Distributed Real-Time Traffic Simulation for Autonomous Vehicle Testing in Urban Environments

Sippl, Christoph; Schwab, Benedikt; Kielar, Peter M.; Djanatliev, Anatoli

doi:10.1109/itsc.2018.8569544

Cited by 10 publications

(7 citation statements)

References 24 publications

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“…The testing and evaluation of automated vehicles can be performed on real roads or in virtual environments [38]. Considering that several millions of test kilometers must be completed to effectively test and evaluate automated vehicles [39], it can be concluded that the real testing and evaluation of automated vehicles are limited by factors such as cost, time, and scalability [40]. Thereby, the virtual environment was first adopted to test and evaluate automated vehicles in this paper to verify the effectiveness of the proposed method.…”

Section: Examples Of the Subjective And Objective Evaluation Of Autom...mentioning

confidence: 99%

An Evaluation Method for Automated Vehicles Combining Subjective and Objective Factors

Wang

et al. 2023

Machines

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The rapid development of automated vehicle technology requires reasonable test scenarios and comprehensive evaluation methods. This paper proposes an evaluation method for automated vehicles combining subjective and objective factors. First, we propose a method for automatically generating test scenarios and for batch testing autonomous vehicles. Then, the use of the target layer, total index layer, and index layer of automated vehicles is proposed to establish a more comprehensive evaluation system for automated vehicles. Specifically, the analytic hierarchy process (AHP, subjective) and improved criteria importance though intercriteria correlation (CRITIC, objective) methods are used to determine the weight of the indicators, and a two-level fuzzy comprehensive (subjective and objective) evaluation method is adopted to comprehensively evaluate the performance of the automated vehicles. Finally, the effectiveness of the proposed evaluation method combining subjective and objective factors is verified through virtual simulations and real-world experiments. Through a combination of subjective and objective methods, improved results can be obtained for safety, efficiency, economy, intelligence, and comfort tests.

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Section: Examples Of the Subjective And Objective Evaluation Of Autom...mentioning

confidence: 99%

An Evaluation Method for Automated Vehicles Combining Subjective and Objective Factors

Wang

et al. 2023

Machines

View full text Add to dashboard Cite

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“…It is possible to define path and motion sequences for pedestrians, but an absence of pedestrian behavior models is prevalent. The simulation of Vulnerable Road Users (VRUs) and their interaction with automated vehicles becomes particularly important for validating automated driving functions in urban environments [18]. Even though MomenTUM was not initially tailored towards the validation of driving functions, the framework with its already implemented behavior models can be used to evaluate new behavior modeling approaches.…”

Section: Runtime Of the Environment Simulationmentioning

confidence: 99%

“…At the strategic level, the pedestrian's target selection is modeled using an Origin-Destination (OD) matrix with its respective areas shown in Figure 8. Since the objective of this work is to research road space modeling, we refer to Sippl et al for a more detailed discussion on the used behavior models [18].…”

Section: Runtime Of the Environment Simulationmentioning

confidence: 99%

“…However, there is presently no testing framework that can satisfy all the requirements [14]. The linking of individual existing tools to a holistic and distributed test framework can thus represent a solution and is currently being pursued [15][16][17][18]. In the context of environment simulation not only the dynamic objects must be exchanged at runtime, but also the static environment models must be available for all individual simulators.…”

Section: Introductionmentioning

confidence: 99%

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Spatio-Semantic Road Space Modeling for Vehicle–Pedestrian Simulation to Test Automated Driving Systems

2020

Self Cite

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Automated driving technologies offer the opportunity to substantially reduce the number of road accidents and fatalities. This requires the development of systems that can handle traffic scenarios more reliable than the human driver. The extreme number of traffic scenarios, though, causes enormous challenges in testing and proving the correct system functioning. Due to its efficiency and reproducibility, the test procedure will involve environment simulations to which the system under test is exposed. A combination of traffic, driving and Vulnerable Road User (VRU) simulation is therefore required for a holistic environment simulation. Since these simulators have different requirements and support various formats, a concept for integrated spatio-semantic road space modeling is proposed in this paper. For this purpose, the established standard OpenDRIVE, which describes road networks with their topology for submicroscopic driving simulation and HD maps, is combined with the internationally used semantic 3D city model standard CityGML. Both standards complement each other, and their combination opens the potentials of both application domains—automotive and 3D GIS. As a result, existing HD maps can now be used by model processing tools, enabling their transformation to the target formats of the respective simulators. Based on this, we demonstrate a distributed environment simulation with the submicroscopic driving simulator Virtual Test Drive and the pedestrian simulator MomenTUM at a sensitive crossing in the city of Ingolstadt. Both simulators are coupled at runtime and the architecture supports the integration of automated driving functions.

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“…Sippl et al [29] developed a distributed real-time traffic simulation for autonomous vehicle testing in urban environments. In their model, the synchronization of the Automotive Data and Time Triggered Framework instance and the traffic simulation in Virtual Test Drive is done by the connection toolbox to synchronize Electronic Control Unit and Runtime Data Bus/Simulation Control Protocol data exchange.…”

Section: Paramics Domain Decompositionmentioning

confidence: 99%

Graphical Analysis of Rollback Process in Ad Hoc Distributed Traffic Simulation

Suh

2020

Applied Sciences

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Recent advancements in sensor, mobile computing, and wireless communication technologies is creating new opportunities to effectively exploit real-time traffic data. Onboard vehicles collect, process, simulate traffic states in a distributed fashion and a local transportation management center coordinates the overall simulation with an optimistic execution technique. Such a distributed approach can provide more up-to-date and robust estimates with decreased communication bandwidth requirements and increased computing capacity. This paper proposes an online ad hoc distributed simulation. The physical operating platform for the model including operating system, communicational middleware, and traffic simulation model are described. Also, this paper investigates the analytical background of rollback process of the proposed ad hoc distributed simulation model. Flow rate diagram and cumulative number of vehicle diagram show that the overall system simulation speed and estimate accuracy may differ significantly as a function of the selected threshold.

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Distributed Real-Time Traffic Simulation for Autonomous Vehicle Testing in Urban Environments

Cited by 10 publications

References 24 publications

An Evaluation Method for Automated Vehicles Combining Subjective and Objective Factors

An Evaluation Method for Automated Vehicles Combining Subjective and Objective Factors

Spatio-Semantic Road Space Modeling for Vehicle–Pedestrian Simulation to Test Automated Driving Systems

Graphical Analysis of Rollback Process in Ad Hoc Distributed Traffic Simulation

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