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V2V
Published in Prashant Ranjan, Ram Shringar Rao, Krishna Kumar, Pankaj Sharma, Wireless Communication, 2023
Prashant Ranjan, Ram Shringar Rao, Krishna Kumar, Pankaj Sharma
In VANETs, the vehicles are equipped with dedicated short-range computing devices, sensing devices, digital roadmap, RADAR, GPS and other information and location pointing devices with advanced processing tools [4]. VANET systems have three types of communications i.e. Vehicle-to-Vehicle (V2V), Vehicle-to-Road Side Unit (V2R) and Vehicle-to-Pedestrian (V2P) communication respectively [5]. V2V communication is a pure wireless infrastructure-less ad-hoc communication between vehicles. V2V communication uses DSRC device to transmit messages [6]. V2V communication does not have a problem with vehicle shadowing in which smaller vehicles are shadowed by a larger vehicle. V2V communication increases driving comforts and safety measures of drivers and passengers during the driving time [7] [8]. Figure 5.1, presents the VANET architecture, its communication systems and different domains discussed as follows.
Promising Applications
Published in Wen Sun, Qubeijian Wang, Nan Zhao, Haibin Zhang, Chao Shen, Ultra-Dense Heterogeneous Networks, 2023
Wen Sun, Haibin Zhang, Nan Zhao, Chao Shen, Lawrence Wai-Choong Wong
Autonomous vehicles can achieve efficient and reliable information exchange through V2V and V2I communication. However, with the growing demand for mobile services and the rapid development of self-driving technology, the amount of data required for autonomous driving systems has shown an exponential growth trend. The advanced driving has brought great challenges to autonomous vehicles, such as high data rates, large network capacity, heterogeneous network integration, and differentiated QoS guarantees. To address these challenges, UDNs are applicable solutions. UDNs presents three use cases of eMBB, URLLC, and mMTC to ensure the performance of the VANETs. In addition, UDNs also show eV2X use cases for vertical domains that support vehicle communication and data services. However, some challenges also need to be addressed to implement UDN-supported self-driving, such as highly time-varying network topology and channel status.
Emerging Technologies and Associated Terminologies
Published in Amalendu Chatterjee, Autonomous and Integrated Parking and Transportation Services, 2019
Vehicle to vehicle (V2V) is a way to share road conditions, traffic jam, and traffic collision information with the vehicle (car or truck) in front or behind you. It enables you to take corrective action when necessary, such as selecting quieter routes via less congested roads. V2V can enhance road safety by warning drivers of potential blind spot collisions. VII, on the other hand, connects vehicles to the Intelligent Transportation Services (ITS) infrastructure for emergency services and applications such as highway traffic management. Highway management services include probing vehicles for traffic, weather, and road surface condition, route advisories, crashes, incident responses, and other warning services.8 VII could be a useful tool for broadcasting parking space availability to the potential drivers (commercial or private).
Smart Mobility in Smart Cities: Emerging challenges, recent advances and future directions
Published in Journal of Intelligent Transportation Systems, 2023
Soumia Goumiri, Saïd Yahiaoui, Soufiene Djahel
Cooperative and connected vehicles is another solution to enhance road safety through enabling the exchange of data between the vehicles, using Vehicle-to-Vehicle (V2V) communication, or the vehicles and the road infrastructure, using Vehicle-to-Infrastructure (V2I) communication, as well as between the vehicles and other road users such as pedestrians and cyclists using V2X communication. To minimize the risk of accidents when performing maneuvers, such as lane change, vehicles need to coordinate their actions using V2V communication to improve the maneuver efficiency and safety level J. Hodgkiss et al. (2019). Vehicles can also report relevant data about accidents, congestion, state of the road, drivers status, etc. This data can be very useful in enabling faster reaction to incidents, minimizing the number of casualties, and timely traffic information delivery to drivers to avoid congested areas, thus reducing further travel delays and the risk of accidents since drivers who are stuck in congestion tend to drive faster to compensate the experienced delay. This critical data must be routed efficiently in order to provide drivers with timely accurate information.
Eco-friendly platooning operation algorithm of the electric vehicles
Published in Journal of Intelligent Transportation Systems, 2023
Joonwon Jang, Sung Il Kwag, Young Dae Ko
Automated vehicles have been commercialized in recent years with the development of autonomous driving technology and communication technology. The autonomous driving technologies, such as LKA (lane keeping assist), LFA (lane following assist), SCC (smart cruise control), and AEB (autonomous emergency braking), have made it possible for vehicles to drive themselves safely on the road. In case of communication technologies, V2V (vehicle to vehicle) and V2I (vehicle to infrastructure) enable autonomous vehicles to consider the surrounding traffic conditions. According to the SAE (Society of Automotive Engineers International), autonomous driving can be defined into six categories that range from no driving autonomation to full driving autonomation. The USDoT (United States Department of Transportation) declared that the SAE document was to be used in the Federal Automated Vehicles Policy. In 2017, in the United States, the NHTSA (National Highway Traffic Safety Administration) provided voluntary guidance through Automated Driving Systems 2.0, which focus on the new operating guidance on SAE Level 3 (USDoT, Ensuring American Leadership in Automated Vehicle Technologies Automated Vehicles 4.0, 2020), which has presently resulted in 18 states passing legislation related to autonomous vehicles. The German government also allowed level 3 in 2017. In level 3, the automated vehicles drive themselves in normal conditions, but they require a driver to quickly intervene in case of an emergency.
Human-centred design of next generation transportation infrastructure with connected and automated vehicles: a system-of-systems perspective
Published in Theoretical Issues in Ergonomics Science, 2023
Yiheng Feng, Yunfeng Chen, Jiansong Zhang, Chi Tian, Ran Ren, Tianfang Han, Robert W. Proctor
If onboard sensors are expressed metaphorically as human eyes, then V2X communications are ‘ears’ of CAVs that receive external information. V2V communications convey other vehicles’ real-time information such as position, speed, acceleration, brake system status, and vehicle size. V2I communications transmit information from the infrastructure side including traffic signal status, road map, and traveler information (SAE International 2009). V2X communications complement the onboard sensors’ perception capabilities. Typical V2X communication range is longer (e.g. a few hundred meters; Kenney 2011) than the detection range of onboard sensors. Also, onboard sensors can only detect and track objects within the line-of-sight, but V2X communication can ‘hear’ from vehicles that are occluded by obstacles.