Vehicular networking and computer vision-based distance estimation for VANET application using Raspberry Pi 3

This research was implementing vehicle networking using WIFI connection and computer vision to measure the distance of vehicles in front of a driver. In particular, this works aimed to improve a safe driving environment thus supporting the current technology concept being developed for inter-vehicular networking, VANET, especially in its safety application such as Overtaking Assistance System. Moreover, it can wirelessly share useful visual information such as hazard area of a road accident. In accordance with Vehicle-to-Vehicle (V2V) concept, a vehicle required to be able to conduct networking via a wireless connection. Useful data and video were the objects to be sent over the network established. The distance of a vehicle to other vehicles towards it is measured and sent via WIFI together with a video stream of the scenery experienced by the front vehicle. Haar Cascade Classifier is chosen to perform the detection. For distance estimation, at least three methods have been compared in this research and found evidence that, for measuring 5 meters, the iterative methods shows 5.80. This method performs well up to 15 meters. For measuring 20 meters, P3P method shows a better result with only 0.71 meters to the ground truth. To provide a physical implementation for both the detection and distance estimation mechanism, those methods were applied in a compact small-sized vehicle-friendly computer device the Raspberry Pi. The performance of the built system then analyzed in terms of streaming latency and accuracy of distance estimation and shows a good result in measuring distance up to 20 meters

Game-theoretical design of an adaptive distributed dissemination protocol for VANETs

Road safety applications envisaged for Vehicular Ad Hoc Networks (VANETs) depend largely on the dissemination of warning messages to deliver information to concerned vehicles. The intended applications, as well as some inherent VANET characteristics, make data dissemination an essential service and a challenging task in this kind of networks. This work lays out a decentralized stochastic solution for the data dissemination problem through two game-theoretical mechanisms. Given the non-stationarity induced by a highly dynamic topology, diverse network densities, and intermittent connectivity, a solution for the formulated game requires an adaptive procedure able to exploit the environment changes. Extensive simulations reveal that our proposal excels in terms of number of transmissions, lower end-to-end delay and reduced overhead while maintaining high delivery ratio, compared to other proposalsPeer ReviewedPostprint (published version

Adaptive video-streaming dissemination in realistic highway vehicular ad-hoc networks

The dissemination of video information contents migth enhance the performances of safety-related applications in vehicular ah-hoc networks (VANETs). A major problem concerns the high sensitivity of the compressed video streams to the severe channel conditions in wireless ad-hoc networks. The reliable dissemination of video contents in mobile environments is recognized as one of the main challenges for the developing and deploying of VANETs. To improve the robustness of dissemination, we propose RCP+ (Road-Casting Protocol) scheme for distributing high-definition video contents in VANETs. RCP+ is a cross layer dissemination mechanism for video safety messages that specifically addresses highway scenarios with zero infrastructure support. Also, a comparison of one of the most popular and widely spread video encoder H.264/AVC with respect to the recently released video coding scheme H.265/HEVC is presented. The comparison is performed by means of simulations showing differences between encoding algorithms in terms of perceived quality. The results indicate a better performance of HEVC based encoding algorithm in comparison to AVC in VANET environments.Peer ReviewedPostprint (published version

Adaptive video-streaming dissemination in realistic highway vehicular ad-hoc networks

The dissemination of video information contents migth enhance the performances of safety-related applications in vehicular ah-hoc networks (VANETs). A major problem concerns the high sensitivity of the compressed video streams to the severe channel conditions in wireless ad-hoc networks. The reliable dissemination of video contents in mobile environments is recognized as one of the main challenges for the developing and deploying of VANETs. To improve the robustness of dissemination, we propose RCP+ (Road-Casting Protocol) scheme for distributing high-definition video contents in VANETs. RCP+ is a cross layer dissemination mechanism for video safety messages that specifically addresses highway scenarios with zero infrastructure support. Also, a comparison of one of the most popular and widely spread video encoder H.264/AVC with respect to the recently released video coding scheme H.265/HEVC is presented. The comparison is performed by means of simulations showing differences between encoding algorithms in terms of perceived quality. The results indicate a better performance of HEVC based encoding algorithm in comparison to AVC in VANET environments.Peer Reviewe

INRISCO: INcident monitoRing in Smart COmmunities

Major advances in information and communication technologies (ICTs) make citizens to be considered as sensors in motion. Carrying their mobile devices, moving in their connected vehicles or actively participating in social networks, citizens provide a wealth of information that, after properly processing, can support numerous applications for the benefit of the community. In the context of smart communities, the INRISCO [1] proposal intends for (i) the early detection of abnormal situations in cities (i.e., incidents), (ii) the analysis of whether, according to their impact, those incidents are really adverse for the community; and (iii) the automatic actuation by dissemination of appropriate information to citizens and authorities. Thus, INRISCO will identify and report on incidents in traffic (jam, accident) or public infrastructure (e.g., works, street cut), the occurrence of specific events that affect other citizens' life (e.g., demonstrations, concerts), or environmental problems (e.g., pollution, bad weather). It is of particular interest to this proposal the identification of incidents with a social and economic impact, which affects the quality of life of citizens.This work was supported in part by the Spanish Government through the projects INRISCO under Grant TEC2014-54335-C4-1-R, Grant TEC2014-54335-C4-2-R, Grant TEC2014-54335-C4-3-R, and Grant TEC2014-54335-C4-4-R, in part by the MAGOS under Grant TEC2017-84197-C4-1-R, Grant TEC2017-84197-C4-2-R, and Grant TEC2017-84197-C4-3-R, in part by the European Regional Development Fund (ERDF), and in part by the Galician Regional Government under agreement for funding the Atlantic Research Center for Information and Communication Technologies (AtlantTIC)