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.

Extending Access Point Connectivity through Opportunistic Routing in Vehicular Networks

Abstract: -Nowadays, the navigation systems available on cars are becoming more and more sophisticated. They greatly improve the experience of drivers and passengers by enabling them to receive map and traffic updates, news feeds, advertisements, media files, etc. Unfortunately, the bandwidth available to each vehicle with the current technology is severely limited. There have been many reports on the inability of 3G networks to cope with large size file downloads, especially in dense and mobile settings. A possible alternative is provided by WiFi access points (APs) that are being installed in several countries along the main routes and in popular areas. Although this approach significantly increases the available bandwidth, it still does not provide a fully satisfactory solution due to the limited transmission range (usually a few hundred meters). In this paper we present a novel routing protocol, based on opportunistic vehicle to vehicle communication, to enable efficient multi-hop routing capabilities between mobile vehicles and APs. Unlike prior work, this protocol fully supports two- way communication, i.e., the traditional vehicle-to-AP as well as the more challenging AP-to-vehicle. We leverage the information offered by the navigation system in terms of final destination and path, to i) route packets to the closest AP and ii) to route replies back to the moving vehicle efficiently.

Energy harvesting in vehicular networks: a contemporary survey

Abstract: Vehicular networks have recently been witnessing an upsurge of interest in energy consumption control. Precisely, in the majority of vehicular networking scenarios, roadside units are deployed along roadways in rural areas as well as on the sides of long highways where a direct connection to the electric grid is merely available. In such situations, these roadside units will be equipped with rechargeable batteries with maintenance requiring costly human intervention. Thus far, the literature offers several proposals of efficient operation schemes for roadside units aiming at optimizing their energy consumption, hence, elongating their duration of availability and participation in the network. Energy harvesting presents itself as an appealing alternative to power/recharge nodal batteries in wireless networks. This article starts by presenting a concise general overview of energy harvesting sources, techniques, and applications. Second, it investigates the feasibility of energy harvesting in vehicular networks, specifically the different challenges confronting its applicability in vehicular environments. Finally, pending related open research problems and directions are presented.

Measuring the performance of IEEE 802.11p using ns-2 simulator for vehicular networks

Abstract: The 802.11p protocol, also known as wireless access for the vehicular environment (WAVE), has recently gained momentum in the area of research and development. The WAVE protocol provides enhancements to the physical (PHY) and medium access control (MAC) layers of the existing 802.11 wireless standards. These enhancements are required to support the intelligent transportation systems (ITS) initiatives of the US Department of Transportation regarding vehicle-to-vehicle, vehicle-to-infrastructure, and infrastructure-to-vehicle communication. Many research groups have contributed to the development of the protocol. Many of the same individuals have worked to extend the ns-2 network simulator to correctly simulate wireless mobile networking, specifically vehicle adhoc networks (VANETs). The objective of this research project is to measure the performance of the WAVE protocol at the MAC layer, using the ns-2 simulator. Specifically, the simulations measure aggregate throughput, average delay, and packet loss metrics.

Machine-vision systems for intelligent transportation systems

Abstract: ITS can use machine vision to detect lane markings, vehicles, pedestrians, road signs, traffic conditions, traffic incidents, and even driver drowsiness. Challenges include making machine-vision systems less expensive, more compact, and more robust in various weather and traffic conditions.