Architecture Design and Development of an On-board Stereo Vision System for Cooperative Automated Vehicles

Kemsaram, Narsimlu; Das, Anweshan; Dubbelman, Gijs

doi:10.1109/itsc45102.2020.9294435

Cited by 3 publications

(7 citation statements)

References 12 publications

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“…Some of the components of these systems act as independent entities that interact toward a goal. They can act as sensors that transmit data to cloud servers [16,48,55,58,62,86,101] or systems' subcomponents that hide their own data model [47,67,98,99,111].…”

Section: Data As a First Class Citizenmentioning

confidence: 99%

“…For example, systems can use API calls to collect data from data sources [10,81] or to receive requests from and send responses to end users [49] reviewed papers (i.e., 56.5%) do not adopt data coupling as data is hidden by each systems' components and these components interact using traditional process calls. They can use API calls [14,31,48,55,62,67,75,86,99,102,109] or remote procedure calls (RPC) [8,15,16,29,43,47,57,58,98,101,103,111,123,126] for communication. We found that not all the systems where components share a common data model necessarily follow the data coupling sub-principle.…”

Section: Data As a First Class Citizenmentioning

confidence: 99%

“…Some of these systems are deployed on single cloud servers [10,31,47,49,56,81,98,105], where all data is stored. Other systems are deployed on resource-constraint devices like robots [57,67,106], or small processing units (e.g., Raspberry Pis) [23,43,62]. While cloud servers are flexible and can handle big-data requirements like the ones addressed by Habibi et al [56] or Schubert et al [105], resource-constraint devices limit the amount of stored data to the point where only trained learning models are deployed [62].…”

Section: Prioritise Decentralisationmentioning

confidence: 99%

“…We found that just over half of the papers report systems where the whole decision-making process and the full learning models' life cycles happen in central nodes. Some of these works are implemented using traditional client-server architectures [10,16,47,49,56,81,98,105,116], others use sensors devices to perform basic data collection tasks [9,14,31,36,48,55,75,86,112], and others work in extreme resource constraint environments deploying the whole system in single and isolated devices [23,43,57,67,83,106].…”

Section: Prioritise Decentralisationmentioning

confidence: 99%

“…The rest of the papers (i.e., 87%) do not follow this principle. Either they are implemented as centralised architectures [2,10,14,23,43,47,49,56,57,67,81,98,105,106,112,116], or federated architectures where there are no interactions between nodes at the same layer (e.g., servers at the edge layer) [8,9,16,29,31,36,48,55,58,62,66,75,83,86,99,[101][102][103].…”

Section: Prioritise Decentralisationmentioning

confidence: 99%

See 4 more Smart Citations

Real-world Machine Learning Systems: A survey from a Data-Oriented Architecture Perspective

Cabrera¹,

Paleyes²,

Thodoroff³

et al. 2023

Preprint

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With the upsurge of interest in artificial intelligence machine learning (ML) algorithms, originally developed in academic environments, are now being deployed as parts of real-life systems that deal with large amounts of heterogeneous, dynamic, and high-dimensional data. Deployment of ML methods in real life is prone to challenges across the whole system life-cycle from data management to systems deployment, monitoring, and maintenance. Data-Oriented Architecture (DOA) is an emerging software engineering paradigm that has the potential to mitigate these challenges by proposing a set of principles to create data-driven, loosely coupled, decentralised, and open systems. However DOA as a concept is not widespread yet, and there is no common understanding of how it can be realised in practice. This review addresses that problem by contextualising the principles that underpin the DOA paradigm through the ML system challenges. We explore the extent to which current architectures of ML-based real-world systems have implemented the DOA principles. We also formulate open research challenges and directions for further development of the DOA paradigm.

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Section: Data As a First Class Citizenmentioning

confidence: 99%

Section: Data As a First Class Citizenmentioning

confidence: 99%

Section: Prioritise Decentralisationmentioning

confidence: 99%

Section: Prioritise Decentralisationmentioning

confidence: 99%

Section: Prioritise Decentralisationmentioning

confidence: 99%

See 3 more Smart Citations

Real-world Machine Learning Systems: A survey from a Data-Oriented Architecture Perspective

Cabrera¹,

Paleyes²,

Thodoroff³

et al. 2023

Preprint

View full text Add to dashboard Cite

show abstract

A model-based design of an onboard stereo vision system: obstacle motion estimation for cooperative automated vehicles

2022

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Cooperative automated vehicle software needs to use advanced software engineering design methodologies to manage the complexity of distributed software. This article presents a design model of a stereo vision system for cooperative automated vehicles based on object-oriented analysis and design methodologies and unified modeling language concepts. We use a rational unified process and the 4+1 architectural view model to design the stereo vision system. The designed model is a part of the perception system of the ego vehicle. The stereo vision system continuously perceives the traffic environment using an on-board front-facing stereo camera and sends information to the vehicle control system. The stereo vision system is developed on Ubuntu 16.04 LTS platform with the Nvidia DriveWorks framework using the C++ programming language, and it is deployed on Nvidia Drive PX2 automotive-grade embedded hardware platform. The designed and developed system is evaluated on the Carla simulation environment and the Renault Twizy cooperative automated vehicle research platform. The experimental results show that the approach is applicable, and the system is capable of running in real-time.

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A Stixel-Based Obstacle Avoidance System for Multi-Rover System

Das,

Dubbelman

2023

AIAA AVIATION 2023 Forum

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Architecture Design and Development of an On-board Stereo Vision System for Cooperative Automated Vehicles

Cited by 3 publications

References 12 publications

Real-world Machine Learning Systems: A survey from a Data-Oriented Architecture Perspective

Real-world Machine Learning Systems: A survey from a Data-Oriented Architecture Perspective

A model-based design of an onboard stereo vision system: obstacle motion estimation for cooperative automated vehicles

A Stixel-Based Obstacle Avoidance System for Multi-Rover System

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