To assess the performance and safety implications of C-ITS services, simulation plays a crucial role. However, obtaining reliable simulation data is challenging, especially during the initial stages of C-ITS service d...
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ISBN:
(纸本)9798350399462
To assess the performance and safety implications of C-ITS services, simulation plays a crucial role. However, obtaining reliable simulation data is challenging, especially during the initial stages of C-ITS service development where empirical data is limited. This limitation hampers the ability to accurately represent and analyze human behavior in simulation models. The primary challenge arises from the unpredictable nature of human behavior, which can trigger unexpected situations that may not align optimally with the intended behavior of ITS systems. These instances can create unfavorable conditions and compromise safety. To address this challenge, our study focuses on exploring the uncertainty that emerges from the dynamic interaction between road users and ITS systems. We examine how uncertainties in human behavior and the corresponding responses of ITS systems impact safety within the C-ITS environment. In our research, we employ a real-life case study conducted at the Eindhoven test site to model and simulate uncertainties among pedestrians, cyclists, and taxi drivers in relation to the Warning System for Pedestrian (WSP) C-ITS service. We gain valuable insights into the potential outcomes and safety implications, that have been shared with both the Eindhoven municipality and the C-MobILE project.
Urban modeling and simulation are critical for addressing urbanization challenges. Optimizing and scaling these simulations can significantly reduce simulation time and resource usage, enabling faster decision making ...
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ISBN:
(纸本)9798350385939;9798350385922
Urban modeling and simulation are critical for addressing urbanization challenges. Optimizing and scaling these simulations can significantly reduce simulation time and resource usage, enabling faster decision making and policy formulation. This paper investigates the performance optimization and scalability of the twin-building case. The study covers various optimization techniques, including compiler-level switches, MPI-specific binding flags, optimal decomposition strategies, and the utilization of vendor-specific compilers. Through extensive experimentation, a significant performance boost was achieved, increasing the performance by approximately 47 times and reducing the simulation time to 46 seconds. This was accomplished by scaling the prototype Twin Building 26.17M case across more than 1,000 CPU-only cores. These findings underscore the importance of performance optimization strategies in effectively harnessing computational resources for large-scale urban modelingsimulations. The study improves performance and serves as a basis for future research on heterogeneous computing platforms to enhance simulation time.
Simulators are widely used in nuclear industry, both for powerplant design and for operator's training purposes. Most of simulators are implemented in a compact, non-editable and area-specified software, customize...
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Simulators are widely used in nuclear industry, both for powerplant design and for operator's training purposes. Most of simulators are implemented in a compact, non-editable and area-specified software, customized for a given type of powerplant. Although there are several types of simulation software, there is currently no solution that could perform a more general and customizable way to simulate the thermal power variation of a nuclear reactor. This paper aims to present modeling, simulating and control implementation of the thermal power of nuclear reactors.
How individuals' movement decisions lead to complex, large-scale behavior of crowds is a central subject in crowd modeling and simulation. Understanding this multiscale, emergent phenomenon can provide deeper insi...
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ISBN:
(纸本)9781665488679
How individuals' movement decisions lead to complex, large-scale behavior of crowds is a central subject in crowd modeling and simulation. Understanding this multiscale, emergent phenomenon can provide deeper insights into social dynamics in a crowd, and can help design real world applications such as evacuation planning systems. Crowd simulation is generally computationally intensive, especially when complex motion planning constraints are imposed on individual actors. Furthermore, altering such constraints requires major changes in the simulation engine. An effective way to deal with these issues is the use of intangible social factors (proxies). Proxies are agent-like entities that are dynamically generated and destroyed. They can be combined with a generic, domain-independent motion planner for computationally efficient simulation. These proxies are generally generated and destroyed based on a fixed set of rules, mimicking intangible social factors among individuals. In this paper, we propose the use of evolving neural networks (Neuroevolution of Augmenting Topologies, NEAT) to dynamically control the use of proxies. Our results show that the neural networks evolve to dynamically utilize the proxies, and proxy use increases performance in a simple evacuation task. These results suggest that proxy rules can be learned based on loosely defined fitness goals. We expect our method to be applicable to more complex behavioralmodeling and simulation domains, beyond crowd modeling.
This work proposes a new representation of pedestrian crossing scenarios and a hybrid modeling approach, RePed, that facilitates transferring microscopic behavior models from behavior research to higher-level trajecto...
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ISBN:
(纸本)9798350384581;9798350384574
This work proposes a new representation of pedestrian crossing scenarios and a hybrid modeling approach, RePed, that facilitates transferring microscopic behavior models from behavior research to higher-level trajectories. With this, real-world trajectory-based scenarios can be augmented with a diverse set of human crossing maneuvers, producing a wealth of new scenarios and addressing the scarcity of rare case data that existing works struggle to deal with. Leveraging the controllability of this modeling approach, perturbation-based augmentation can be applied to enrich scenarios further. In addition, the representation is rooted in the Ego vehicle's coordinate system with a logical representation of roads. This design enables scenario retargeting to various road structures, traffic conditions, and ego vehicle behaviors. Thus, it strongly supports scenario-based testing by forcing pedestrians to produce certain situations in simulation even when the Ego Vehicle tries to evade them.
simulation is a key technology in robotics as it enables the generation of environmental data and testing scenarios for development and maintenance purposes. However, simulations are an imperfect representation of the...
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ISBN:
(纸本)9798350384581;9798350384574
simulation is a key technology in robotics as it enables the generation of environmental data and testing scenarios for development and maintenance purposes. However, simulations are an imperfect representation of the real-world and the so-called sim-to-real gap between simulation and reality hinders the deployment of virtual developed solutions without additional effort. modeling complex systems like highly dynamic and holonomic mobile robots presents additional complexities in simulation. This paper addresses these challenges through a case study on creating a model for a highly dynamic logistics robot. The study considers the modeling of the entire system down to creating suitable colliders for the rollers of a Mecanum wheel. Additionally, the impact of significant physics parameters is presented. To bridge the sim-to-real gap, a pipeline is developed that utilizes a Motion Capture system to compare the behavior of a real robot with its simulated counterpart across various motions. By leveraging expert knowledge gained from the real-world data, the simulation model is manually tuned to replicate complex system behaviors, such as sliding effects.
In this work, we propose PedGrid, a grid-based simulator based on the OpenAI Gymnasium framework, to model pedestrian behavior for autonomous driving simulation. The simulator enables behavior modeling using both rule...
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ISBN:
(纸本)9798350399462
In this work, we propose PedGrid, a grid-based simulator based on the OpenAI Gymnasium framework, to model pedestrian behavior for autonomous driving simulation. The simulator enables behavior modeling using both rule-based and learning-based techniques. Simplified world and actor descriptions allow for rapid implementation of new approaches to provide preliminary findings. The simulator has a set of modules for defining behavioral agents and collecting data for use in various sorts of pedestrian behavior studies. We compare the findings of two pedestrian behavior research to confirm the simulator's validity. We also assess the scaling performance of PedGrid by analyzing run-time vs. pedestrian count.
Quartz crystal oscillators are fundamental components in electronic circuits with stringent time requirements;providing a proper crystal oscillator model for simulation is crucial for Electromagnetic Compatibility (EM...
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ISBN:
(纸本)9784885523472;9798350349498
Quartz crystal oscillators are fundamental components in electronic circuits with stringent time requirements;providing a proper crystal oscillator model for simulation is crucial for Electromagnetic Compatibility (EMC) and Signal Integrity (SI) analysis. This paper presents two types of behavioral models of quartz oscillators for EMC-oriented circuit simulations. These behavioral models allow the oscillator to be simulated without the need to resort to the complete oscillator circuit. The proposed models are tested in simulation of four oscillators, operating at different frequencies. These models provide a tool for early-stage analysis of EMC and SI performance in electronic systems.
Currently, many of the problems studied around mobile robotics aim to solve the provision of greater autonomy. This paper review the field of mobile robotics with sliding wheels and differential traction. The main con...
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ISBN:
(纸本)9798350373981;9798350373974
Currently, many of the problems studied around mobile robotics aim to solve the provision of greater autonomy. This paper review the field of mobile robotics with sliding wheels and differential traction. The main contributions are: the use of specialized tools (software) to simulate the various stages of modeling and for the built of prototype. Specifically, the MatLab Simulink (R) software is used for the simulation of the model exported from SolidWorks to the Simulink environment integrated with the controller design. Also, as mentioned before, SolidWorks for the project and simulation of the robot's mechanical components (Simscape application for multi-body mechanical systems). Desired trajectories are generated through parametric functions, continuous lines from specific points through interpolation techniques and using desired speeds. Control laws, and trajectory tracking are based on kinematic and dynamic models. The results of simulation are presented and analyzed. Finally, the prototype and the experimental results are presented.
Due to the transition to renewable energies, electricity markets need to be made fit for purpose. To enable the comparison of different energy market designs, modeling tools covering market actors and their heterogene...
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ISBN:
(纸本)9798350381757;9798350381740
Due to the transition to renewable energies, electricity markets need to be made fit for purpose. To enable the comparison of different energy market designs, modeling tools covering market actors and their heterogeneous behavior are needed. Agent-based models are ideally suited for this task. Such models can be used to simulate and analyze changes to market design or market mechanisms and their impact on market dynamics. In this paper, we conduct an evaluation and comparison of two actively developed open-source energy market simulation models. The two models, namely AMIRIS and ASSUME, are both designed to simulate future energy markets using an agent-based approach. The assessment encompasses modelling features and techniques, model performance, as well as a comparison of model results, which can serve as a blueprint for future comparative studies of simulation models. The main comparison dataset includes data of Germany in 2019 and simulates the Day-Ahead market and participating actors as individual agents. Both models are comparable close to the benchmark dataset with a MAE between 5.6 and 6.4 (sic)/MWh while also modeling the actual dispatch realistically.
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