Review of Electrical and Electronic Architectures for Autonomous Vehicles: Topologies, Networking and Simulators

Wang, Wenwei; Guo, Kaidi; Cao, Wanke; Zhu, Hailong; Nan, Jinrui; Yu, Lei

doi:10.1007/s42154-023-00266-9

Cited by 3 publications

(1 citation statement)

References 99 publications

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“…Connected autonomous vehicles (CAVs), however, extend beyond this concept. They not only interact with other vehicles but also with motorcycles, bicycles, pedestrians, and other road users, as well as Internet of Things (IoT) services, including via Road-Side-Units [23], over Dedicated Short-Range Networking (DSRC) or 5G-V2X networking [24,25]. The CAVs referred to in this study differ from simple AVs primarily in their networking capabilities.…”

Section: Definition Of Connected Autonomous Vehiclesmentioning

confidence: 99%

A Greenhouse Gas Footprint Analysis of Advanced Hardware Technologies in Connected Autonomous Vehicles

Zhang,

Zhao,

Song

et al. 2024

Sustainability

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Greenhouse gas emissions are a critical concern for China’s automotive industry, especially for passenger cars due to their high sales’ volume. Recently, the trend towards connected and autonomous driving vehicles has been significant in the passenger car market. However, the impact of these systems on the life cycle emissions of vehicles remains unclear. This paper focuses on system function levels from driver assistance to full driving automation and studies their life cycle greenhouse gas emissions. This research establishes a component list for the hardware system and a material inventory. Then, this paper reveals significant differences in total system emissions at these technology levels, 540.1 kg for primary, 1318.7 kg for medium, and 2279.2 kg for advanced systems. Despite this difference, the total is less than 7.23% of the total vehicle emissions. To further reduce this portion of GHG emissions, it is recommended that vehicles favor millimeter-wave radar over solid-state LiDAR in their sensing system hardware, coupled with cameras as the primary sensing element. In addition, Intelligent Hardware Systems are not recommended for internal combustion engine passenger cars for optimal balance between functionality and environmental impact.

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Section: Definition Of Connected Autonomous Vehiclesmentioning

confidence: 99%

A Greenhouse Gas Footprint Analysis of Advanced Hardware Technologies in Connected Autonomous Vehicles

Zhang,

Zhao,

Song

et al. 2024

Sustainability

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Design and development of an intelligent zone based master electronic control unit for power optimization in electric vehicles

Prabhakaran,

Thirumoorthi,

Sri Dhivya Krishnan

2024

Sci Rep

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HP-LSTM: Hawkes Process–LSTM-Based Detection of DDoS Attack for In-Vehicle Network

Li,

Liu

2024

Future Internet

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Connected and autonomous vehicles (CAVs) are advancing at a fast speed with the improvement of the automotive industry, which opens up new possibilities for different attacks. A Distributed Denial-of-Service (DDoS) attacker floods the in-vehicle network with fake messages, resulting in the failure of driving assistance systems and impairment of vehicle control functionalities, seriously disrupting the normal operation of the vehicle. In this paper, we propose a novel DDoS attack detection method for in-vehicle Ethernet Scalable service-Oriented Middleware over IP (SOME/IP), which integrates the Hawkes process with Long Short-Term Memory networks (LSTMs) to capture the dynamic behavioral features of the attacker. Specifically, we employ the Hawkes process to capture features of the DDoS attack, with its parameters reflecting the dynamism and self-exciting properties of the attack events. Subsequently, we propose a novel deep learning network structure, an HP-LSTM block, inspired by the Hawkes process, while employing a residual attention block to enhance the model’s detection efficiency and accuracy. Additionally, due to the scarcity of publicly available datasets for SOME/IP, we employed a mature SOME/IP generator to create a dataset for evaluating the validity of the proposed detection model. Finally, extensive experiments were conducted to demonstrate the effectiveness of the proposed DDoS attack detection method.

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Review of Electrical and Electronic Architectures for Autonomous Vehicles: Topologies, Networking and Simulators

Cited by 3 publications

References 99 publications

A Greenhouse Gas Footprint Analysis of Advanced Hardware Technologies in Connected Autonomous Vehicles

A Greenhouse Gas Footprint Analysis of Advanced Hardware Technologies in Connected Autonomous Vehicles

Design and development of an intelligent zone based master electronic control unit for power optimization in electric vehicles

HP-LSTM: Hawkes Process–LSTM-Based Detection of DDoS Attack for In-Vehicle Network

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