电动汽车车载网络综述
LIN和CAN车载网络介绍
浅谈车载网络为了在提高性能与控制线束数量之间寻求一种有效的解决途径,在20世纪80年代初，出现了一种基于数据网络的车内信息交互方式——车载网络。
车载网络采取基于串行数据总线体系的结构，最早的车载网络是在UART(Universal Asynchronous Receiver/Transmitter)的基础上建立，如通用汽车的E&C、克莱斯勒的CCD等车载网络都是UART在汽车上的应用实例。
由于汽车具有强大的产业背景，随后车载网络由借助通用微处理器/微控制器集成的通用串行数据总线，逐渐过渡到根据汽车具体情况，在微处理器/微控制器中定制专用串行数据总线。
20世纪90年代中期，为了规范车载网络的研究设计与生产应用，美国汽车工程师协会(SAE)下属的汽车网络委员会按照数据传输速率划分把车载网络分为Class A、Class B、Class C三个级别：Class A的数据速率通常低于20Kbps，如LIN，主要用于车门控制、空调、仪表板；Class B的数据速率为10Kbps～125Kbps，如低速CAN(ISO 11898)，主要是事件驱动和周期性的传输；Class C的数据速率为125Kbps～1Mbps，如高速CAN(ISO898)，主要用于引擎定时、燃料输送、ABS等需要实时传输的周期性参数。
拥有更高传输速率的MOST和FlexRay主要适用于音视频数据流的传输。
目前与汽车动力、底盘和车身密切相关的车载网络主要有CAN、LIN和FlexRay。
从全球车载网络的应用现状来看，通过20多年的发展，CAN已成为目前全球产业化汽车应用车载网络的主流。
CAN，全称为“Controller Area Network”，即控制器局域网，CAN 数据总线又称为CAN—BUS总线，20世纪80年代初由德国Bosch 公司开发，作为一种由ISO定义的串行通讯总线，其通信介质可以是双绞线、同轴电缆或光导纤维。
An Overview of Internet of Vehicles 车联网综述
signal range and drop out of the network, oth-er vehicles can join in, connecting vehicles to one another to create a mobile Internet. We de-termine that V ANET only covers a very small mobile network that is subject to mobility con-straints and the number of connected vehicles. Several characteristics of large cities, such as traffic jams, tall buildings, bad driver behav-iors, and complex road networks, further hin-der its use. Therefore, for V ANET, the objects involved are temporary, random and unstable, and the range of usage is local and discrete, i.e., VANET cannot provide whole (global) and sustainable services/applications for cus-tomers. Over the past several decades, there has not been any classic or popular implemen-tation of VANET. The desired commercial interests have not emerged either. Therefore, V ANET’s usage has begun to stagnate.In contrast to VANET, IoV has two main technology directions: vehicles’ neworking and vehicles’ intelligentialize. Vehicles’ net-working is consisting of V ANET (also called vehicles’ interconnection), Vehicle Telematics (also called connected vehicles) and Mobile Internet (vehicle is as a wheeled mobile termi-nal). Vehicles’ intelligence is that the integra-tion of driver and vehicle as a unity is more intelligent by using network technologies, which refers to the deep learning, cognitive computing, swarm computing, uncertainty artificial intelligence, etc. So, IoV focuses on the intelligent integration of humans, vehi-cles, things and environments and is a largerAbstract: The new era of the Internet of Things is driving the evolution of conventional Vehicle Ad-hoc Networks into the Internet of Vehicles (IoV). With the rapid development of computation and communication technologies, IoV promises huge commercial interest and research value, thereby attracting a large number of companies and researchers. This paper proposes an abstract network model of the IoV , discusses the technologies required to create the IoV , presents different applications b a s e d o n c e r t a i n c u r r e n t l y e x i s t i n g technologies, provides several open research challenges and describes essential future research in the area of IoV .Keywords: internet of vehicles; VANET; vehicle telematics; network modelI. I NTRODUCTIONAccording to recent predictions 1, 25 billion “things” will be connected to the Internet by 2020, of which vehicles will constitute a significant portion. With increasing numbers of vehicles being connected to the Internet of Things (IoT), the conventional Vehicle Ad-hoc Networks (VANETs) are changing into the Internet of Vehicle (IoV). We explore the reasons for this evolution below.As is well-known, V ANET [1] turns every participating vehicle into a wireless router or mobile node, enabling vehicles to connect to each other and, in turn, create a network with a wide range. Next, as vehicles fall out of theAn Overview of Internet of VehiclesYANG Fangchun, WANG Shangguang, LI Jinglin, LIU Zhihan, SUN QiboState Key Laboratory of Networking and Switching Technology Beijing University of Posts and Telecommunications, Beijing, ChinaV EHICULAR N ETWORKING1/7037738/The_Inter-net_of_Things_A_Study_in_Hype_Reality_Disrup-tion_and_Growtthe conventional Vehicle Ad-hoc Networks (V ANETs), Vehicle Telematics, and other con-nected vehicle networks have to evolve into the Internet of Vehicle (IoV). The question accordingly arises as to why such systems did not evolve into IoT, Internet or wireless mo-bile networks.The main reason is that some characteris-tics of IoV are different from IoT, Internet or wireless mobile networks. Firstly, in wireless mobile networks, most end-users’ trajectories follow a random walk model. However, in IoV , the trajectory of vehicles is subject to the road distributions in the city. Secondly, IoT focuses on things and provides data-aware-ness for connected things, while the Internet focuses on humans and provides information services for humans. However, IoV focuses on the integration of humans and vehicles, in which, vehicles are an extension of a human’s abilities, and humans are an extension of a vehicle’s intelligence. The network model, the service model, and the behavior model of human-vehicle systems are highly different from IoT, Internet or wireless mobile network. Finally, IoV interconnects humans within and around vehicles, intelligent systems on board vehicles, and various cyber-physical systems in urban environments, by integrating vehi-cles, sensors, and mobile devices into a global network, thus enabling various services to be delivered to vehicles and humans on board and around vehicles. Several researchers have referred to the vehicle as a manned computer with four wheels or a manned large phone in IoV. Thus, in contrast to other networks, ex-isting multi-user, multi-vehicle, multi-thing and multi-network systems need multi-level collaboration in IoV .In this paper, we first provide a network model of IoV using the swarm model and an individual model. We introduce existing re-search work focusing on activation and main-tenance of IoV. Then, we survey the various applications based on some currently existing technologies. Finally, we give several open re-search challenges for both the network model and the service model of human-vehicle sys-network that provides services for large cities or even a whole country. IoV is an open and integrated network system with high manage-ability, controllability, operationalization and credibility and is composed of multiple users, multiple vehicles, multiple things and multiple networks. Based on the cooperation between computation and communication, e.g., col-laborative awareness of humans and vehicles, or swarm intelligence computation and cog-nition, IoV can obtain, manage and compute the large scale complex and dynamic data of humans, vehicles, things, and environments to improve the computability, extensibility and sustainability of complex network systems and information services. An ideal goal for IoV is to finally realize in-depth integration of human-vehicle-thing-environment, reduce social cost, promote the efficiency of trans-portation, improve the service level of cities, and ensure that humans are satisfied with and enjoy their vehicles. With this definition, it is clear that V ANET is only a sub network of IoV. Moreover, IoV also contains Vehicle Telematics [2], which is a term used to define a connected vehicle interchanging electronic data and providing such information services as location-based information services, remote diagnostics, on-demand navigation, and au-dio-visual entertainment content. For IoV , Ve-hicle Telematics is simply a vehicle with more complex communication technologies, and the intelligent transportation system is an applica-tion of IoV , but vehicle electronic systems do not belong to IoV .In the last several years, the emergence of IoT, cloud computing, and Big Data has driven demand from a large number of users. Individ-ual developers and IT enterprises have pub-lished various services/applications. However, because V ANET and Vehicle Telematics lack the processing capacity for handling global (whole) information, they can only be used in short term applications or for small scale ser-vices, which limits the development and popu-lar demand for these applications on consumer vehicles. There is a desperate need for an openand integrated network system. Therefore,people who consume or provide services/ap-plications of IoV . Human do not only contain the people in vehicles such as drivers and pas-sengers but also the people in environment of IoV such as pedestrians, cyclists, and drivers’ family members. Vehicle in IoV terminology refers to all vehicles that consume or provide services/applications of IoV . Thing in IoV ter-minology refers to any element other than hu-man and vehicle. Things can be inside vehicles or outside, such as AP or road. Environment refers to the combination of human, vehicle and thing.The individual model focuses on one vehi-cle. Through the interactions between human and environment, vehicle and environment, and thing and environment, IoV can provide services for the vehicles, the people and the things in the vehicles. In the model, the in-tra-vehicle network is used to support the interaction between human and vehicle, and the interaction between vehicle and thing in that vehicle. The inter-vehicle network is usedtems, i.e., enhanced communication through computation and sustainability of service pro-viding, and outline essential future research work in the area of IoV .The rest of this paper is organized as fol-lows. Section 2 describes o ur proposed net-work model of IoV. The overview of IoV is presented from three different perspectives in Section 3. In Section 4, several open research challenges and essential future research work related to IoV are outlined. Finally, we present this paper’s conclusions in Section 5.II. N ETWORK M ODEL OF IOVAs shown in Fig. 1, we propose a network model of IoV based on our previous work [3], in which the model is composed of a swarm model and an individual model. The key as-pect of the network model is the integration between human, vehicle, thing, and environ-ment.Human in IoV terminology refers to all theFig.1Network model of IoVsignificantly improve the quality of vehicle service, while a bad wireless access may often lead to the breakdown of services. As is well-known, routing technology is the research core of traditional networks. For IoV , while routing is still the core of the inter-vehicle network, it is also essential for delivering the control message. Finally, IoV has the two most im-portant elements, i.e., users and network. For a simple IoV, wireless access is its user, and routing is its network. With the development of IoV , however, these elements might be less important, and other technologies may play a vital role, such as collaboration technology and swarm intelligence computing. However, due to page limitations, a detailed discussion is beyond this paper.Note that the technologies introduced in this section cannot cover the technologies of IoV , and most of them belong to V ANET [4] or Ve-hicle Telematics. The reason is that IoV is an open and integrated network system composed of multiple users, multiple vehicles, multiple things and multiple networks, and an integrat-ed IoV is not described. Hence, this section mainly focuses on existing technologies and applications, even if they do not represent the technologies and applications of IoV .3.1 Activation of IoVThere are many steps in the activation of IoV , but the most important step is to take the vehi-cles into the integrated network of IoV using wireless access technologies. At present, there are many existing wireless access technologies such as WLANs, WiMAX, Cellular Wireless, and satellite communications [5]. As shown in Fig. 1, most of these technologies are used to connect vehicles to each other in IoV .WLAN contains IEEE 802.11a/b/g/n/p standards. IEEE 802.11-based WLAN, which has achieved great acceptance in the market, supports short-range, relatively high-speed data transmission. The maximum achievable data rate in the latest version (802.11n) is ap-proximately 100 Mbps. IEEE 802.11p is a new communication standard in the IEEE 802.11 family which is based on the IEEE 802.11a.to support the interaction between human and environment, vehicle and environment, and thing and environment. Swarm model focus-es on multi-user, multi-vehicle, multi-thing and multi-network scenarios. Through swarm intelligence, crowd sensing and crowd sourc-ing, and social computing, IoV can provide services/applications. Moreover, in this model, the interaction between human and human, ve-hicle and vehicle, and thing and thing, all need an integrated network to collaborate with each other and with the environment. Note that IoV has a computation platform for providing vari-ous decisions for whole network, and there are many virtual vehicles with drivers correspond-ing to physica vehicles and drivers. Then we call the virtual vehicle with driver as Autobot. In the IoV, Autobot can interact with each other by using swarm computing technologies and provide decision-making information for IoV in the computation platform.III. T ECHNOLOGY AND A PPLICATION OF IOVOver a decade ago, both industrial and aca-demic researchers proposed many advanced technologies for the application layer, the mo-bile model & the channel model, the physical layer & the data link layer, the network layer & the transport layer, and security & privacy; these technologies are all used in IoV . In this section, we only focus on giving an overview of the technologies and their applications in IoV, and do not describe the details of the technologies. The overview describes the acti-vation of the IoV , maintenance of the IoV , and IoV applications.For the activation and maintenance of the IoV, we only summarize the wireless access technology and the routing technology. There are several reasons for focusing on these two technologies. Firstly, most researchers working on IoV focus on wireless access and routing, for which the number of proposed re-search works are the highest. Secondly, wire-less access technologies play an important role in IoV . A good wireless access technology canquality of service, even for non-line-of-sight transmissions. The key advantage of WiMAX compared to WLAN is that the channel access method in WiMAX uses a scheduling algo-rithm in which the subscriber station needs to compete only once for initial entry into the network.Cellular wireless comprises of 3G, 4G and LTE. Current 3G networks deliver data at a rate of 384 kbps to moving vehicles, and can go up to 2 Mbps for fi xed nodes. 3G sys-tems deliver smoother handoffs compared to WLAN and WiMAX systems, and many nota-ble works have been proposed. For example, Chao et al. [8] modeled the 3G downloading and sharing problem in integration networks. Qingwen et al. [9] made the first attempt in exploring the problem of 3G-assisted data delivery in V ANETs. However, due to central-ized switching at the mobile switching center (MSC) or the serving GPRS support node (SGSN), 3G latency may become an issue for many applications. Vinel [3] provided an an-IEEE 802.11p is designed for wireless access in the vehicular environment to support intel-ligent transport system applications. The use of wireless LANs in V ANETs requires further research. For example, Wellens et al. [6] pre-sented the results of an extensive measure-ment campaign evaluating the performance of IEEE 802.11a, b, and g in car communication scenarios, and showed that the velocity has a negligible impact, up to the maximum tested speed of 180 km/h. Yuan et al. [7] evaluated the performance of the IEEE 802.11p MAC protocol applied to V2V safety communica-tions in a typical highway environment. Wi-MAX contains IEEE 802.16 a/e/m standards. IEEE 802.16 standard-based WiMAX are able to cover a large geographical area, up to 50 km, and can deliver significant bandwidth to end-users - up to 72 Mbps theoretically. While IEEE 802.16 standard only supports fixed broadband wireless communications, IEEE 802.16e/mobile WiMAX standard supports speeds up to 160 km/h and different classes of Fig.2 Wireless access technologies in IoVAPManagement and Control on the APIEEE 802.16WiMax DatabaseAP Management and Control on the APAPManagement and Control on the APCellular NetworkCellular NetworkDatabaseSatellite NetworkSatellite Network DatabaseAPManagement and Control on the APIEEE 802.11WLAN DatabaseVehicleVehicleVehicleVehicleCentralized Management and Control Unitand Control Unit (CMCU)NetworkDatabaseCMCUIoV3.2 Maintenance of IoVThere are also many aspects to the mainte-nance of IoVs, such as data-awareness, virtual networks, and encoding, but the most im-portant aspect is the switching of the control message for IoV. Routing technology is the suitable solution, and in IoV , is dependent on a number of factors such as velocity, density, and direction of motion of the vehicles. As shown in Fig. 1, vehicles can either be the source or the destination during the process of routing, and various standards have been built to accomplish the task of routing. With the growing needs of the users to access various resources during mobility, efficient techniques are required to support their needs and keep them satisfied.Topology based maintenance: Because of the large overhead incurred for route discovery and route maintenance for highly mobile unco-ordinated vehicles, only a few of the existing routing protocols for inter-vehicle networks are able to handle the requirements of safety applications [10,11]. An important group of routing protocols for ad-hoc networks is based on topology, and needs the establishment of an end-to-end path between the source and the destination before sending any data packet. Due to rapid changes in the network topology and highly varying communication channel conditions, the end-to-end paths determined by regular ad-hoc topology-based routing pro-tocols are easily broken. To solve this prob-lem, several routing protocols have been pro-posed [12,13] [14,15] [16] [17]. For example, Namboodiri and Gao [12] proposed a predic-tion-based routing for V ANETs. The PBR is a reactive routing protocol, which is specifically tailored to the highway mobility scenario, to improve upon routing capabilities without us-ing the overhead of a proactive protocol. The PBR exploits the deterministic motion pat-tern and speeds, to predict roughly how long an existing route between a “node” vehicle and a “gateway” vehicle will last. Using this prediction, the authors pre-emptively create new routes before the existing route lifetimealytical framework which allows comparing 802.11p/WA VE and LTE protocols in terms of the probability of delivering the beacon before the expiration of the deadline. Lei et al. [4] studied the potential use cases and technical design considerations in the operator con-trolled device-to-device communications. The potential use cases were analyzed and classi-fied into four categories. Each use case had its own marketing challenges and the design of related techniques should take these fac-tors into consideration. Gerla and Kleinrock [5] discussed LTE cellular service in a future urban scenario with very high bandwidth and broad range. The so-called cognitive radios will allow the user to be “best connected” all the time. For instance, in a shopping mall or in an airport lounge, LTE will become congested, and the user’s cognitive radio will disconnect from LTE. For vehicles, due to large costs, sat-ellite communications are barely used, except for GPS. It is only a supplement for temporary and emergency uses, when other communica-tion technologies are invalid or unavailable. Looking at the wireless access technologies described above, we think that the 4G or LTE should be the most efficient technology to launch the inter-vehicle network and to acti-vate the IoV . The reasons are as follows. First-ly, 4G or LTE is the most used communication standard, and has been deployed by most countries to provide access services. Obvious-ly, any vehicle can use it to connect to the IoV . Secondly, in the context of high buildings and a complex city environment, the performance of 4G or LTE is the best among all wireless access technologies. Finally, in the past ten years, the development of VANET has been very slow, and can barely be used in the real world. The main reason is that the connected vehicles cannot maintain V ANET in city roads because the goals of drivers are random and different. To maintain the V ANET, all vehicles must access the integrated network of IoV, after which IoV can be activated to provide services for users.which combines store-carry-and-forward tech-nique with routing decisions based on geo-graphic location. These geographic locations are provided by GPS devices. In GeoSpray, authors proposed a hybrid approach, mak-ing use of a multiple copy and a single copy routing scheme. To exploit alternate paths, GeoSpray starts with multiple copy schemes which spread a limited number of bundle cop-ies. Afterwards, it switches to a single copy scheme, which takes advantage of additional opportunities. It improves delivery success and reduces delivery delay. The protocol ap-plies active receipts to clear the delivered bun-dles across the network nodes. Compared with other geographic location-based schemes, and single copy and non-location based multiple copy routing protocols, it was found that Geo-Spray improves delivery probability and re-duces delivery delay. In contrast to the above work, Bernsen and Manivannan proposed [20] a routing protocol for V ANETs that utilizes an undirected graph representing the surrounding street layout, where the vertices of the graph are points at which streets curve or intersect, and the graph edges represent the street seg-ments between those vertices. Unlike existing protocols, it performs real-time, active traffic monitoring and uses these data and other data gathered through passive mechanisms to as-sign a reliability rating to each street edge. Then, considering the different environments, a qualitative survey of position-based rout-ing protocols was made in [21], in which the major goal was to check if there was a good candidate for both environments or not. An-other perspective was offered by Liu et al. [22], who proposed a relative position based message dissemination protocol to guarantee high delivery ratio with acceptable latency and limited overhead. Campolo et al. [23] used the time, space and channel diversity to improve the efficiency and robustness of network ad-vertisement procedures in urban scenarios. Clustering based maintenance: In this type of routing scheme, one of the nodes among the vehicles in the cluster area becomes a clusterhead (CH), and manages the rest ofexpires. Toutouh et al. [13] proposed a well-known mobile ad hoc network routing proto-col for V ANETs to optimize parameter settings for link state routing by using an automatic optimization tool. Nzounta et al.[15] proposed a class of road-based VANET routing proto-cols. These protocols leverage real-time ve-hicular traffic information to create paths. Fur -thermore, geographical forwarding allows the use of any node on a road segment to transfer packets between two consecutive intersections on the path, reducing the path’s sensitivity to individual node movements. Huang et al. [16] examined the efficiency of node-disjoint path routing subject to different degrees of path coupling, with and without packet redundancy. An Adaptive approach for Information Dis-semination (AID) in VANETs was presented in [14], in which each node gathered the in-formation on neighbor nodes such as distance measurements, fixed upper/lower bounds and the number of neighboring nodes. Using this information, each node dynamically adjusts the values of local parameters. The authors of this approach also proposed a rebroadcast-ing algorithm to obtain the threshold value. The results obtained show that AID is better than other conventional schemes in its cate-gory. Fathy et al. [17] proposed a QoS Aware protocol for improving QoS in VANET. The protocol uses Multi-Protocol Label Switching (MPLS), which runs over any Layer 2 technol-ogies; and routers forward packets by looking at the label of the packet without searching the routing table for the next hop.Geographic based maintaining. The geo-graphic routing based protocols rely mainly on the position information of the destination, which is known either through the GPS sys-tem or through periodic beacon messages. By knowing their own position and the destination position, the messages can be routed directly, without knowing the topology of the network or prior route discovery. V . Naumov et al. [18] specifically designed a position-based routing protocol for inter-vehicle communication in a city and/or highway environment. Soares et al. [19] proposed the GeoSpray routing protocol,dynamic transmission range, the direction of vehicles, the entropy, and the distrust value parameters. Wang et al. [26] refined the orig -inal PC mechanism and proposed a passive clustering aided mechanism, the main goal of which is to construct a reliable and stable clus-ter structure for enhancing the routing perfor-mance in V ANETs. The proposed mechanism includes route discovery, route establishment, and data transmission phases. The main idea is to select suitable nodes to become cluster-heads or gateways, which then forward route request packets during the route discovery phase. Each clusterhead or gateway candidate self-evaluates its qualification for clusterhead or gateway based on a priority derived from athe nodes, which are called cluster members. If a node falls in the communication range of two or more clusters, it is called a border node. Different protocols have been proposed for this scheme, and they differ in terms of how the CH is selected and the way the routing is done. R. S. Schwartz et al. [24] proposed a dissemination protocol suitable for both sparse and dense vehicular networks. Suppression techniques were employed in dense networks, while the store-carry-forward communication model was used in sparse networks. A. Daein-abi [25] proposed a novel clustering algorithm - vehicular clustering - based on a weighted clustering algorithm that takes into consider-ation the number of neighbors based on theavoidance. At present, collision avoidance technologies are largely vehicle-based systems offered by original equipment manufacturers as autonomous packages which broadly serve two functions, collision warning and driver assistance. The former warns the driver when a collision seems imminent, while the latter partially controls the vehicle either for steady-state or as an emergency intervention [41]. To be specific, collision warning includes notifi -cations about a chain car accident, warnings about road conditions such as slippery road, and approaching emergency vehicle warning [5]. On the one hand, collision warnings could be used to warn cars of an accident that oc-curred further along the road, thus presenting a pile-up from occurring. On the other hand, they could also be used to provide drivers with early warnings and prevent an accident from happening in the first place. Note that driving near and through intersections is one of the most complex challenges that drivers face be-cause two or more traffic flows intersect, and the possibility of collision is high [42]. The intelligent intersection, where such conven-tional traffic control devices as stop signs and traffic signals are removed, has been a hot area of research for recent years. Vehicles coordi-nate their movement across the intersection through a combination of centralized and dis-tributed real-time decision making, utilizing global positioning, wireless communications and in-vehicle sensing and computation 1. A number of solutions for collision avoidance of multiple vehicles at an intersection have been proposed. A computationally efficient control law [43-45] has been derived from ex-ploitation of the monotonicity of the vehicles’ dynamics, but it has not been applied to more than two vehicles. An algorithm that addresses multi-vehicle collisions, based on abstraction, has been proposed in [46]. An algorithmic ap-proach to enforcing safety based on a time slot assignment, which can handle a larger number of vehicles, is found in [41]. Colombo et al. [47] designed a supervisor for collision avoid-ance, which is based on a hybrid algorithm that employs a dynamic model of the vehiclesweighted combination of the proposed metrics. P. Miao [27] proposed a cooperative commu-nication aware link scheduling scheme, with the objective of maximizing the throughput for a session in C-V ANETs. They let the RSU schedule the multi-hop data transmissions among vehicles on highways by sending small sized control messages.Based on the above overview, we provide a relative comparison of all routing protocols in Tab 1. In this table, Route length is the total distance between source and destination. PDR is the packet delivery ratio. Latency is the in-terval of time between the first broadcast and the end of the last host’s broadcast. Latency includes buffering, queuing, transmission and propagation delays.3.3 IoV applicationsWith the rapid development of numeric infor-mation technology and network technology, it is brought forward that theautomatization and intelligentization of vehicle.This gives birth to lots of applications which combine safe driving with service provision. For example, Apple CarPlay, originally introduced as iOS in vehicles, offer full-on automobile integration for Apple’s Maps and turn-by-turn navigation, phone, iMeessage, and music service 5. Similar to CarPlay, Google Android Auto provides a distraction-free interface that allows drivers enjoy the services by connecting Android de-vices to the vehicle. Chinese Tecent recently launched its homegrown navigation app Lu-bao that features user generated contents and social functions 7. For demonstration purposes, in this paper, IoV applications can be divided into two major categories: Safety applications and User applications. Applications that in-crease vehicle safety and improve the safety of the passengers on the roads by notifying the vehicles about any dangerous situation in their neighborhood are called safety applications. Applications that provide value-added services are called User applications.Technologies to enhance vehicular and passenger safety are of great interest, and one of the important applications is collision。
车载网络的概念
2.车载网络系统的定义
为了实现汽车 域网技术把各个电控 单元连接起来，多个 处理器之间相互连接、 协调工作并共享信息 构成了汽车车载计算 机网络系统，简称车 载网络系统。
车载网络系统
3.车载网络系统的相关术语
1）数据总线 各个计算机或是模块间进行数据通讯的通道，简单的说就是一条信 息高速公路。 2）通讯协议 数据在总线上的传输规则。 3）总线速度 在形容数据的传输速度时经常用到“比特率”，比特率是每秒千字 节（KB/sec）。
车载网络系统的概念
知识点
01 车载网络系统的概述 02 车载网络系统的定义 03 车载网络系统的相关术语
1.车载网络系统的概述
随着汽车电控系统的日益复杂，以及对汽车内部控制功能电控单元 相互之间通信能力要求的日益增长，采用传统点对点的连接会使得 车内线束增多，这样在内部通讯的可靠性安全性以及重量方面都给 汽车设计和制造带来很大的困扰。为了解决这些问题，车载网络系 统应运而生。
谢谢观看
简述车载网络协议的分类和特点。
简述车载网络协议的分类和特点。
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文档下载后可定制修改，请根据实际需要进行调整和使用，谢谢!本店铺为大家提供各种类型的实用资料，如教育随笔、日记赏析、句子摘抄、古诗大全、经典美文、话题作文、工作总结、词语解析、文案摘录、其他资料等等，想了解不同资料格式和写法，敬请关注!Download tips: This document is carefully compiled by this editor. I hope that after you download it, it can help you solve practical problems. The document can be customized and modified after downloading, please adjust and use it according to actual needs, thank you! In addition, this shop provides you with various types of practical materials, such as educational essays, diary appreciation, sentence excerpts, ancient poems, classic articles, topic composition, work summary, word parsing, copy excerpts, other materials and so on, want to know different data formats and writing methods, please pay attention!车载网络协议的分类和特点在现代汽车中，车载网络协议是连接各种电子设备和传感器的关键。
车载WIFI方案简介通用课件
车载WiFi方案通常具备更高级的安全功能，如防火墙、加密技术等， 可以保护用户的数据安全。
挑战分析
01
信号稳定性
车载WiFi方案的信号稳定性是一个重要的问题。由于车辆的移动性和环
境因素的干扰，可能会影响网络连接的稳定性。
02 03
设备兼容性
车载WiFi方案需要与各种不同的设备兼容，包括手机、平板电脑、笔记 本电脑等。然而，不同设备的操作系统和硬件配置可能存在差异，这给 设备兼容性带来了挑战。
媒体娱乐
车载WiFi将为用户提供更加丰富、高质量的媒体娱乐内容，如高清 视频、在线游戏等。
商业模式创新
定制化服务
针对不同行业和用户需求，提供 定制化的车载WiFi解决方案，满 足个性化需求。
广告与内容付费
通过与广告商和内容提供商合作， 车载WiFi可以提供有偿的广告和 内容服务，实现商业模式的创新。
通过采用先进的网络覆盖技术，车载WiFi方案能够在车内实现全面、均匀的网络信 号覆盖，确保用户在车内任何位置都能够获得稳定的网络连接。
网络覆盖技术需要综合考虑信号传输距离、信号穿透能力、信号抗干扰能力等因素， 以满足不同车型和不同使用场景的需求。
网络安全技术
网络安全技术是车载WiFi方案中 保障用户信息安全的重要技术。
数据分析与服务
利用用户行为数据和网络流量数 据，提供数据分析服务，帮助企 业了解用户需求和市场趋势，实 现精准营销和商业决策。
谢谢聆听
车载WiFi方案需要采用先进的安 全技术，如加密通信、防火墙、 入侵检测等，以保护用户数据的
安全和隐私。
网络安全技术还需要考虑防止网 络攻击和恶意入侵等问题，以确 保车载WiFi网络的安全稳定运行。
车载网络系统(汽车电子控制技术)
4）诊断系统总线协议标准是为了满足OBDⅡ（ON Board Diagnose）、OBD Ⅲ或E-OBD（European-On Board Diagnose）标准。
5）多媒体系统总线协议标准分为三种类型，分别是低速、高 速和无线，对应SAE的分类相应为：IDB-C（Intelligent Data BUS-CAN）、IDB-M（Multimedia）和IDB-Wireless。
数据总线原则上用一条导线就足以满足功能要求了，但通常 总线系统上还是配备了第二条导线，信号在第二条导线上按相 反顺序传送的，可有效抑制外部干扰。
10.2 控制器局域网
10.2.1 CAN的基本知识
1.CAN工作原理
当CAN 总线上的一个节点发送数据时，它以报 文形式广播给网络中所有节点，对每个节点来说， 无论数据是否是发给自己的，都对其进行接收， 每组报文开头的11位字符为标识符 （CAN2.0A），定义了报文的优先级，这种报文 格式称为面向内容的编址方案。在同一系统中标 识符是唯一的，不可能有两个节点发送具有相同 标识符的报文。当一个节点要向其它节点发送数 据时，该节点的CPU 将要发送的数据和自己的标 识符传送给本节点的CAN芯片，并处于准备状态， 当它收到总线分配时，转为发送报文状态。
（10）车载网络传 输的基本原理 车载 网络系统由多个控制 单元组成，控制单元 通过收发器（发射/ 接收放大器）并联在 总线导线上，所有控 制单元的地位均相同， 也称之为多主机结构， 如图10-4所示，数 据交换是按顺序连续 完成的。
图10-4 车载CAN网络系统的总线连接图
数据总线是车内电子装置中的一个独立系统，用于在连接的 控制单元之间进行数据交换，如果数据传输总线系统出现故障， 故障就会存入相应的控制单元故障存储器内，可以用诊断仪读 出这些故障。控制单元拥有自诊断功能，通过自诊断功能，还 可识别出与数据传输总线相关的故障。诊断仪读出数据传输总 线故障记录后，可按这些数据准确地查寻故障，控制单元内的 故障记录用于初步确定故障，还可用于读出排除故障后的无故 障说明。
汽车车载网络技术详解最新版精品课件第1章 车载网络系统基础知识
6．比特和字节
计算机中的所有信息都以位（bit，亦称比特，是二进制数 字的最小信息单位）为单位进行存储和处理的。 1千字节（KB）= 210字节，即1 024字节 1兆字节（MB）= 220 字节，即1 024KB（1 048 576字节） l千兆字节（GB）= 230字节，即1 024MB（1 073 741 824字节） 注意：换算系数不是1 000，而是1 024。
DDB/Optical（Domestic 音频系统通信协议将DDB作为音频系统总线采 Digital Bus/Optical） 用光通信
5.6Mbit/s
C&C
MOST（Media Oriented 信息系统通信协议以欧洲为中心，由克莱斯
System Transport） 勒与BMW公司推动
IEEE1394
CAN）
同步的CAN
Byteflight
重视安全、按用途分类的控制用LAN协议通用 时分多路复用（FTDMA）
FlexRay
重视安全、按用途分类的控制用LAN协议
1Mbit/s 10Mbit/s 5Mbit/s
Robert Bosch公司 CIA
BMW公司
BMW公司Daimler Chrysler公司
（2）总线数据传输的要求 1）可靠性高 2）使用方便 3）数据密度大 4）数据传输快
（3）总线数据传输的优点 1）简化线束 2）可以进行设备之间的通信，丰富了功能。 3）通过信息共享减少传感器信号的重复数量。
数字总线信号传递方式
线束对比 a）传统线束 b）采用车载网络后的线束
3．车载网络系统的发展史
1987年12月日本车采用LAN
表1-3 几种车载网络的开发年份、采用厂家与发表年份
汽车车载网络系统的认识
数据链路层最重要的作用就是通过一些数据链路层的协议， 在不可靠的物理链路上实现可靠的数据传输。
16
汽车车载网络系统的认识
五、车载网络的分类
车
用途
载
网
应用范围
络
的
功能
分
类
车身系统局域网 安全系统局域网 动力传动系统局域网 信息系统局域网
车内局域网 车外局域网
面向传感器、执行器控制的低速网络 面向独立模块间数据共享的中速网络 面向高速、实时闭环控制的多路传输网 面向多媒体信息的高速传输网络 面向乘员的安全系统高速、实时网络
12
汽车车载网络系统的认识
三、车载网络系统的组成
通信协议
通信协议是控制通信实体间有效完成信息交换的一组约定 和规则。
通信协议的三要素
（1）语法：确定通信双方之间“如何讲”，即通信信息帧 的格式。 （2）语义：确定通信双方之间“讲什么”，即通信信息帧 的数据和控制信息。 （3）定时规则：确定事件传输的顺序以及速度匹配。
6
汽车车载网络系统的认识
二、车载网络技术的发展史
5、1987年，全球最大的半导体芯片制造商，美国因特尔公司 开发出了第一枚CAN的芯片82526。荷兰最大的电子公司飞 利浦公司很快也推出了CAN的芯片82C200。 6、1992年，奔驰公司作为第一个采用CAN总线技术的公司， 将CAN总线系统装配在客车上。 7、1993年11月，国际化标准组织公布了CAN协议的国际标 准ISO11898以及ISO11519。
9
汽车车载网络系统的认识
三、车载网络系统的组成
数据总线
数据总线是电控单元之间传输数据和信息的通道，就是通 常所说的“信息高速公路”。数据总线的功用就是传输数 据和信息。数据总线的传输介质常用双绞线、同铀电缆和 光纤。
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电动汽车车载网络 引言 汽车技术发展到今天， 很多新型电气设备得到了大量应用， 尤其是电动汽车 的电气系统已经变成了一个复杂的大系统。 为了满足电动汽车各子系统的实时性 要求，需要对公共数据实行共享 电动汽车作为清洁绿色的新能源汽车 , 将在未来交通体系中发挥越来越重要 的作用。 汽车中电器的技术含量和数量是衡景汽车性能的一个重要标志。 汽车电器技 术含量和数量的增加， 意味着汽车性能的提高。 但汽车电器的增加， 同样使汽车 电器之间的信息交且桥梁——线束和与其配套的电器接插件数量成倍上升。在 1955年平均一辆汽车所用线束总长度为 45 米。为了在提高性能与控制线束数量 之问寻求一种有效的解决途径， 在20世纪 80年代初，出现了一种基于数据网络 的车内信息交互方式——车载网络。
一、汽车车载网络的组成 车载网络按照应用加以划分，大致可以分为 4 个系统：车身系统，动力传 动系统、安全系统和信息系统。 图1奥迪A4的车载网络系统 车身系统电路主要有二大块： 主控单兀电路、受控单兀电路、门控单兀电路。
主控单元按收开关信号之后，先进行分析处理，然后通过CAN总线把控制指令发 送给各受控端，各受控端晌应后作出相应的动作。 车前、车后控制端只接收主拄 端的指令，按主控端的要求执行，并把执行的结果反馈给主控端。门控单元不但 通过总接收主控端的指令，还接收车门上的开关信号输入。根据指令和开关信号， 门控单元会做出相应动作，然后把执行结果发往主控单元。 在动力传动系统内，动力传动系统模块的位置比较集中， 可固定在一处，利 用网络将发动机舱内设置的模块连接起来。在将汽车的主要因素一跑、停止 与拐弯这些功能用网络连接起来时，就需要较高速的网络传输速度。动力数据总 线一般连接3块电脑，它们是发动机、ABS/ EDL及自动变速器电脑（动力CAN数 据总线实际可以连接安全气囊、四轮驱动与组合仪表等电脑 ）。总线可以同时传 递10组数据，发动机电脑5组、AB》EDL电脑3组和自动变速器电脑2组。数 据总线以500Kbit /s速率传递数据，每一数据组传递大约需要 0.25ms,每一电
控单元7-20ms发送一次数据。优先权顺序为ABVEDL电控单元--发动机电控单 元 -- 自动变速器电控单元
因此，线束变长， 而且容易受到干扰的影响。 为了防干扰应尽量降低通信速 度，但
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灯朮平调幣转萱/灯 厂是砸硕! —随着安全系统和信息系统的发展高速传输成为必然的趋势。 且人机接口的 模块、节点的数量增加， 通信速度控制及成本相对增加， 使人们不得不摸索更加 高速、安全、廉价的解决方案。此时，汽车总线的概念被提出，总线技术可以大 大提高汽车电器控制的安全性、 可靠性，降低汽车电子电控系统的维护保养成本 和故障率。 二、汽车车载网络分类及其发展趋势 2.1 汽车车载网络的分类
目前存在的多种汽车网络标准，SAE车辆网络委员会将汽车数据传输网划分 为 A、B、C 三类： A 类——面向传感器 / 执行器控制的低速网络，数据传输位速率通常只有
1-10 kbps。主要应用于电动门窗、座椅调节、灯光照明等控制。在 A类网络中
存有多种协议标准，目前正在逐步兴起的是 LIN( Local Interconnect Networ k ) 总线， LIN 是面向低端通讯的一种协议，主要应用在通信速率要求不高的场合， 通过单总线的方
式来实现。 B类一一面向独立模块间数据共享的中速网络， 位速率一般为10-100 kbps。 主要
应用于电子车辆信息中心故障诊断、 仪表显示、 安全气囊等系统， 以减少冗 余的传感器和其他 电子部件 。 B 类网络系统 标准主要包 括控制 器局域网 (Controller Area Network，CAN 协议、车辆局域网(Vehicle Area Network， VAN协议以及汽车工程师协会(Society of Automotive Engineers ， SAE的 SAE J1850协议。在容错性能和故障诊断方面， CAN具有明显的优势，因此在汽
车内部的动力电子系统等对实时性和可靠性要求较高的领域占有不可替代的地 位；考虑到成本因素，VAN也在汽车网络中占有一席之地，特别适用于车身电子 系统等对实时性和可靠性要求相对较低，网络上的某些节点功能比较简单的场 合；SAE J1850由于其通信速率上的限制已逐渐被淘汰。 C类一一面向高速、实时闭环控制的多路传输网，最高位速率可达 1 Mbps
主要用于悬架控制、牵引控制、先进发动机控制、 ABS等系统，以简化分布式控 制和进一步减少车身线束。在 C类标准中，欧洲的汽车制造商从1992年以来，20
基本上采用的都是咼速通讯的 CAN总线标准ISO11898,它可支持咼达1Mb/s的 各种通讯速率；而从1994以来SAEJ1939则广泛用于卡车、大客车、建筑设备、 农业机械等工业领域的高速通讯，其通讯速率为 250kb/s o
另外还有是面向多媒体应用、高速信息流传输的高性能网络，位速率一般 在2Mb/s以上，目前已有位速率达到 400Mb/s的网络标准，800Mb/s的网络标准 也在研究使用。这类网络系统主要连接汽车内部用于多媒体功能的电子设备， 包 括了语音系统、车载电话、音响、电视、车载计算机和 GPS等系统。 一般来说，汽车通信网络可以划分为四个不同的领域， 每个领域都有其独特 的要求： 1•信息娱乐系统：此领域的通信要求高速率和高带宽，有时会是无线传输。 目前主
流应用协议有MOST 2. 高安全的线控系统：由于此领域涉及安全性很高的刹车和导向系统， 所以
它的通信要求高容错性、高可靠性和高实时性。可以考虑的协议有 TTCAN FlexRay、TTP等；
3. 车身控制系统：在这个领域CAN协议己经有了二十多年的应用积累，其中 包括
传统的车身控制和传动控制； 4•低端控制系统：此系统包括那些仅需要简单串行通信的 ECU(Electronic Control Un it) 电子控制单元，比如控制后视镜和车门的智能传感器以及激励器 等，这应该
是LIN总线最适合的应用领域。
图2车上网络系统价格及传输速度分布25000 10DQ0 IDQ[] 125
节点相対歳本 2.2 车载网络的发展趋势
在国外，目前汽车网络总线技术已经成为乘用车和商用车的标准配置， 其中 CAN网络技术应用相当普及。在欧洲，80%勺轿车不同程度上使用了该技术；在美 洲，汽车以使用 J1850 居多，具有代表性的有福特使用的 41.6KbpsJ1850 和通 用、克莱斯勒使用的10.4KbpsJ1850，但从趋势看正逐步往 CAN技术转移。 目前国内使用总线技术的车型几乎全部使用 CAN总线。CAN总线开始在奥迪 A6、奥迪A4宝来、帕萨特BS波罗、菲亚特派力奥、菲亚特西耶那、宝马等 产品上出
现，主要应用在动力传动系统、安全系统 （ABS EBD ASR ESP等）和 车身系统 （门、窗、空调、灯光、锁、座椅等 ）。相关技术的应用也带动了我国网 络总线研发能
力迅速提高， 整车企业可以介入网络总线相关技术标准的研究和制 定，但关键的总线技术还掌握在国外供应商手上。 X-by-Wire ，即线控操作， 是未来汽车的发展方向。 该技术来源于飞机制造， 基
本思想就是用电子控制系统代替机械控制系统，减轻重量，提高可靠性，如 Steer-by-Wire ， Brake-by-Wire 等。由于整个设计思想涉及动力、制动、方向 控制等关键功能，
对汽车网络也就提出了不同要求。在未来的 5 - 10年里， X-by-Wire 技术将使传统的汽车机械系统变成通过高速容错通信总线与高性能 CPU 相连
的电气系统。 我国对于电动汽车车用总线技术的研究，主要分为两个阶段 : 即功能实现阶 段和性能完善阶段。目前国内第一阶段的工作已基本完成， 基于CAN总线的自主 研发技术己经在新能源汽车上取得成功应用。 我国的汽车企业、高校和科研院所， 如一汽集团、上汽集团、长安汽车公司、奇瑞汽车公司、清华大学、北京理工大 学、北京交通大学、同济大学、中科院、中国汽车研究中心等 200 多家单位投入 了大量的人力、财力研发电动汽车。 三、CAN总线在电动汽车中的运用 3.1 总线网络拓扑结构
网络拓扑结构设计是构建网络的第一步， 也是实现各种网络协议的基础， 它 对网络的性能、 可靠性和通信费用等都有很大影响。 网络拓扑结构按照几何图形 的形状可分为 5 种类型 : 总线型拓扑、环形拓扑、星形拓扑、网络拓扑和树形拓 扑，这些形状也可以混合构成混合拓扑结构。 由于电动汽车汽车的网络特点可归 纳为通讯距离短、网络复杂度要求不高、扩展性要求高及实施性可靠性要求高。 考虑其特点，可以综合比较出总线型的结构是最适合车用网络体系的 图3网络拓扑结构 CAN是 一种多主方式的串行通讯总线，位速率高，抗电磁干扰性强，能够检 测出
产生的任何错误。它具有优先权和仲裁功能，多个控制模块通过CANS制器 挂到CAN-bus上,每个节点都有单独的通信处理能力， 形成多主机局部网络。其 可靠性和实时性远
高于普通的通信技术。 3.2 CAN总线框架
目前汽车设计中的网络结构，采用两条CAN网络，一条用于动力系统的高速 CAN速率为250 Kb-1 Mb/s；另一条应用于车身系统的低速 CAN速率为10 Kb-125 Kb/s。高速CAN主要连接对象是发动机控制器、 变速箱、ABS空制器、助力转向， 安全气囊控制器等。低速CAh主要连接和控制的汽车内外部照明、 灯光信号、空 调、组合仪表等其他低速电子控制单元。