevance propagation (LRP) is a widely used technique to understand how ANN models come to their conclusion and to understand what a model has learned. Here, we focus on Echo State Networks (ESNs) as a certain type of recurrent neural networks, also known as reservoir computing. ESNs are easy to train and only require a small number of trainable parameters, but are still black-box models. We show how LRP can be applied to ESNs in order to open the black-box. We also show how ESNs can be used not only for time series prediction but also for image classification: Our ESN model serves as a detector for El Nino Southern Oscillation (ENSO) from sea surface temperature anomalies. ENSO is actually a well-known problem and has been extensively discussed before. But here we use this simple problem to demonstrate how LRP can significantly enhance the explainablility of ESNs. Shortened title, corrected author affiliation, added citation reference: Accepted at 3rd International Conference on Machine Learning Techniques (MLTEC 2022), Zurich, Switzerland

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ OceanReparrow_drop_down
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    Conference object . 2022 . Peer-reviewed
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    https://doi.org/10.48550/arxiv...
    Article . 2022
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      https://doi.org/10.48550/arxiv...
      Article . 2022
      License: arXiv Non-Exclusive Distribution
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Lukas Ewecker; Ebubekir Asan; Lars Ohnemus; Sascha Saralajew;

    AbstractIn recent years, computer vision algorithms have become more powerful, which enabled technologies such as autonomous driving to evolve rapidly. However, current algorithms mainly share one limitation: They rely on directly visible objects. This is a significant drawback compared to human behavior, where visual cues caused by objects (e. g., shadows) are already used intuitively to retrieve information or anticipate occurring objects. While driving at night, this performance deficit becomes even more obvious: Humans already process the light artifacts caused by the headlamps of oncoming vehicles to estimate where they appear, whereas current object detection systems require that the oncoming vehicle is directly visible before it can be detected. Based on previous work on this subject, in this paper, we present a complete system that can detect light artifacts caused by the headlights of oncoming vehicles so that it detects that a vehicle is approaching providently (denoted as provident vehicle detection). For that, an entire algorithm architecture is investigated, including the detection in the image space, the three-dimensional localization, and the tracking of light artifacts. To demonstrate the usefulness of such an algorithm, the proposed algorithm is deployed in a test vehicle to use the detected light artifacts to control the glare-free high beam system proactively (react before the oncoming vehicle is directly visible). Using this experimental setting, the provident vehicle detection system’s time benefit compared to an in-production computer vision system is quantified. Additionally, the glare-free high beam use case provides a real-time and real-world visualization interface of the detection results by considering the adaptive headlamps as projectors. With this investigation of provident vehicle detection, we want to put awareness on the unconventional sensing task of detecting objects providently (detection based on observable visual cues the objects cause before they are visible) and further close the performance gap between human behavior and computer vision algorithms to bring autonomous and automated driving a step forward.

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Institutionelles Rep...arrow_drop_down
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    Autonomous Robots
    Article . 2022 . Peer-reviewed
    License: CC BY
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    KITopen
    Article . 2022
    License: CC BY
    Data sources: KITopen
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
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    https://doi.org/10.5445/ir/100...
    Article . 2022
    License: CC BY
    Data sources: Datacite
    https://doi.org/10.15488/13654...
    Article . 2022
    License: CC BY
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    https://doi.org/10.48550/arxiv...
    Article . 2021
    License: arXiv Non-Exclusive Distribution
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Institutionelles Rep...arrow_drop_down
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      Autonomous Robots
      Article . 2022 . Peer-reviewed
      License: CC BY
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      KITopen
      Article . 2022
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
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      https://doi.org/10.5445/ir/100...
      Article . 2022
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      https://doi.org/10.15488/13654...
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      https://doi.org/10.48550/arxiv...
      Article . 2021
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Amador, Oscar; Ronelöv, Erik; Boustedt, Katarina; Blidkvist, Jesper; +1 Authors

    The use of reactive detection technologies such as passive and active sensors for avoiding car accidents involving pedestrians and other Vulnerable Road Users (VRU) is one of the cornerstones of Cooperative, Connected, and Automated Mobility (CCAM). However, CCAM systems are not yet present in all roads at all times. The use of currently available technologies that are embedded in smartphones, such as location services and Internet access, are enablers for the early detection of VRUs. This paper presents the proof-of-concept of a system that provides vehicles with enough information about the presence of VRUs by using public cellular networks, an MQTT broker, and IEEE 802.11p-enabled hardware (a roadside unit and an on-board unit). The system was tested in an urban environment and in a test track, where its feasibility was evaluated. Results were satisfactory, proving the system is reliable enough to alert of the sudden appearance of a VRU in time for the driver to react. © 2022 IEEE. Funding text: Karlsruhe Institute of Technology acknowledges the support from Helmholtz Association (FE.5167.0007.0012 – Cooperative Autonomous Systems).

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Digitala Vetenskapli...arrow_drop_down
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    image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
    https://doi.org/10.1109/icves5...
    Conference object . 2022 . Peer-reviewed
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    Article . 2023
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    Authors: Anita Schöbel; Reena Urban;

    Route choice models in public transport have been discussed for a long time. The main factor why a passenger chooses a specific path is usually based on its length or travel time. However, also the ticket price that passengers have to pay may influence their decision since passengers prefer cheaper paths over more expensive ones. In this paper, we deal with the cheapest ticket problem which asks for a cheapest ticket to travel between a pair of stations. The complexity and the algorithmic approach to solve this problem depend crucially on the underlying fare structure, e.g., it is easy if the ticket prices are proportional to the distance traveled (as in distance tariff fare structures), but may become NP-complete in zone tariff fare structures. We hence discuss the cheapest ticket problem for different variations of distance- and zone-based fare structures. We start by modeling the respective fare structure mathematically, identify its main properties, and finally provide a polynomial algorithm, or prove NP-completeness of the cheapest ticket problem. We also provide general results on the combination of two fare structures, which is often observed in practice. Comment: 35 pages, revised version

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    https://doi.org/10.48550/arxiv...
    Article . 2021
    License: CC BY
    Data sources: Datacite
    Transportation Science
    Article . 2022 . Peer-reviewed
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      https://doi.org/10.48550/arxiv...
      Article . 2021
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      Transportation Science
      Article . 2022 . Peer-reviewed
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    Authors: Tsaregorodtsev, Alexander; Müller, Johannes; Strohbeck, Jan; Herrmann, Martin; +2 Authors

    Monocular camera sensors are vital to intelligent vehicle operation and automated driving assistance and are also heavily employed in traffic control infrastructure. Calibrating the monocular camera, though, is time-consuming and often requires significant manual intervention. In this work, we present an extrinsic camera calibration approach that automatizes the parameter estimation by utilizing semantic segmentation information from images and point clouds. Our approach relies on a coarse initial measurement of the camera pose and builds on lidar sensors mounted on a vehicle with high-precision localization to capture a point cloud of the camera environment. Afterward, a mapping between the camera and world coordinate spaces is obtained by performing a lidar-to-camera registration of the semantically segmented sensor data. We evaluate our method on simulated and real-world data to demonstrate low error measurements in the calibration results. Our approach is suitable for infrastructure sensors as well as vehicle sensors, while it does not require motion of the camera platform. Comment: 7 pages, 3 figures, accepted at the 25th International Conference on Intelligent Transportation Systems (ITSC) 2022

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    Authors: Kachirayil, Febin; Weinand, Jann Michael; Scheller, Fabian; McKenna, Russell;

    The electrification of heating, cooling, and transportation to reach decarbonization targets calls for a rapid expansion of renewable technologies. Due to their decentral and intermittent nature, these technologies require robust planning that considers non-technical constraints and flexibility options to be integrated effectively. Energy system models (ESMs) are frequently used to support decision-makers in this planning process. In this study, 116 case studies of local, integrated ESMs are systematically reviewed to identify best-practice approaches to model flexibility and address non-technical constraints. Within the sample, storage systems and sector coupling are the most common types of flexibility. Sector coupling with the transportation sector is rarely considered, specifically with electric vehicles even though they could be used for smart charging or vehicle-to-grid operation. Social aspects are generally either completely neglected or modeled exogenously. Lacking actor heterogeneity, which can lead to unstable results in optimization models, can be addressed through building-level information. A strong emphasis on cost is found and while emissions are also frequently reported, additional metrics such as imports or the share of renewable generation are nearly entirely absent. To guide future modeling, the paper concludes with a roadmap highlighting flexibility and robustness options that either represent low-hanging fruit or have a large impact on results. Applied Energy, 324 ISSN:1872-9118 ISSN:0306-2619

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    Applied Energy
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      Applied Energy
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    Authors: Johannes Muller; Jan Strohbeck; Martin Herrmann; Michael Buchholz;

    Motion planning at urban intersections that accounts for the situation context, handles occlusions, and deals with measurement and prediction uncertainty is a major challenge on the way to urban automated driving. In this work, we address this challenge with a sampling-based optimization approach. For this, we formulate an optimal control problem that optimizes for low risk and high passenger comfort. The risk is calculated on the basis of the perception information and the respective uncertainty using a risk model. The risk model combines set-based methods and probabilistic approaches. Thus, the approach provides safety guarantees in a probabilistic sense, while for a vanishing risk, the formal safety guarantees of the set-based methods are inherited. By exploring all available behavior options, our approach solves decision making and longitudinal trajectory planning in one step. The available behavior options are provided by a formal representation of the situation context, which is also used to reduce calculation efforts. Occlusions are resolved using the external perception of infrastructure-mounted sensors. Yet, instead of merging external and ego perception with track-to-track fusion, the information is used in parallel. The motion planning scheme is validated through real-world experiments. Comment: 12 pages, 8 figures

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    IEEE Transactions on Intelligent Transportation Systems
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      IEEE Transactions on Intelligent Transportation Systems
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    Authors: Wang, Chao; Chu, Derck; Martens, Marieke; Krüger, Matti; +1 Authors

    Currently, there are still various situations in which automated driving systems (ADS) cannot perform as well as a human driver, particularly in predicting the behaviour of surrounding traffic. As humans are still surpassing state-of-the-art ADS in this task, a new concept enabling human driver to help ADS to better anticipate the behaviour of other road users was developed. Preliminary results suggested that the collaboration at the prediction level can effectively enhance the experience and comfort of ADS. For an in-depth investigation of the concept, we implemented an interactive prototype, called Prediction-level Cooperative Automated Driving system (PreCoAD), adapting an existing ADS that has been previously validated on the public road. The results of a driving simulator study among 15 participants in different highway scenarios showed that PreCoAD could enhance automated driving performance and provide a positive user experience. Follow-up interviews with participants also provided insights into the improvement of the system. Comment: 13pages, 7 figures

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    Authors: Pfandzelter, Tobias; Henning, Sören; Schirmer, Trever; Hasselbring, Wilhelm; +1 Authors

    In cloud event processing, data generated at the edge is processed in real-time by cloud resources. Both distributed stream processing (DSP) and Function-as-a-Service (FaaS) have been proposed to implement such event processing applications. FaaS emphasizes fast development and easy operation, while DSP emphasizes efficient handling of large data volumes. Despite their architectural differences, both can be used to model and implement loosely-coupled job graphs. In this paper, we consider the selection of FaaS and DSP from a cost perspective. We implement stateless and stateful workflows from the Theodolite benchmarking suite using cloud FaaS and DSP. In an extensive evaluation, we show how application type, cloud service provider, and runtime environment can influence the cost of application deployments and derive decision guidelines for cloud engineers. Comment: Accepted for Publication at the 10th IEEE International Conference on Cloud Engineering (IC2E 2022)

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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Berenike Masing; Niels Lindner; Ralf Borndörfer;

    We consider the line planning problem in public transport in the Parametric City, an idealized model that captures typical scenarios by a (small) number of parameters. The Parametric City is rotation symmetric, but optimal line plans are not always symmetric. This raises the question to quantify the symmetry gap between the best symmetric and the overall best solution. For our analysis, we formulate the line planning problem as a mixed integer linear program, that can be solved in polynomial time if the solutions are forced to be symmetric. The symmetry gap is provably small when a specific Parametric City parameter is fixed, and we give an approximation algorithm for line planning in the Parametric City in this case. While the symmetry gap can be arbitrarily large in general, we show that symmetric line plans are a good choice in most practical situations.

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    Transportation Research Part B Methodological
    Article . 2022 . Peer-reviewed
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      Transportation Research Part B Methodological
      Article . 2022 . Peer-reviewed
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    Authors: Landt-Hayen, Marco; Kröger, Peer; Claus, Martin; Rath, Willi;

    Artificial neural networks (ANNs) are known to be powerful methods for many hard problems (e.g. image classification, speech recognition or time series prediction). However, these models tend to produce black-box results and are often difficult to interpret. Layer-wise relevance propagation (LRP) is a widely used technique to understand how ANN models come to their conclusion and to understand what a model has learned. Here, we focus on Echo State Networks (ESNs) as a certain type of recurrent neural networks, also known as reservoir computing. ESNs are easy to train and only require a small number of trainable parameters, but are still black-box models. We show how LRP can be applied to ESNs in order to open the black-box. We also show how ESNs can be used not only for time series prediction but also for image classification: Our ESN model serves as a detector for El Nino Southern Oscillation (ENSO) from sea surface temperature anomalies. ENSO is actually a well-known problem and has been extensively discussed before. But here we use this simple problem to demonstrate how LRP can significantly enhance the explainablility of ESNs. Shortened title, corrected author affiliation, added citation reference: Accepted at 3rd International Conference on Machine Learning Techniques (MLTEC 2022), Zurich, Switzerland

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    https://doi.org/10.48550/arxiv...
    Article . 2022
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      https://doi.org/10.48550/arxiv...
      Article . 2022
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    Authors: Lukas Ewecker; Ebubekir Asan; Lars Ohnemus; Sascha Saralajew;

    AbstractIn recent years, computer vision algorithms have become more powerful, which enabled technologies such as autonomous driving to evolve rapidly. However, current algorithms mainly share one limitation: They rely on directly visible objects. This is a significant drawback compared to human behavior, where visual cues caused by objects (e. g., shadows) are already used intuitively to retrieve information or anticipate occurring objects. While driving at night, this performance deficit becomes even more obvious: Humans already process the light artifacts caused by the headlamps of oncoming vehicles to estimate where they appear, whereas current object detection systems require that the oncoming vehicle is directly visible before it can be detected. Based on previous work on this subject, in this paper, we present a complete system that can detect light artifacts caused by the headlights of oncoming vehicles so that it detects that a vehicle is approaching providently (denoted as provident vehicle detection). For that, an entire algorithm architecture is investigated, including the detection in the image space, the three-dimensional localization, and the tracking of light artifacts. To demonstrate the usefulness of such an algorithm, the proposed algorithm is deployed in a test vehicle to use the detected light artifacts to control the glare-free high beam system proactively (react before the oncoming vehicle is directly visible). Using this experimental setting, the provident vehicle detection system’s time benefit compared to an in-production computer vision system is quantified. Additionally, the glare-free high beam use case provides a real-time and real-world visualization interface of the detection results by considering the adaptive headlamps as projectors. With this investigation of provident vehicle detection, we want to put awareness on the unconventional sensing task of detecting objects providently (detection based on observable visual cues the objects cause before they are visible) and further close the performance gap between human behavior and computer vision algorithms to bring autonomous and automated driving a step forward.

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    Autonomous Robots
    Article . 2022 . Peer-reviewed
    License: CC BY
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    KITopen
    Article . 2022
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    https://doi.org/10.5445/ir/100...
    Article . 2022
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    https://doi.org/10.15488/13654...
    Article . 2022
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    Article . 2021
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      Autonomous Robots
      Article . 2022 . Peer-reviewed
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      https://doi.org/10.5445/ir/100...
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    Authors: Amador, Oscar; Ronelöv, Erik; Boustedt, Katarina; Blidkvist, Jesper; +1 Authors

    The use of reactive detection technologies such as passive and active sensors for avoiding car accidents involving pedestrians and other Vulnerable Road Users (VRU) is one of the cornerstones of Cooperative, Connected, and Automated Mobility (CCAM). However, CCAM systems are not yet present in all roads at all times. The use of currently available technologies that are embedded in smartphones, such as location services and Internet access, are enablers for the early detection of VRUs. This paper presents the proof-of-concept of a system that provides vehicles with enough information about the presence of VRUs by using public cellular networks, an MQTT broker, and IEEE 802.11p-enabled hardware (a roadside unit and an on-board unit). The system was tested in an urban environment and in a test track, where its feasibility was evaluated. Results were satisfactory, proving the system is reliable enough to alert of the sudden appearance of a VRU in time for the driver to react. © 2022 IEEE. Funding text: Karlsruhe Institute of Technology acknowledges the support from Helmholtz Association (FE.5167.0007.0012 – Cooperative Autonomous Systems).

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    https://doi.org/10.1109/icves5...
    Conference object . 2022 . Peer-reviewed
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    Authors: Anita Schöbel; Reena Urban;

    Route choice models in public transport have been discussed for a long time. The main factor why a passenger chooses a specific path is usually based on its length or travel time. However, also the ticket price that passengers have to pay may influence their decision since passengers prefer cheaper paths over more expensive ones. In this paper, we deal with the cheapest ticket problem which asks for a cheapest ticket to travel between a pair of stations. The complexity and the algorithmic approach to solve this problem depend crucially on the underlying fare structure, e.g., it is easy if the ticket prices are proportional to the distance traveled (as in distance tariff fare structures), but may become NP-complete in zone tariff fare structures. We hence discuss the cheapest ticket problem for different variations of distance- and zone-based fare structures. We start by modeling the respective fare structure mathematically, identify its main properties, and finally provide a polynomial algorithm, or prove NP-completeness of the cheapest ticket problem. We also provide general results on the combination of two fare structures, which is often observed in practice. Comment: 35 pages, revised version

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    https://doi.org/10.48550/arxiv...
    Article . 2021
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    Transportation Science
    Article . 2022 . Peer-reviewed
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      https://doi.org/10.48550/arxiv...
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    Authors: Tsaregorodtsev, Alexander; Müller, Johannes; Strohbeck, Jan; Herrmann, Martin; +2 Authors

    Monocular camera sensors are vital to intelligent vehicle operation and automated driving assistance and are also heavily employed in traffic control infrastructure. Calibrating the monocular camera, though, is time-consuming and often requires significant manual intervention. In this work, we present an extrinsic camera calibration approach that automatizes the parameter estimation by utilizing semantic segmentation information from images and point clouds. Our approach relies on a coarse initial measurement of the camera pose and builds on lidar sensors mounted on a vehicle with high-precision localization to capture a point cloud of the camera environment. Afterward, a mapping between the camera and world coordinate spaces is obtained by performing a lidar-to-camera registration of the semantically segmented sensor data. We evaluate our method on simulated and real-world data to demonstrate low error measurements in the calibration results. Our approach is suitable for infrastructure sensors as well as vehicle sensors, while it does not require motion of the camera platform. Comment: 7 pages, 3 figures, accepted at the 25th International Conference on Intelligent Transportation Systems (ITSC) 2022

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    Authors: Kachirayil, Febin; Weinand, Jann Michael; Scheller, Fabian; McKenna, Russell;

    The electrification of heating, cooling, and transportation to reach decarbonization targets calls for a rapid expansion of renewable technologies. Due to their decentral and intermittent nature, these technologies require robust planning that considers non-technical constraints and flexibility options to be integrated effectively. Energy system models (ESMs) are frequently used to support decision-makers in this planning process. In this study, 116 case studies of local, integrated ESMs are systematically reviewed to identify best-practice approaches to model flexibility and address non-technical constraints. Within the sample, storage systems and sector coupling are the most common types of flexibility. Sector coupling with the transportation sector is rarely considered, specifically with electric vehicles even though they could be used for smart charging or vehicle-to-grid operation. Social aspects are generally either completely neglected or modeled exogenously. Lacking actor heterogeneity, which can lead to unstable results in optimization models, can be addressed through building-level information. A strong emphasis on cost is found and while emissions are also frequently reported, additional metrics such as imports or the share of renewable generation are nearly entirely absent. To guide future modeling, the paper concludes with a roadmap highlighting flexibility and robustness options that either represent low-hanging fruit or have a large impact on results. Applied Energy, 324 ISSN:1872-9118 ISSN:0306-2619

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    Applied Energy
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      Applied Energy
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    Authors: Johannes Muller; Jan Strohbeck; Martin Herrmann; Michael Buchholz;

    Motion planning at urban intersections that accounts for the situation context, handles occlusions, and deals with measurement and prediction uncertainty is a major challenge on the way to urban automated driving. In this work, we address this challenge with a sampling-based optimization approach. For this, we formulate an optimal control problem that optimizes for low risk and high passenger comfort. The risk is calculated on the basis of the perception information and the respective uncertainty using a risk model. The risk model combines set-based methods and probabilistic approaches. Thus, the approach provides safety guarantees in a probabilistic sense, while for a vanishing risk, the formal safety guarantees of the set-based methods are inherited. By exploring all available behavior options, our approach solves decision making and longitudinal trajectory planning in one step. The available behavior options are provided by a formal representation of the situation context, which is also used to reduce calculation efforts. Occlusions are resolved using the external perception of infrastructure-mounted sensors. Yet, instead of merging external and ego perception with track-to-track fusion, the information is used in parallel. The motion planning scheme is validated through real-world experiments. Comment: 12 pages, 8 figures

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    IEEE Transactions on Intelligent Transportation Systems
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      IEEE Transactions on Intelligent Transportation Systems
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    Authors: Wang, Chao; Chu, Derck; Martens, Marieke; Krüger, Matti; +1 Authors

    Currently, there are still various situations in which automated driving systems (ADS) cannot perform as well as a human driver, particularly in predicting the behaviour of surrounding traffic. As humans are still surpassing state-of-the-art ADS in this task, a new concept enabling human driver to help ADS to better anticipate the behaviour of other road users was developed. Preliminary results suggested that the collaboration at the prediction level can effectively enhance the experience and comfort of ADS. For an in-depth investigation of the concept, we implemented an interactive prototype, called Prediction-level Cooperative Automated Driving system (PreCoAD), adapting an existing ADS that has been previously validated on the public road. The results of a driving simulator study among 15 participants in different highway scenarios showed that PreCoAD could enhance automated driving performance and provide a positive user experience. Follow-up interviews with participants also provided insights into the improvement of the system. Comment: 13pages, 7 figures

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    https://doi.org/10.1145/354317...
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    Authors: Pfandzelter, Tobias; Henning, Sören; Schirmer, Trever; Hasselbring, Wilhelm; +1 Authors

    In cloud event processing, data generated at the edge is processed in real-time by cloud resources. Both distributed stream processing (DSP) and Function-as-a-Service (FaaS) have been proposed to implement such event processing applications. FaaS emphasizes fast development and easy operation, while DSP emphasizes efficient handling of large data volumes. Despite their architectural differences, both can be used to model and implement loosely-coupled job graphs. In this paper, we consider the selection of FaaS and DSP from a cost perspective. We implement stateless and stateful workflows from the Theodolite benchmarking suite using cloud FaaS and DSP. In an extensive evaluation, we show how application type, cloud service provider, and runtime environment can influence the cost of application deployments and derive decision guidelines for cloud engineers. Comment: Accepted for Publication at the 10th IEEE International Conference on Cloud Engineering (IC2E 2022)

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