Abstract

The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-642-39247-4_6 Road traffic is experiencing a drastic increase in recent years, thereby increasing the every day traffic congestion problems, especially in cities. Vehicle density is one of the main metrics used for assessing the road traffic conditions. Currently, most of the existing vehicle density estimation approaches, such as inductive loop detectors or traffic surveillance cameras, require infrastructure-based traffic information systems to be installed at various locations. In this paper, we present I-VDE, a solution to estimate the density of vehicles that has been specially designed for Vehicular Networks. Our proposal allows Intelligent Transportation Systems to continuously estimate the vehicular density by accounting for the number of beacons received per Road Side Unit, as well as the roadmap topology. Simulation results indicate that our approach accurately estimates the vehicular density, and therefore automatic traffic controlling systems may use it to predict traffic jams and introduce countermeasures. Barrachina Villalba, J.; Garrido Picazo, MP.; Fogue, M.; Martínez, FJ.; Cano Escribá, JC.; Tavares De Araujo Cesariny Calafate, CM.; Manzoni, P. (2013). I-VDE: A Novel Approach to Estimate Vehicular Density by Using Vehicular Networks. En Ad-hoc, Mobile, and Wireless Network. Springer. 63-74. doi:10.1007/978-3-642-39247-4_6 Senia 63 74 Document type: Part of book or chapter of book

Abstract

© 2013 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. Road traffic is experiencing a drastic increase, and vehicular traffic congestion is becoming a major problem, especially in metropolitan environments throughout the world. Additionally, in modern Intelligent Transportation Systems (ITS) communications, the high amount of information that can be generated and processed by vehicles will significantly increase message redundancy, channel contention, and message collisions, thus reducing the efficiency of message dissemination processes. In this work, we present a V2X architecture to estimate traffic density on the road that relies on the advantages of combining V2V and V2I communications. Our proposal uses both the number of beacons received per vehicle (V2V) and per RSU (V2I), as well as the roadmap topology features to estimate the vehicle density. By using our approach, modern Intelligent Transportation Systems will be able to reduce traffic congestion and also to adopt more efficient message dissemination protocols. This work was partially supported by the Ministerio de Ciencia e Innovación, Spain, under Grant TIN2011-27543-C03-01, by the Fundación Universitaria Antonio Gargallo and the Obra Social de Ibercaja, under Grant 2013/B010, as well as the Government of Aragón and the European Social Fund (T91 Research Group). Barrachina Villalba, J.; Sangüesa, JA.; Fogue, M.; Garrido, P.; Martínez, FJ.; Cano Escribá, JC.; Tavares De Araujo Cesariny Calafate, CM.... (2013). V2X-d: a Vehicular Density Estimation System that combines V2V and V2I Communications. IEEE. doi:10.1109/WD.2013.6686518 S

Abstract

International audience; Today, thanks to vehicular networks, drivers may receive useful information produced or relayed by neighboring sensors or vehicles (e.g., the location of an available parking space, of a traffic congestion, etc.). In this paper, we address the problem of providing assistance to the driver when no recent information has been received on his/her vehicle. Therefore, we present a cooperative scheme to aggregate, store and exchange these events in order to have an history of past events. This scheme is based on a dedicated spatio-temporal aggregation structure using Flajolet-Martin sketches and deployed on each vehicle. Contrary to existing approaches considering data aggregation in vehicular networks, our main goal here is not to save network bandwidth but rather to extract useful knowledge from previous observations. In this paper, we present our aggregation data structure, the associated exchange protocol and a set of experiments showing the effectiveness of our proposal.

Abstract

International audience; On the path to zero fatalities on the roadways, all vehicles have to periodically broadcast cooperative awareness messages (CAMs) in a timely and reliable manner, even in areas of high traffic density. The carrier senses multiple access with collision avoidance (CSMA/CA) scheme of IEEE 802.11, the de-facto standard for vehicular communications, is known to offer no reliability to broadcast packets that cannot be acknowledged, and to poorly perform at high network load due to collisions and interference. In this paper, an enhanced CSMA/CA protocol is analyzed for vehicular networks, which improves the CAM timeliness and reliability by leveraging full-duplex (FD) transceivers on board. FD devices can listen to the channel while transmitting, thus making collision detection viable. A FD vehicle can detect a CAM collision while sending, promptly abort the packet and retransmit it later. Results achieved through an analytical model under mathematically tractable assumptions, and through extensive system-level simulations in a complex urban environment, show the effectiveness of the protocol to cope with direct collisions, especially in high traffic areas, paving the way towards the realization of cooperative automated driving.