Development and Validation of ADAS Perception Application in ROS Environment Integrated with CARLA Simulator

Stevic, Stevan; Krunić, Momčilo; Dragojević, Marko; Kaprocki, Nives

doi:10.1109/telfor48224.2019.8971063

Cited by 16 publications

(6 citation statements)

References 5 publications

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“…However, the installation process is very similar for both ROS and ROS2. In fact, the CARLA community has an extensive collection of manuals and code developed in ROS, allowing for straightforward integration, as demonstrated in various previous works [17,18].…”

Section: Ros-robot Operating Systemmentioning

confidence: 99%

An Urban Traffic Dataset Composed of Visible Images and Their Semantic Segmentation Generated by the CARLA Simulator

Rosende,

Gavilán,

Fernández-Andrés

et al. 2023

Data

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A dataset of aerial urban traffic images and their semantic segmentation is presented to be used to train computer vision algorithms, among which those based on convolutional neural networks stand out. This article explains the process of creating the complete dataset, which includes the acquisition of the images, the labeling of vehicles, pedestrians, and pedestrian crossings as well as a description of the structure and content of the dataset (which amounts to 8694 images including visible images and those corresponding to the semantic segmentation). The images were generated using the CARLA simulator (but were like those that could be obtained with fixed aerial cameras or by using multi-copter drones) in the field of intelligent transportation management. The presented dataset is available and accessible to improve the performance of vision and road traffic management systems, especially for the detection of incorrect or dangerous maneuvers.

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Section: Ros-robot Operating Systemmentioning

confidence: 99%

An Urban Traffic Dataset Composed of Visible Images and Their Semantic Segmentation Generated by the CARLA Simulator

Rosende,

Gavilán,

Fernández-Andrés

et al. 2023

Data

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“…A tool coupling solution for the 3D vehicle and environment simulator CARLA, which is also used in this paper, is presented by Stevic et al [20]. ROS and Autoware as prototyping platforms were connected to CARLA using a ROS bridge component for the simulator.…”

Section: Related Workmentioning

confidence: 99%

“…With the presented feature set and as one of the most widely used simulators in ADS development (see Refs. [9], [31], [20]), CARLA qualifies for the DCP slave role.…”

Section: Use Case Definitionmentioning

confidence: 99%

Simulator Coupled with Distributed Co-Simulation Protocol for Automated Driving Tests

et al. 2021

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To meet the challenges in software testing for automated vehicles, such as increasing system complexity and an infinite number of operating scenarios, new simulation methods must be developed. Closed-loop simulations for automated driving (AD) require highly complex simulation models for multiple controlled vehicles with their perception systems as well as their surrounding context. For the realization of such models, different simulation domains must be coupled with co-simulation. However, widely supported model integration standards such as functional mock-up interface (FMI) lack native support for distributed platforms, which is a key feature for AD due to the computational intensity and platform exclusivity of certain models. The newer FMI companion standard distributed co-simulation protocol (DCP) introduces platform coupling but must still be used in conjunction with AD co-simulations. As part of an assessment framework for AD, this paper presents a DCP compliant implementation of an interoperable interface between a 3D environment and vehicle simulator and a co-simulation platform. A universal Python wrapper is implemented and connected to the simulator to allow its control as a DCP slave. A C-code-based interface enables the co-simulation platform to act as a DCP master and to realize cross-platform data exchange and time synchronization of the environment simulation with other integrated models. A model-in-the-loop use case is performed with the traffic simulator CARLA running on a Linux machine connected to the co-simulation master xMOD on a Windows computer via DCP. Several virtual vehicles are successfully controlled by cooperative adaptive cruise controllers executed outside of CARLA. The standard compliance of the implementation is verified by exemplary connection to prototypic DCP solutions from 3rd party vendors. This exemplary application demonstrates the benefits of DCP compliant tool coupling for AD simulation with increased tool interoperability, reuse potential, and performance.

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“…The associate editor coordinating the review of this manuscript and approving it for publication was Prof. Miroslav Lutovac. [23].…”

Section: Iisimulatorsmentioning

confidence: 99%

Development of ADAS perception applications in ROS and "Software-In-the-Loop" validation with CARLA simulator

et al. 2020

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Higher levels of autonomous driving are bringing sophisticated requirements and unpredicted challenges. In order to solve these problems, the set of functionalities in modern vehicles is growing in terms of algorithmic complexity and required hardware. The risk of testing implemented solutions in real world is high, expensive and time consuming. This is the reason for virtual automotive simulation tools for testing are heavily acclaimed. Original Equipment Manufacturers (OEMs) use these tools to create closed sense, compute, act loop to have realistic testing scenarios. Production software is tested against simulated sensing data. Based on these inputs a set of actions is produced and simulated which generates consequences that are evaluated. This creates a possibility for OEMs to minimize design errors and optimize costs of the vehicle production before any physical prototypes are produced. This paper presents the development of simple C++/Python perception applications that can be used in driver assistance functionalities. Using ROS as a prototyping platform these applications are validated and tested with "Software-In-the Loop" (SIL) method. CARLA simulator is used as a generator for input data and output commands of the autonomous platform are executed as simulated actions within simulator. Validation is done by connecting Autoware autonomous platform with CARLA simulator in order to test against various scenes in which applications are applicable. Vision based lane detection, which is one of the prototypes, is also tested in a real world scenario to demonstrate the applicability of algorithms developed with simulators to real-time processing

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Development and Validation of ADAS Perception Application in ROS Environment Integrated with CARLA Simulator

Cited by 16 publications

References 5 publications

An Urban Traffic Dataset Composed of Visible Images and Their Semantic Segmentation Generated by the CARLA Simulator

An Urban Traffic Dataset Composed of Visible Images and Their Semantic Segmentation Generated by the CARLA Simulator

Simulator Coupled with Distributed Co-Simulation Protocol for Automated Driving Tests

Development of ADAS perception applications in ROS and "Software-In-the-Loop" validation with CARLA simulator

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