No full-text available
To read the full-text of this research,
you can request a copy directly from the authors.
High-Speed, Low-Latency In-Vehicle Network Based on the Bus Topology for Autonomous Vehicles: Automotive Networking and Applications
... With the growing amount of data being transmitted within vehicles, it is imperative to develop IVNs that take into account the specific communication needs of AVs. Table 1 depicts the specified deadline requirements for each sensor [18]. Sensor configurations for different vehicle categories are shown in Table 2, with each sensor serving a unique purpose in a variety of industries. ...
Autonomous Vehicles (AVs) are revolutionizing transportation by integrating advanced sensors, artificial intelligence, and communication networks to enhance safety and efficiency. This review explores the architecture of AVs, focusing on perception, localization, path planning, and control. A detailed analysis of AV sensors, including LiDAR, radar, cameras, and inertial navigation systems, highlights their roles, advantages, and limitations. Additionally, the paper examines in-vehicle and inter-vehicle communication networks, such as CAN, LIN, FlexRay, and Ethernet, which facilitate real-time data exchange. The study also addresses the key challenges AVs face, including cybersecurity threats, data processing, legal policies, and ethical concerns. By synthesizing recent advancements and ongoing challenges, this paper provides a comprehensive understanding of the state of AV technologies and their future prospects.
... With the growing amount of data being transmitted within vehicles, it is imperative to develop IVNs that take into account the specific communication needs of AVs. Table 1 depicts the specified deadline requirements for each sensor [18]. ...
Autonomous Vehicles (AVs) are revolutionizing transportation by integrating advanced sensors, artificial intelligence, and communication networks to enhance safety and efficiency. This review explores the architecture of AVs, focusing on perception, localization, path planning, and control. A detailed analysis of AV sensors, including LiDAR, radar, cameras, and inertial navigation systems, highlights their roles, advantages, and limitations. Additionally, the paper examines in-vehicle and inter-vehicle communication networks, such as CAN, LIN, FlexRay, and Ethernet, which facilitate real-time data exchange. The study also addresses the key challenges AVs face, including cybersecurity threats, data processing, legal policies, and ethical concerns. By synthesizing recent advancements and ongoing challenges, this paper provides a comprehensive understanding of the state of AV technologies and their future prospects.
... The quantity of data traffic and the quantity of sensors, including cameras, lidar, and radar, needed for AVs are growing in order to facilitate more advanced levels of autonomous driving. With the growing amount of data being transmitted within vehicles, it is imperative to develop IVNs that take into account the specific communication needs of AVs.Table 2.1depicts the specified deadline requirements for each sensor[48]. ...
A CAN bus, the common intra-vehicle network standard, has been used for over three decades. However, its weight, maintenance costs, and installation complexity increase with more ECUs, especially in AVs. This book aims to replace wired CAN with wireless CAN. Proposed solutions include designing an AV model with external and internal ECUs using CANoe/MATLAB simulation. Modifying ECU architecture for wireless communication, implementing a hidden communication environment with CCK modulation, and addressing jamming signals using dual channels. Testing using MATLAB and OPNET shows stable BER and packet loss, with robust CCK modification and challenges in signal interception. Results indicate successful integration of internal and external ECUs with IEEE 802.11b,and using 100BaseT Fast Ethernet for high bandwidth LiDAR data and delay requirements.
... It emphasizes the significance of the message's priority. By comparing the results obtained for the final simulation network, all ECUs were within the acceptable limits of deadline delay (10 ms for camera, radar, and LiDAR ECUs and 5-50 ms for control ECUs) [19]. In LiDAR, in the case of using 10 Mbps, the delay was within acceptable limits to some extent. ...
The controller area network (CAN) bus, the prevailing standard for in-vehicle networking (IVN), has been used for more than four decades, despite its simple architecture, to establish communications between electronic control units (ECUs). Weight, maintenance overheads, improved flexibility, and wiring complexity escalate as the quantity of ECUs rises, especially for high-demand autonomous vehicles (AVs). The primary objective of this study is to examine and discuss the significant challenges that arise during the migration from a wired CAN to a wireless CAN (WCAN). Suggested remedies include changing the configuration of the conventional ECU, creating a hidden wireless communication domain for each AV, and developing a plan to counteract the jamming signals. The simulation of the proposed WCAN was done using MATLAB and validated using OPNET analysis. The results showed that the packet loss of the eavesdropping electronic control unit ranged from 63% to 100%. Anti-jamming results show that when packet loss reaches 2% for a continuous period of time of 0.01 sec, the passive channel is automatically activated, ensuring secure data transmission.
... Second, the proliferation of applications that require a significant amount of bandwidth, such as autonomous vehicles [18], virtual reality [19], and augmented reality [20], necessitates the use of networks with low-latency and high-bandwidth capabilities. Edge computing helps relieve the strain on network infrastructure by providing locallybased computing and storage capabilities [21]. ...
The notion of edge computing has recently arisen as a potentially helpful advancement in distributed computing and communication infrastructure. To better understand the evolution and diffusion of technological knowledge in this field, we conducted a citation graph analysis of scholarly publications related to edge computing. Our study aims to identify the critical technological trajectories and research themes that have shaped the development and adoption of edge computing over time. We employ Main Path Analysis (MPA) to construct a citation graph using a comprehensive publications dataset from Web of Science (WoS) databases. We applied keyword co-occurrence analysis techniques to identify clusters of research topics and their interconnections. Occurrence cluster analysis results indicate that current research in edge computing is primarily centered around the architecture of edge computing, high-speed networks, mobile edge computing, computing systems, and blockchain and security technologies. We also identified the significant papers and contributors in the edge computing field and their impact on the technological trajectory of edge computing. The results reveal 35 significant papers that shape the emergence of four phases of the technology trajectory, including edge computing transition, architecture, edge future, and edge optimization.
... The design and engineering of the automated rickshaw components, specifically the compute stack, require careful consideration of the data traffic patterns at various nodes, as shown in Table 2. [32,33]. ...
This paper presents the implementation and potential use-cases of a new innovative development of a fully connected and automated three-wheeled cycle rickshaw. The rickshaw is used for transporting passengers or logistics parcels or a combination of both. For this purpose, the rickshaw is equipped with an electric power train system including a lithium accumulator as well as actuators for breaking, propulsion and the steering of the front wheel. The environmental sensing is currently realized via three LiDAR sensors mounted at the roof of the rickshaw observing the 360-degree surrounding of the vehicle. Equipped with a state-of-the-art on-board unit for V2X-communication and remote-control access in cases of overstress situations for the trajectory planning and self-driving functionality the rickshaw represents a fully equipped connected and automated vehicle for urban road traffic. The rickshaw shows a substantial potential to increase the productivity, reliability and flexibility of logistics and transport services. A higher degree of automation in logistics and freight transport-within this prototypical implementation realized by the self-driving functionality-allows for a more cost-efficient operation of logistics fleets and businesses. Additionally, less weight due to the absence of a driver and lightweight components also leads to a reduced energy consumption. The developed self-driving rickshaw gives the opportunity to automatize first-and last-mile logistics services as well as passenger transport with reduced costs.
... Table 2 shows the types and numbers of external ECUs used in addition to the maximum number of detection objects for the camera and radar. Table 3 represents the delay deadline communication requirements of each ECU [9]. ...
The development of autonomous vehicles (AVs) has gained significant attention in recent yearsdue to their potential benefits in terms of increased safety, reduced traffic congestion, and improved energyefficiency. Various types of Controller Area Network (CAN) bus protocols in AVs are crucial for theirproper functioning. This paper presents an efficient design of a basic autonomous vehicle based on variousCAN bus types. The proposed design incorporates a multi-protocol CAN bus system that enables efficientcommunication between the different components of the AV. The system is designed to be scalable andadaptable to future advancements in autonomous driving. The paper also discusses the challenges facedduring the design process and the solutions to overcome them. Simulation results demonstrate theeffectiveness of the proposed design, highlighting its reliability and robustness in various driving scenarios.Overall, the proposed design can be a foundation for developing more advanced AVs and pave the waytoward safer and more efficient transportation systems.
... After a series of verifications, the results showed that the proposed method has better performance than other traditional methods. Choi et al. [20] proposed methods to improve the performance of IVNs based on the bus topology. Simulations showed that the methods can improve the data transmission speed and reduce the transmission delay. ...
The bus network is widely used in industrial automation and avionics systems due to its many advantages. Network reliability is an important indicator of the bus network design and analysis. However, the widely used reliability evaluation method is not capable of dealing with the bus network. In this paper, we model the bus network without redundancy and the bus network with redundancy, propose the algorithms to calculate the two-terminal reliability and the k-terminal reliability of the bus network with redundancy, and verify the effectiveness of the algorithms in three scenarios. The experimental results show that when the reliability of the link reaches 0.9, the two-terminal reliability of the bus network with redundancy of six terminal nodes, eight terminal nodes, and ten terminal nodes is 40.95%, 52.17%, and 61.26% higher than that of the bus network without redundancy, respectively; k-terminal reliability is 61.26%, 74.58%, and 83.32% higher than that of the bus network without redundancy, respectively. The bus network with redundancy increases the communication paths for data exchange between devices, and has higher reliability than the bus network without redundancy. The algorithms proposed in this paper provide an effective solution for the reliability evaluation of the bus network. It perfects the reliability evaluation system of the network with different topology architectures.
The automotive industry is currently undergoing a revolution. Electrification, automation, and connectivity become major trends in future vehicles. Autonomous driving vehicles require a variety of sensors to perceive their surroundings and rely on high-speed and reliable intra-vehicle networks (IVNs) for data transmission. As the number and performance of sensors increase and the IVN evolves from distributed architecture to domain centralized and zone centralized architecture, the demand for IVN data rates escalates. Optical fiber communication is a promising solution in IVN due to its high bandwidth, light weight, and good electromagnetic compatibility. However, the harsh environment in vehicles such as wide temperature range, vibration, dust and grease contamination poses a great challenge to employ optical fiber communication in IVN. To tackle this issue, novel intra-vehicle optical network configurations and technologies have been proposed. In addition, the development of vehicle-to-everything (V2X) communication technology will further improve road safety and traffic efficiency. Optical wireless communication can offer advantages over radio frequency technology for V2X communication.
Information-centric networking (ICN) allows data to be cached at each node in the network. It is vital in vehicular networks (VNs) to improve caching performance and reduce content delay in high-traffic scenarios. In cooperative VNs, the requested content can be cached in the base station or nearby nodes without fetching the requested content from the server. The existing content popularity approaches face challenges in predicting popular content due to a time-varying environment, resulting in popularity being changed frequently. It is hard to predict such content in highly dynamic vehicular traffic. Therefore, the current approaches are less practical in a realistic scenario. This paper proposes an intelligent caching method for massive traffic in VNs to address these issues based on deep transfer learning (DTL). The primary purpose of this study is to reduce the system cost and content delay by increasing the cache hit rate based on popular data in dynamic traffic. The proposed solution uses a collaborative cache with social interaction among clusters to share the most popular content (MPC). Furthermore, it designs a time-varying mechanism to predict content popularity in a highly dynamic environment and share the widespread knowledge with other target nodes based on DTL. In addition, a content update method is developed to address the content replacement in a cooperative cache environment. Based on thorough analysis and evaluation, similar and dissimilar contents on base stations are classified among source and target clusters. The extensive simulation and experimentation confirm that the developed work achieved better than baseline studies.
With the advancement of X-by-wire chassis technology, the number of CAN bus-mounted nodes in steering-by-wire (SbW) vehicles has increased, resulting in an increase of input time delay (ITD) in SbW system’s control input. When the maximum ITD (MITD) exceeds ITD critical value (ITD-CV) that SbW controller can tolerate, SbW system would diverge, causing a major accident. In order to improve the control performance of SbW systems, a novel strategy is proposed, containing an analysis part and a controller design part. In the analysis part, a novel critical eigenroot-based ITD-CV and stable delay range (SDR) analysis method, using Hurwitz stability criterion to analyze the direction where the eigenroots cross the imaginary axis with ITD varying, is built to evaluate and optimize the SbW system controller. In the controller design part, a novel TD-H
2
/H
∞
controller is established. Specifically, an SbW model with implicit ITD is derived utilizing state transformation theory, and an angle tracking controller (ATC) is developed using H
2
and H
∞
norm constraints to ensure tracking and robustness performance. Finally, simulation and hardware-in-the-loop (HIL) experiment are carried out to verify that the proposed method can efficiently calculate SDR, and achieve superior control performance.
Artificial Intelligence (AI) is transforming all of the technologies we use every day. More than ever, we are very near to the objective of vehicle autonomy, which has long been desired. Large automakers are also spending billions of dollars on the development of autonomous vehicles (AVs). Among the advantages of this new technology are the possibility for increased passenger safety, less congested roads, reduced traffic, optimized traffic, reduced fuel consumption, less pollution, and improved travel experiences. However, there are also new security and privacy problems associated with this paradigm change. Previously simple mechanical devices, vehicles are today computerized, networked, and intelligent. They gather vast amounts of data, which must be shielded from intrusions. In this paper, we examine privacy issues and security hurdles in AVs. We investigate several attacks using a layer-by-layer methodology. It summarizes the contributions of these research works and categorizes them based on application domains. It also identifies open problems and research challenges that need to be addressed to fully realize the potential of AI in advancing V2X systems. Our intention is to provide insights into the unresolved research issues surrounding AVs and to suggest future lines of inquiry.
To address the problems of low network centralized management, weak interaction, limited hardware scalability, compatibility issues and challenges in expansion in the static deployment of traditional in-vehicle networks (IVNs), a new IVN architecture is designed. At the same time, to better meet the IVN Quality of Service (QoS) requirements and improve the real-time guarantee of data transmission, the QoS routing optimization mechanism under the new architecture is established. First, a new IVN architecture including a forwarding plane, control plane and application plane is designed by introducing software defined network (SDN) technology and combining it with the IVN itself. Second, the end-to-end delay optimization model of IVN is established by introducing network calculus theory, defining system parameters, creating a network model, calculating latency, considering queuing and congestion. the traditional routing algorithm is improved, and the DBROA algorithm has been proposed, which enhances the performance of QoS routing by introducing features such as distributed routing decisions, beacon mechanisms, optimization algorithms, and adaptability. This improvement allows it to better meet the QoS requirements of various applications and services, thereby enhancing existing QoS routing algorithms. Finally, an IVN routing optimization system is built and implemented, and the performance of different algorithms is compared and analyzed. The experimental results show that compared with the traditional Dijkstra and ECMP algorithms, the DBROA algorithm can effectively reduce the data forwarding delay and packet loss rate, improve the overall performance of IVN, and provide better QoS guarantees for IVN real-time data transmission.
The development of intelligent driving and X-by-wire chassis technology increases the computational complexity and the number of CAN bus-mounted nodes of steering-by-wire vehicles, which leads to non-negligible large random time delay (TD) of the SbW system's control input. TD has a great impact on SbW system's tracking error, which will inevitably deteriorate the safety and yaw stability of vehicles and even cause sideslip accidents. In order to ensure the safety of SbW vehicles, a layered time-delay robust control strategy (LTDRCS) consisting an upper and a lower controller is proposed. Specifically, a novel Lyapunov-Krasovskii (L-K) TD H∞ controller (H
∞
C) is designed as the lower controller to reduce tracking error, and the system's stability and convergence are synchronously guaranteed by an L-K function and an H∞ norm constraint. As for the upper controller, a novel terminal sliding mode controller (NTSMC) is established to control the yaw rate index and sideslip angle index. In order to restrain the serious influence of the SbW system's inevitable, unknown, and bounded tracking error caused by TD on vehicle yaw stability and ensure the rapid convergence of the system, a novel integral term is introduced. Simulation and experiments show that the proposed strategy efficiently improves the tracking accuracy of the SbW system and the vehicle yaw stability under random TD condition, which benefits from the synergy of the upper and lower layers.
ResearchGate has not been able to resolve any references for this publication.