OpenScenario: A Flexible Integrated Environment to Develop Educational Activities Based on Pedagogical Scenarios

Jullien, Jérôme; Martel, Christian; Vignollet, Laurence; Wentland, Maia

doi:10.1109/icalt.2009.24

Cited by 18 publications

(8 citation statements)

References 5 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…CARLA Scenario Runner module can be downloaded from the CARLA GitHub, obtaining an execution engine for CARLA and traffic scenario definition. These scenarios can be modified by editing an OpenSCENARIO [15] script definition where town, vehicles, climate conditions and also driving behaviours are defined. Fig.…”

Section: Qualitative Damot Evaluation In Carlamentioning

confidence: 99%

$$360^{\circ }$$ real-time and power-efficient 3D DAMOT for autonomous driving applications

Gómez-Huélamo

Egido

Bergasa

et al. 2022

Multimed Tools Appl

View full text Add to dashboard Cite

Autonomous Driving (AD) promises an efficient, comfortable and safe driving experience. Nevertheless, fatalities involving vehicles equipped with Automated Driving Systems (ADSs) are on the rise, especially those related to the perception module of the vehicle. This paper presents a real-time and power-efficient 3D Multi-Object Detection and Tracking (DAMOT) method proposed for Intelligent Vehicles (IV) applications, allowing the vehicle to track $$360^{\circ }$$ 360 ∘ surrounding objects as a preliminary stage to perform trajectory forecasting to prevent collisions and anticipate the ego-vehicle to future traffic scenarios. First, we present our DAMOT pipeline based on Fast Encoders for object detection and a combination of a 3D Kalman Filter and Hungarian Algorithm, used for state estimation and data association respectively. We extend our previous work ellaborating a preliminary version of sensor fusion based DAMOT, merging the extracted features by a Convolutional Neural Network (CNN) using camera information for long-term re-identification and obstacles retrieved by the 3D object detector. Both pipelines exploit the concepts of lightweight Linux containers using the Docker approach to provide the system with isolation, flexibility and portability, and standard communication in robotics using the Robot Operating System (ROS). Second, both pipelines are validated using the recently proposed KITTI-3DMOT evaluation tool that demonstrates the full strength of 3D localization and tracking of a MOT system. Finally, the most efficient architecture is validated in some interesting traffic scenarios implemented in the CARLA (Car Learning to Act) open-source driving simulator and in our real-world autonomous electric car using the NVIDIA AGX Xavier, an AI embedded system for autonomous machines, studying its performance in a controlled but realistic urban environment with real-time execution (results).

show abstract

Section: Qualitative Damot Evaluation In Carlamentioning

confidence: 99%

$$360^{\circ }$$ real-time and power-efficient 3D DAMOT for autonomous driving applications

Gómez-Huélamo

Egido

Bergasa

et al. 2022

Multimed Tools Appl

View full text Add to dashboard Cite

show abstract

“…Scenarios can be defined through a Python interface that allows users to easily describe sophisticated and synchronized maneuvers that involve multiple entities like vehicles, pedestrians, and other traffic participants. It also supports the OpenSCE-NARIO [176] standard file format for scenario descriptions, making it simple and efficient to incorporate a variety of existing traffic scenarios from the community. DI-Drive Casezoo [130] consists of a set of scenarios used to train and evaluate diving policy in a simulator.…”

Section: Scenario Design Platformmentioning

confidence: 99%

“…Users can read, modify, visualize, and store their own traffic scenarios using the Python API provided by CommonRoad. In addition, CommonRoad also supports more scenario specifications, such as Lanelet2 [179] and OpenSCENARIO [176].…”

Section: Scenario Design Platformmentioning

confidence: 99%

A Survey on Safety-Critical Driving Scenario Generation -- A Methodological Perspective

Ding¹,

Xu²,

Arief³

et al. 2022

Preprint

View full text Add to dashboard Cite

Autonomous driving systems have witnessed a significant development during the past years thanks to the advance in machine learning-enabled sensing and decision-making algorithms. One critical challenge for their massive deployment in the real world is their safety evaluation. Most existing driving systems are still trained and evaluated on naturalistic scenarios collected from daily life or heuristically-generated adversarial ones. However, the large population of cars, in general, leads to an extremely low collision rate, indicating that the safety-critical scenarios are rare in the collected real-world data. Thus, methods to artificially generate scenarios become crucial to measure the risk and reduce the cost. In this survey, we focus on the algorithms of safety-critical scenario generation in autonomous driving. We first provide a comprehensive taxonomy of existing algorithms by dividing them into three categories: data-driven generation, adversarial generation, and knowledge-based generation. Then, we discuss useful tools for scenario generation, including simulation platforms and packages. Finally, we extend our discussion to five main challenges of current works -fidelity, efficiency, diversity, transferability, controllability -and research opportunities lighted up by these challenges.

show abstract

“…Commonly used open source schemas such as Open-Drive and OpenScenario specified their road elements and traffic dynamic elements definitions in detail [23], [31]. Ulbrich et al [46] proposed that the elements of a scene should include test vehicles, traffic environment elements, driving task information, and specific driving behaviors.…”

Section: Scenario Ontologymentioning

confidence: 99%

A Scenario-Based Development Framework for Autonomous Driving

2020

Preprint

View full text Add to dashboard Cite

This article summarizes the research progress of scenario-based testing and development technology for autonomous vehicles. We systematically analyzed previous research works and proposed the definition of scenario, the elements of the scenario ontology, the data source of the scenario, the processing method of the scenario data, and scenario-based V-Model. Moreover, we summarized the automated test scenario construction method by random scenario generation and dangerous scenario generation.

show abstract

OpenScenario: A Flexible Integrated Environment to Develop Educational Activities Based on Pedagogical Scenarios

Cited by 18 publications

References 5 publications

$$360^{\circ }$$ real-time and power-efficient 3D DAMOT for autonomous driving applications

$$360^{\circ }$$ real-time and power-efficient 3D DAMOT for autonomous driving applications

A Survey on Safety-Critical Driving Scenario Generation -- A Methodological Perspective

A Scenario-Based Development Framework for Autonomous Driving

Contact Info

Product

Resources

About