Understanding Vehicle-to-Vehicle IEEE 802.11p Beaconing Performance in Real-World Highway Scenarios

Periodic exchange of situational information (beacons) is at the basis of most active safety applications in vehicular environments. Despite its fundamental role in raising the level of "situational awareness" onboard vehicles, very little is known to date on beaconing performance in a real vehicular environment. This paper analyzes the results of two measurement campaigns that have been designed with the purpose of disclosing beaconing performance in a variety of vehicular links, for what concerns vehicle configuration (tall/short), line-of-sight conditions (LOS/NLOS), as well as single-hop or two-hop propagation of the information reported in the beacons. For the first time, beaconing performance is characterized in terms of not only the packet (beacon) delivery rate (PDR), but also in terms of the packet (beacon) inter-reception (PIR) time. The latter metric has been suggested in the literature as more accurately measuring the level of "situation awareness" onboard vehicles than the traditional PDR metric. This paper also presents a simulation-based analysis aimed at estimating the benefit of multi-hop propagation of situational information beyond the second hop of communication. The analysis of the data collected in the measurement campaigns as well as the simulation-based analysis disclose a number of interesting insights which might prove useful in the design of active safety applications. Finally, another major contribution of this paper is promoting the Gilbert-Elliot model, previously proposed to model bit-error bursts in packet switched networks, as a very accurate model of beacon reception behavior observed in real-world scenarios

Information Dissemination in VANETS by Piggybacking on Beacons -- An Analysis of the Impact of Network Parameters

Piggybacking on beacons is a forwarding technique that is regularly used in vehicular ad-hoc network (VANET) research as a means to disseminate data. With this technique data is attached to and transmitted along with scheduled beacons, without changing the timing of the beacons. In this paper we evaluate the effect that several network parameters - such as the network density, the beacon frequency, and the transmission power level - have on the piggybacking performance. As performance metrics we measure the delay, the reception probability, and the reception probability as a function of time elapsed since transmission. Our eventual goal is to model the latter metric as a function of the network parameters. Here we analyse which network parameters should be taken into account in such a model. We show that the transmission power, the transmission bit rate, the inter-node distance, the dissemination distance, and the beacon frequency should be taken into account

Situational Awareness Enhancement for Connected and Automated Vehicle Systems

Recent developments in the area of Connected and Automated Vehicles (CAVs) have boosted the interest in Intelligent Transportation Systems (ITSs). While ITS is intended to resolve and mitigate serious traffic issues such as passenger and pedestrian fatalities, accidents, and traffic congestion; these goals are only achievable by vehicles that are fully aware of their situation and surroundings in real-time. Therefore, connected and automated vehicle systems heavily rely on communication technologies to create a real-time map of their surrounding environment and extend their range of situational awareness. In this dissertation, we propose novel approaches to enhance situational awareness, its applications, and effective sharing of information among vehicles.;The communication technology for CAVs is known as vehicle-to-everything (V2x) communication, in which vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) have been targeted for the first round of deployment based on dedicated short-range communication (DSRC) devices for vehicles and road-side transportation infrastructures. Wireless communication among these entities creates self-organizing networks, known as Vehicular Ad-hoc Networks (VANETs). Due to the mobile, rapidly changing, and intrinsically error-prone nature of VANETs, traditional network architectures are generally unsatisfactory to address VANETs fundamental performance requirements. Therefore, we first investigate imperfections of the vehicular communication channel and propose a new modeling scheme for large-scale and small-scale components of the communication channel in dense vehicular networks. Subsequently, we introduce an innovative method for a joint modeling of the situational awareness and networking components of CAVs in a single framework. Based on these two models, we propose a novel network-aware broadcast protocol for fast broadcasting of information over multiple hops to extend the range of situational awareness. Afterward, motivated by the most common and injury-prone pedestrian crash scenarios, we extend our work by proposing an end-to-end Vehicle-to-Pedestrian (V2P) framework to provide situational awareness and hazard detection for vulnerable road users. Finally, as humans are the most spontaneous and influential entity for transportation systems, we design a learning-based driver behavior model and integrate it into our situational awareness component. Consequently, higher accuracy of situational awareness and overall system performance are achieved by exchange of more useful information