Vehicular communication systems

About: Vehicular communication systems is a research topic. Over the lifetime, 2532 publications have been published within this topic receiving 64775 citations. The topic is also known as: V2V & vehicle-to-vehicle.

Message transmission for vehicle-to-vehicle communication enabled devices

Abstract: A method of transmitting a message is disclosed, wherein the method is for a vehicle-to-vehicle communication enabled device adapted to operate in accordance with a vehicle-to-vehicle communication protocol and in accordance with a cellular communication protocol for communication with a wireless communication network. The method comprises determining (110) a geographical position of the vehicle-to-vehicle communication enabled device and determining (150), based on the determined geographical position, whether at least one direction extending from the determined geographical position lacks other vehicle-to-vehicle communication enabled devices for reception of the message. If at least one direction lacks other vehicle-to-vehicle communication enabled devices for reception of the message, the method comprises transmitting (170) a report to a network node of the wireless communication network, wherein the report indicates the message. Corresponding computer program product, arrangement and communication device are also disclosed. This method ensures that safety relevant messages are always delivered to all relevant V2V enabled devices, even if the device density is too low, in that it bridges the gap by using the cellular network as a backup.

Vehicular Cloud: Stochastic Analysis of Computing Resources in a Road Segment

Abstract: Considerable attention has been assigned to Vehicular Cloud towards identifying methods to utilize under-used, available computing and physical resources of vehicles effectively. Most work on vehicular cloud is so far on the taxonomy definition level, and the dynamically changing amount of available resources characterizes vehicular cloud as more cumbersome and complex than the traditional Clouds. In this paper, we define and analyze the expected number of vehicles in a roadway segment. These vehicles can serve as the building blocks for the vehicular cloud, enabling a tremendously large set of applications that benefit the whole traffic system. To contribute with the analysis, two types of traffic scenarios are considered in this work. We use a macroscopic traffic model to investigate the free-flow traffic, and we utilize the queuing theory to observe the queuing-up traffic. The average number of vehicles within a roadway segment is calculated using stochastic models. The results show the boundaries on enabling vehicular cloud, allowing to determine a range of parameters for simulating vehicular clouds.

Traffic light based time stable geocast (T-TSG) routing for urban VANETs

Abstract: Vehicular Ad Hoc Networks is a self-organizing, distributed communication network formed by highly Mobile Vehicles. This type of networks is developed as part of Intelligent Transportation Systems (ITS) to bring significant improvement to the transportation systems. One of the main goal of ITS, is to increase safety on road and reduce traffic congestion. Safety application requires messages to be sent to all nodes which belong to a particular geographical region. This message must be available to all the vehicles which enter the Geographical Region within a certain Time Period. Also, there are wide varieties of scenarios in VANETs to communicate. In urban environment, there are many streets, intersections, avenues etc. Hence, Driver has many options to reach his destination. In Highway environment, vehicles stay in the same road as there are only few entrances and exits. From a routing perspective, there are different options to forward information in an urban environment depending upon the behavior of traffic lights whereas in highway, most of the same set of vehicles may be used to forward information. In this paper, we have proposed a novel time stable geocast routing protocol nameed as traffic light based time stable geocast (T-TSG) routing protocol for informing vehicles after an accident in urban vehicular environment. T-TSG is a three phase routing approach based on traffic light behavior. It has better message delivery rate, negligible network load for life time management and lower end-to-end delay performance under simulated urban environment.

Extensive Experimental Characterization of Communications in Vehicular Ad Hoc Networks within Different Environments

Abstract: Test-bed based research is an important aspect in mobile ad hoc networks (MANETs) and especially in vehicular ad hoc networks (VANETs). However because of the high associated cost, we do not see as many high quality experiment studies as simulation or analysis ones. In this paper, we present extensive experimental measurements of vehicle-to-vehicle communication on several typical scenarios in order to study the critical factors that affect multimedia applications over an IEEE 802.11 VANET. Unlike [4], we proof that in addition to short message transfer, the deployment of multimedia applications is also feasible. We found that network performances are clearly different according to the environment (city, highway, etc.), the distance between vehicles and the vehicles speed.

Cross-layer architecture for congestion control in Vehicular Ad-hoc Networks

Abstract: Vehicular Ad-hoc Networks (VANETs) are special kind of Mobile Ad-hoc Networks (MANETs). The distinctive characteristics of the VANETs include high speed of vehicular nodes and high variability in node density. Congestion detection and control protocols have been proved to be an efficient method for improving network performance and are well studied for the MANET environment. However, they often result in sub-optimal network performance for the vehicular network environment due to the specialized characteristics of VANET. In this paper we present an adaptive and distributed cross-layer congestion detection and control protocol for the VANET environment. During the congestion detection phase, information from each layer of the network protocol stack is combined and mapped on to congestion levels. In the subsequent congestion control phase parameters like contention window, transmission rate and transmit power are jointly adjusted to improve on the network performance. The effectiveness of the proposed model is evaluated through mathematical analysis and simulation-based studies.