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A Systematic Review of Perception System and Simulators for Autonomous Vehicles Research
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This paper presents a systematic review of the perception systems and simulators for autonomous vehicles (AV). This work has been divided into three parts. In the first part, perception systems are categorized as environment perception systems and positioning estimation systems. The paper presents the physical fundamentals, principle functioning, and electromagnetic spectrum used to operate the most common sensors used in perception systems (ultrasonic, RADAR, LiDAR, cameras, IMU, GNSS, RTK, etc.). Furthermore, their strengths and weaknesses are shown, and the quantification of their features using spider charts will allow proper selection of different sensors depending on 11 features. In the second part, the main elements to be taken into account in the simulation of a perception system of an AV are presented. For this purpose, the paper describes simulators for model-based development, the main game engines that can be used for simulation, simulators from the robotics field, and lastly simulators used specifically for AV. Finally, the current state of regulations that are being applied in different countries around the world on issues concerning the implementation of autonomous vehicles is presented.
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“The Global Positioning System (GPS) is the most common GNSS system freely available to be used in any part of the world [111].”
From Sensor-Based Prognostic Health Management of Advanced Driver Assistance System for Autonomous Vehicles: A Recent Survey (2022) · cites this paper as [111]
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“It is mentioned that a pure vision-based system has advantages like affordability and simplicity of implementation.”
From Object Detection in Autonomous Vehicles under Adverse Weather: A Review of Traditional and Deep Learning Approaches (2024) · cites this paper as [48]
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“Such simulation not only includes software simulation like CarSim and CARLA. but also includes hybrid realization with hardware-in-the-loop or vehicle-in-the-loop design [67].”
From Trustworthy AI: From Principles to Practices (2023) · cites this paper as [67]
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“Such simulation not only includes software simulation like CarSim and CARLA. but also includes hybrid realization with hardware-in-the-loop or vehicle-in-the-loop design [67].”
From Trustworthy AI: From Principles to Practices (2023) · cites this paper as [67]
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Metadata
- Authors
- Rosique, F., Navarro, P. J., Fernández, C., & Padilla, A.
- Affiliations
- Universidad Politécnica de Cartagena (ES)
- Corresponding author
- Rosique, Francisca
- Navarro, Pedro J.
- Venue
- Sensors
- Publisher
- MDPI AG
- Published
- 2019-02-05
- Volume
- 19
- Issue
- 3
- Pages
- 648
- ISSN
- 1424-8220 (ISSN-L)
- PMC
- PMC6387009
- OpenAlex
- W2912493354
- Cited by
- 469
- References
- 63
- Citations by year
- 2026: 34 · 2025: 49 · 2024: 80 · 2023: 96 · 2022: 71 · 2021: 74 · 2020: 47 · 2019: 17
- FWCI
- 5.47
- Type
- journal article
- Language
- en
- Open access
- gold
- dx.doi.org
- Licence
- Locations
- Sensors (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, other-oa)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Digital Repository (Polytechnic University of Cartagena) (submittedVersion, cc-by-nc-nd)
- Funders
- Dirección General de Tráfico (SPIP2017-02286)
- Ministerio de Economía y Competitividad (BFU2017-88300-C2-2-R)
- Fundación Séneca (19895/GERM/15)
- Topics
- Physical Sciences › Engineering › Automotive Engineering › Autonomous Vehicle Technology and Safety
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Robotics and Sensor-Based Localization
- Physical Sciences › Engineering › Automotive Engineering › Vehicle Dynamics and Control Systems
- Keywords
- autonomous vehicles, perception systems, vehicle simulator, sensor comparison, ultrasonic sensors, radar, LiDAR, camera, inertial measurement unit, GNSS, RTK, game engines, model-driven engineering, autonomous vehicle regulation
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