Dr.-Ing. Sandra Gausemeier - Kontakt (Universität Paderborn)

Simulation Environment for Traffic Control Systems Targeting Mixed Autonomy Traffic Scenarios

C. Link, K. Malena, S. Gausemeier, A. Trächtler, in: Proceedings of the 9th International Conference on Vehicle Technology and Intelligent Transport Systems, SCITEPRESS - Science and Technology Publications, 2023

Abstract

DOI

The development of autonomous vehicles and their introduction in urban traffic offer many opportunities for traffic improvements. In this paper, an approach for a future traffic control system for mixed autonomy traffic environments is presented. Furthermore, a simulation framework based on the city of Paderborn is introduced to enable the development and examination of such a system. This encompasses multiple elements including the road network itself, traffic lights, sensors as well as methods to analyse the topology of the network. Furthermore, a procedure for traffic demand generation and routing is presented based on statistical data of the city and traffic data obtained by measurements. The resulting model can receive and apply the generated control inputs and in turn generates simulated sensor data for the control system based on the current system state.

Traffic Estimation and MPC-Based Traffic Light System Control in Realistic Real-Time Traffic Environments

K. Malena, C. Link, L. Bußemas, S. Gausemeier, A. Trächtler, in: Communications in Computer and Information Science, Springer International Publishing, 2022, pp. 232–254

Abstract

DOI

Modern traffic control systems are key to cope with current and future traffic challenges. In this paper information obtained from a microscopic traffic estimation using various data sources is used to feed a new developed traffic control approach. The presented method can control a traffic area with multiple traffic light systems (TLS) reacting to individual road users and pedestrians. In contrast to widespread green time extension techniques, this control selects the best phase sequence by analyzing the current traffic state reconstructed in SUMO and its predicted progress. To achieve this, the key aspect of the control strategy is to use Model Predictive Control (MPC). In order to maintain realism for real world applications, among other things, the traffic phase transitions are modelled in detail and integrated within the prediction. For the efficiency, the approach incorporates a fuzzy logic preselection of all phases reducing the computational effort. The evaluation itself is able to be easily adjusted to focus on various objectives like low occupancies, reducing waiting times and emissions, few number of phase transitions etc. determining the best switching times for the selected phases. Exemplary traffic simulations demonstrate the functionality of the MPC-based control and, in addition, some aspects under development like the real-world communication network are also discussed.

Validation of an Online State Estimation Concept for Microscopic Traffic Simulations◆

K. Malena, C. Link, S. Mertin, S. Gausemeier, A. Trächtler, in: 2021 IEEE Transportation Electrification Conference & Expo (ITEC), IEEE, 2021

Abstract

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DOI

This paper deals with a novel method for the online fitting of a microscopic traffic simulation model to the current state of a real world traffic area. The traffic state estimation is based on limited data of different measurement sources and guarantees general accordance of reality and simulation in terms of multimodal road traffic counts and vehicle speeds. The research is embedded in the challenge of improving the traffic by controlling the traffic light systems (TLS) of the examined area. Therefore, the current traffic state and the predicted route choices of individual road users are the matter of interest. The concept is generally transferable to any road traffic system. To give an impression of the accuracy and potential of the approach, the validation and first application results are presented.

Subjective Evaluation of Filter- and Optimization-Based Motion Cueing Algorithms for a Hybrid Kinematics Driving Simulator

P. Biemelt, S. Böhm, S. Gausemeier, A. Trächtler, in: Proceedings of the IEEE International Conference on Systems, Man, and Cybernetics (SMC), 2021, pp. 1619 - 1626

Online State Estimation for Microscopic Traffic Simulations using Multiple Data Sources*

K. Malena, C. Link, S. Mertin, S. Gausemeier, A. Trächtler, in: VEHITS 2021 Proceedings of the 7th International Conference on Vehicle Technology and Intelligent Transport Systems, SCITEPRESS, 2021, pp. 386-395

Abstract

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The online fitting of a microscopic traffic simulation model to reconstruct the current state of a real traffic area can be challenging depending on the provided data. This paper presents a novel method based on limited data from sensors positioned at specific locations and guarantees a general accordance of reality and simulation in terms of multimodal road traffic counts and vehicle speeds. In these considerations, the actual purpose of research is of particular importance. Here, the research aims at improving the traffic flow by controlling the Traffic Light Systems (TLS) of the examined area which is why the current traffic state and the route choices of individual road users are the matter of interest. An integer optimization problem is derived to fit the current simulation to the latest field measurements. The concept can be transferred to any road traffic network and results in an observation of the current multimodal traffic state matching at the given sensor position. First case studies show promosing results in terms of deviations between reality and simulation.

https://www.scitepress.org/PublicationsDetail.aspx?ID=3xZWfOSENWk=&t=1 - (confirmation)

Design and Objective Evaluation of Filter- and Optimization-based Motion Cueing Strategies for a Hybrid Kinematics Driving Simulator with 5 Degrees of Freedom

P. Biemelt, S. Gausemeier, A. Trächtler, International Journal On Advances in Systems and Measurements (2020), 13(3 & 4), pp. 203-219

Design and Evaluation of a Novel Filter-Based Motion Cueing Strategy for a Hybrid Kinematics Driving Simulator with 5 Degrees of Freedom

P. Biemelt, S. Mertin, N. Rüddenklau, S. Gausemeier, A. Trächtler, in: Proceedings of the Driving Simulation Conference Europe VR, Driving Simulation Association, 2020, pp. 85-92

Macroscopic Traffic Flow Control using Consensus Algorithms

S. Mertin, K. Malena, C. Link, S. Gausemeier, A. Trächtler, in: The 23rd IEEE International Conference on Intelligent Transportation Systems, International Conference on Intelligent Transportation Systems (ITSC), 2020

A Model-Based Online Reference Prediction Strategy for Model Predictive Motion Cueing Algorithms

P. Biemelt, C. Link, S. Gausemeier, A. Trächtler, in: Proceedings of the 21st IFAC World Congress, 2020, pp. 6082 - 6088

Objective Evaluation of a Novel Filter-Based Motion Cueing Algorithm in Comparison to Optimization-Based Control in Interactive Driving Simulation

P. Biemelt, S. Mertin, N. Rüddenklau, S. Gausemeier, A. Trächtler, in: Proceedings of the International Conference on Advances in System Simulation (SIMUL), IARIA, 2019

Simulation-Based Lighting Function Development of High-Definition Headlamps

N. Rüddenklau, P. Biemelt, S. Mertin, S. Gausemeier, A. Trächtler, in: 13th International Symposium on Automotive Lighting (ISAL), utzverlag GmbH, 2019, pp. 677-686

Proof-of-Concept einer komplexen Co-Simulationsumgebung für einen Fahrsimulator zur Untersuchung von Car2X-Kommunikations-Szenarien

S. Mertin, D. Buse, M. Franke, A. Trächtler, S. Gausemeier, F. Dressler, in: VDI/VDE AUTOREG 2019, VDI Verlag Düsseldorf, 2019, pp. 159-170

Hardware-in-the-Loop Simulation of High-Definition Headlamp Systems

N. Rüddenklau, S. Gausemeier, A. Trächtler, in: VDI/VDE AUTOREG 2019, VDI- Verlag, Düsseldorf, 2019

Real-Time Lighting of High-Definition Headlamps for Night Driving Simulation

N. Rüddenklau, P. Biemelt, S. Mertin, S. Gausemeier, A. Trächtler, in: IARIA SysMea, IARIA, 2019, pp. 72-88

Shader-Based Realtime Simulation of High-Definition Automotive Headlamps

N. Rüddenklau, P. Biemelt, S. Henning, S. Gausemeier, A. Trächtler, in: SIMUL 2018, The Tenth International Conference on Advances in System Simulation, IARIA, 2018

A Simulation Framework for Testing a Conceptual Hierarchical Autonomous Traffic Management System including an Intelligent External Traffic Simulation

S. Henning, P. Biemelt, N. Rüddenklau, S. Gausemeier, A. Trächtler, in: Proceedings of the DSC 2018 Europe VR: New trends in Human in the Loop simulation and testing. Driving simulation and VR, Driving Simulation Association, 2018, pp. 91-98

A Model Predictive Motion Cueing Strategy for a 5-Degree-of-Freedom Driving Simulator with Hybrid Kinematics

P. Biemelt, S. Henning, N. Rüddenklau, S. Gausemeier, A. Trächtler, in: Proceedings of the Driving Simulation Conference Europe VR (DSC), 2018, pp. 79-85

An Application-Oriented Design Method for Networked Driving Simulation

K. Abdelgawad, J. Gausemeier, A. Trächtler, S. Gausemeier, R. Dumitrescu, J. Berssenbrügge, J. Stöcklein, M. Grafe, Designs ‒ International Journal of Engineering Designs, Band 1 (2017), 1, pp. 6.1-6.47

Modellbasierte Untersuchung der Zuverlässigkeit algorithmisch bestimmter kritischer Stellen in Straßennetzwerken

S. Henning, P. Biemelt, K. Abdelgawad, S. Gausemeier, A. Trächtler, in: VDI/VDE (AUTOREG 2017), VDI-Verlag, Düsseldorf, 2017

Networked Driving Simulation for Future Autonomous and Cooperative Vehicle Systems

K. Abdelgawad, S. Henning, P. Biemelt, S. Gausemeier, A. Trächtler, in: VDI/VDE (AUTOREG 2017), VDI-Verlag, Düsseldorf, 2017

Methodology for Determining Critical Locations in Road Networks based on Graph Theory

S. Henning, P. Biemelt, K. Abdelgawad, S. Gausemeier, A. Trächtler, in: IFAC World Congress 2017, IFAC, 2017

Advanced Traffic Simulation Framework for Networked Driving Simulators

K. Abdelgawad, S. Henning, P. Biemelt, S. Gausemeier, A. Trächtler, in: AAC2016 (IFAC), 8th IFAC Symposium on Advances in Automotive Control (AAC 2016), IFAC, 2016

Flexible Operation Workflow of a Driving Simulation Center for ADAS Development

K. Abdelgawad, B. Hassan, A. Kohlstedt, J. Stöcklein, J. Berssenbrügge, M. Grafe, S. Gausemeier, K. Jäker, A. Trächtler, in: New Developments in Driving Simulation Design and Experiments, Driving Simulation Conference, 2015

Flexible Operation Workflow of a Driving Simulation Center for ADAS Development

K. Abdelgawad, B. Hassan, A. Kohlstedt, J. Stöcklein, J. Berssenbrügge, M. Grafe, S. Gausemeier, K. Jäker, A. Trächtler, in: New Developments in Driving Simulation Design and Experiments, Driving Simulation Conference, 2015

Entwicklung eines prädiktiven Motion-Cueing-Verfahrens für den ATMOS-Fahrsimulator

D. Zimmermann, A. Kohlstedt, S. Gausemeier, A. Trächtler, in: 12. Paderborner Workshop Augmented & Virtual Reality in der Produktentstehung, Verlagsschriftenreihe des Heinz Nixdorf Instituts, Paderborn, 2015, pp. 261-272

Subjective Evaluation of Different Motion Cueing Algorithms Implemented on ATMOS Driving Simulator

I. Al Qaisi, D. Zimmermann, A. Kohlstedt, S. Gausemeier, A. Trächtler, in: Driving Simulation Conference 2014, 2014

Ein Fahrerassistenzsystem zur prädiktiven Planung energie- und zeitoptimaler Geschwindigkeitsprofile mittels Mehrzieloptimierung

S.F. Gausemeier, Verlagsschriftenreihe des Heinz Nixdorf Instituts, Paderborn, 2013

Fahrerassistenzsystem für energie- und zeitoptimales Fahren durch prädiktive Geschwindigkeitsprofil-Planung

S. Gausemeier, 2012

Fahrerassistenzsystem für energie- und zeitoptimales Fahren durch prädiktive Geschwindigkeitsprofil-Planung

S. Gausemeier, A. Trächtler, K. Jäker, 13. Braunschweiger Symposium AAET (2012)