COPADRIVe - A Realistic Simulation Framework for Cooperative Autonomous Driving Applications

Vieira, Bruno Ferreira; Severino, Ricardo; Filho, Ênio Vasconcelos; Koubâa, Anis; Tovar, Eduardo

doi:10.1109/iccve45908.2019.8965161

Cited by 17 publications

(6 citation statements)

References 10 publications

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“…The Packet Delivery Rate (PDR) under PSP is also evaluated, specifically in congested network conditions. These results extend previous work [16], [17] by carrying out an integrated analysis of the control and networking perspective in four Co-VP scenarios.…”

Section: Introductionsupporting

confidence: 86%

“…The CAM trigger threshold values are defined in [46]; for convenience, we refer to this set of values as the Basic Service [Transmission Trigger] Profile (BSP), following [17]. The threshold values triggers are defined within an upper (T max ) and lower (T min ) messages bound times and kinematics triggers to check e δ i+1 and e θ i+1 comparing SV i+1 data with the received one from SV i .…”

Section: Exploring Trigger Thresholds For Cam Messages a Current Etsi...mentioning

confidence: 99%

“…In [12], ETSI defines some ITS use cases, including a Co-VP situation, where it reduces T max to 0.5ms. This use case is defined as BSP for platooning (BSP-P) in [17]. This change causes that, in a straight line, a platoon member whose constant velocity is greater than or equal to 6.67m/s will transmit a CAM by trigger τ Speed instead of T max , unless another trigger is detected.…”

Section: Exploring Trigger Thresholds For Cam Messages a Current Etsi...mentioning

confidence: 99%

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Improving the Performance of Cooperative Platooning With Restricted Message Trigger Thresholds

et al. 2022

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Cooperative Vehicular Platooning (Co-VP) is one of the most prominent and challenging applications of Intelligent Traffic Systems. To support such vehicular communications, the ETSI ITS G5 standard specifies event-based communication profiles, triggered by kinematic parameters such as speed. The standard defines a set of threshold values for such triggers but no careful assessment in realistic platooning scenarios has been done to confirm the suitability of such values. In this work, we investigate the safety and performance limitations of such parameters in a realistic platooning co-simulation environment. We then propose more conservative threshold values, that we formalize as a new profile, and evaluate their impact in the longitudinal and lateral behaviour of a vehicular platoon as it carries out complex driving scenarios. Furthermore, we analyze the overhead introduced in the network by applying the new threshold values. We conclude that a pro-active message transmission scheme leads to improved platoon performance for highway scenarios, notably an increase greater than 40% in the longitudinal performance of the platoon, while not incurring in a significant network overhead. The obtained results also demonstrated an improved platoon performance for semi-urban scenarios, including obstacles and curves, where the heading error decreases in 26%, with slight network overhead.

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Section: Introductionsupporting

confidence: 86%

Section: Exploring Trigger Thresholds For Cam Messages a Current Etsi...mentioning

confidence: 99%

Section: Exploring Trigger Thresholds For Cam Messages a Current Etsi...mentioning

confidence: 99%

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Improving the Performance of Cooperative Platooning With Restricted Message Trigger Thresholds

et al. 2022

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“…Both implementations do not have the ability to simulate physical phenomena since there is not a physics engine-based simulator. Finally, the work in [19] integrated Gazebo with Artery for supporting cooperative scenarios such as platooning.…”

Section: Integrated Simulatorsmentioning

confidence: 99%

Open-Source Integrated Simulation Framework for Cooperative Autonomous Vehicles

Anagnostopoulos

Koulamas

Lalos

et al. 2022

2022 11th Mediterranean Conference on Embedded Computing (MECO)

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While many mature and reliable simulation engines exist for different system components, such as the network or the sensing and physics subsystems, the integration of these simulators into a single framework and workflow is not always a straightforward task. This paper presents such an integrated simulation framework, built from available open source components, focusing on cooperative autonomous vehicles research and development. The framework combines the CARLA simulation engine with the ETSI ITS-G5 implementation of the Artery/OMNET++ network simulator, as well as with selected functionality available in ROS, in order to provide a complete and high-fidelity integrated simulation environment which can be exploited for the development and testing of unaltered final code running in ROS-enabled devices.

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“…Among the most relevant applications that autonomous driving includes are adaptive cruise control, emergency braking, precise steering control, autonomous parking, precision approach and narrow lane driving for transit buses, door-to-door transport for the elderly, automated heavy truck platoon, automatic driving in emergencies [8,9]. These applications represent a skill set that enables safe driving along a lane on the road.…”

Section: Introductionmentioning

confidence: 99%

Dynamic Simulation and Kinematic Control for Autonomous Driving in Automobile Robots

Zea

Guevara

Recalde

et al. 2020

Advances in Intelligent Systems and Computing

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This article proposes a simple simulation methodology that allows to experiment with the dynamic behavior of vehicles, which applies control laws that allow automated driving in unstructured environments, through the use of robotic application simulation software Webots, which shortens the experimentation times of autonomous driving systems, It also allows to overcome the limitations that this type of projects involves, such as, high infrastructure costs, the difficulties of validating the system, qualified personnel and the participation of various elements with different dynamic behaviors that make up a real traffic space. The use of the virtualized model of a BMW X5 vehicle and the instrumentation of multiple sensors necessary for its operation are presented. Finally, a path tracking algorithm is developed using Matlab scientific programming software, and the dynamic behavior of the vehicle is evaluated through the response curves of the robot states, these results represent the starting point for future research and the implementation of physical tests.

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COPADRIVe - A Realistic Simulation Framework for Cooperative Autonomous Driving Applications

Cited by 17 publications

References 10 publications

Improving the Performance of Cooperative Platooning With Restricted Message Trigger Thresholds

Improving the Performance of Cooperative Platooning With Restricted Message Trigger Thresholds

Open-Source Integrated Simulation Framework for Cooperative Autonomous Vehicles

Dynamic Simulation and Kinematic Control for Autonomous Driving in Automobile Robots

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