Measurement-Based Analysis on Vehicle-to-Vehicle Connectivity in Tunnel Environment

Vehicular ad hoc network (VANET) brings an excellent solution to ensure road safety and transportation efficiency in critical environment like tunnel. Particularly, radio link connectivity of vehicle-to-vehicle (V2V) significantly influences the performance of VANETs. The communication range of the radio systems is a random variable in reality due to the channel fading effect. Therefore, the connectivity model between vehicles in realistic environment is a key for accurate evaluation of system performances. In this paper, we study the V2V connectivity performance in the presence of channel randomness for tunnel environment. Firstly, based on channel measurement campaign, empirical path loss (PL) and small-scale fading channel models are established. Secondly, we study the influence of large-scale fading parameters on V2V connectivity. Thirdly, based on real small-scale fading characteristics, we derive the V2V connectivity probability between any two vehicles under Nakagami fading channel for one-dimensional VANET, and give the closed-form of V2V connectivity probability. Finally, we study the influences of various parameters (i.e., Nakagami fading factor, vehicle density, and neighbor order) on V2V connectivity performance. Results show that with the Nakagami fading shape factor increases, the connectivity probability increases. The shadowing fading can improve connectivity in the VANET; the path loss exponent, transmission distance, and signal-to-noise ratio (SNR) threshold have a negative impact on connectivity probability. The transmit power, vehicle density, and path loss threshold value have a positive impact on connectivity

Customizing Vehicular Ad Hoc Networks to Individual Drivers and Traffic Conditions

This dissertation studies the ability to individualize vehicular ad hoc networks (VANETs) in order to improve safety. Adapting a VANET to both its individual drivers\u27 characteristics and traffic conditions enables it to transmit in a smart manner to other vehicles. This improvement is now possible due to the progress that is being made in VANETs. To accomplish this adaptation, our approach is to use VANET data to learn drivers\u27 characteristics. This information along with the traffic data, can be used to customize the VANETs to individual drivers. In this dissertation, we show that this process benefits all the drivers by reducing the collision probability of the network of vehicles. Our Monte Carlo simulation results show that this approach achieves more than 25% reduction in traffic collision probability compared to the case with optimized equal vehicular communication access for each vehicle. Therefore, it has a considerable advantage over other systems. First, we propose a method to estimate the distribution of a driver\u27s characteristics by employing the VANET data. This is essential for our intended application in accident warning systems and vehicular communications. Second, this estimated distribution and the traffic information are used to adapt the transmission rates of vehicles to each driver\u27s safety level in order to reduce the number of collisions in the network. We derive the packet success probability for a chain of vehicles by taking multi-user interference, path loss, and fading into account. Then, by considering the delay constraints and types of potential collisions, we approximate the required channel access probabilities and illustrate the collision probability. Third, since the packet success probability and thus communication interference affect the collision probability noticeably, we examine various interference models and their effect on the collision probability with more scrutiny. In our analysis, two signal propagation models with and without carrier sensing are considered for the dissemination of periodic safety messages, and it is illustrated how employing more accurate interference models results in a higher level of safety (lower collision probability)for the network. Finally, there is an unclear relation between the intensity of an ad hoc network (the number of vehicles in a certain area) and the performance of the system. Hence, we study a reverse approach in which the geometry (intensity) of the unmanned aerial vehicles varies and certain requirements such as safety and coverage need to be satisfied. The numerical results show that safety and interference limits the coverage of the network and there is only a relatively small range of intensities which satisfy all three

SIMULATION AND ANALYSIS OF VEHICULAR AD-HOC NETWORKS IN URBAN AND RURAL AREAS

According to the American National Highway Traffic Safety Administration, in 2010, there were an estimated 5,419,000 police-reported traffic crashes, in which 32,885 people were killed and 2,239,000 people were injured in the US alone. Vehicular Ad-Hoc Network (VANET) is an emerging technology which promises to decrease car accidents by providing several safety related services such as blind spot, forward collision and sudden braking ahead warnings. Unfortunately, research of VANET is hindered by the extremely high cost and complexity of field testing. Hence it becomes important to simulate VANET protocols and applications thoroughly before attempting to implement them. This thesis studies the feasibility of common mobility and wireless channel models in VANET simulation and provides a general overview of the currently available VANET simulators and their features. Six different simulation scenarios are performed to evaluate the performance of AODV, DSDV, DSR and OLSR Ad-Hoc routing protocols with UDP and TCP packets. Simulation results indicate that reactive protocols are more robust and suitable for the highly dynamic VANET networks. Furthermore, TCP is found to be more suitable for VANET safety applications due to the high delay and packet drop of UDP packets.fi=Opinnäytetyö kokotekstinä PDF-muodossa.|en=Thesis fulltext in PDF format.|sv=Lärdomsprov tillgängligt som fulltext i PDF-format

Efficient Multihop Wireless Communications in VANETs

Oggigiorno, una quota rilevante dei veicoli presenti sul mercato è dotata di notevoli capacità computazionali, sensoriali e cognitive. Questi veicoli ``intelligenti'' otterrebbero un beneficio ancora maggiore da queste potenzialità, attraverso l'impiego delle cosiddette comunicazioni inter-veicolari (Inter-Vehicular Communications, IVCs), un insieme di protocolli, standard e tecnologie in grado di dotare i veicoli di capacità comunicative. In particolare, grazie alle tecnologie IVCs, i veicoli possono creare reti decentralizzate, ed auto-organizzate, comunemente note come Vehicular Ad-hoc NETworks (VANETs). Quest'ultime possono essere formate, sia fra veicoli, determinando la realizzazione di comunicazioni inter-veicolari pure (Vehicle-to-Vehicle communications, V2V), oppure coinvolgendo anche nodi fissi (ad esempio, posti ai lati delle strade), determinando la realizzazione di comunicazioni da veicolo verso infrastruttura (Vehicle-to-Infrastructure, V2I), o da infrastruttura verso veicolo (Infrastructure-to-Vehicle I2V). In questa tesi presenteremo una famiglia di protocolli di instradamento a passi multipli, adatti per un largo spettro di applicazioni nell'ambito delle VANET, quali la prevenzione di incidenti stradali, o applicazioni di raccolta dati, in scenari di tipo V2V, V2I, o I2V. Il primo protocollo che viene proposto è un nuovo schema di broadcasting probabilistico per reti lineari a passi multipli, noto come Irresponsible Forwarding (IF), secondo il quale ogni veicolo decide probabilisticamente se effettuare la ritrasmissione (broadcast) di un messaggio ricevuto. La probabilità di ritrasmissione è determinata sulla base della propria distanza dalla sorgente e della densità spaziale dei propri vicini. I vantaggi principali del protocollo IF rispetto alle soluzioni presenti in letteratura, sono costituiti dalla sua natura intrinsecamente distribuita, dalla bassa latenza, e dall'assenza di overhead, in quanto esso non prevede l'utilizzo di pacchetti ausiliari di supporto Successivamente, presenteremo un secondo protocollo di instradamento probabilistico, noto come Silencing Irresponsible Forwarding (SIF), che riprendendo le idee alla base di IF, permette di ottenere una maggiore efficienza (e.g., un minore numero di ritrasmissioni), senza penalizzarne l'affidabilità, e mantenendo valori di latenza comparabili ad IF. In seguito, verrà inoltre proposto un protocollo di clustering decentralizzato, noto come Cluster-Head Election IF (CHE-IF). Quest'ultimo si propone di sfruttare lo spontaneo processo di formazione di cluster effimeri di nodi nelle reti veicolari, in maniera distribuita ed efficiente. Per ottenere questo risultato, CHE-IF utilizza l'idea alla base di IF, ma introducendo dei pacchetti di controllo aggiuntivi, espressamente dedicati alla realizzazione di cluster di nodi. Infine, le prestazioni di tutti i protocolli proposti verranno testate mediante simulazioni numeriche in realistici scenari veicolari, quali autostrade e strade urbane, assumendo di utilizzare interfacce radio compatibili con lo standard IEEE 802.11p.Nowadays, most of the vehicles available on the market are provided by sensorial, computational, and cognitive skills. Vehicles can achieve a higher awareness level, by exploiting these potentialities through Inter-Vehicular Communications (IVCs), a set of technologies that gives networking capabilities to the vehicles. Leveraging on the IVC technology, vehicles can create decentralized and self-organized vehicular networks, commonly denoted as Vehicular Ad-hoc NETworks (VANETs). These networks can be formed between vehicles, leading to Vehicle-to-Vehicle communications (V2V), or they can also involve some fixed network nodes (e.g., access points or road side unit) leading to the so-called Vehicle-to-Infrastructure (V2I) and Infrastructure-to-Vehicle (I2V) communications. In this thesis we present a family of multihop broadcast forwarding protocols suitable for a wide range of VANETs applications, ranging from accident-preventing, to data collection applications, in V2V, V2I, or I2V scenarios. The first proposed protocol is a new probabilistic-based broadcasting scheme for multi-hop linear networks, denoted as Irresponsible Forwarding (IF), where each vehicle probabilistically rebroadcasts a received data packet on the basis of (i) its distance from the source and (ii) the spatial density of its neighbors. The main advantages of the IF protocol with respect to solutions present in the literature, are its inherently distributed nature, the low-latency, and the absence of overhead, since auxiliary supporting packets are not needed. On the basis of the IF concept, we will present an improved probabilistic forwarding protocol, denoted as Silencing Irresponsible Forwarding (SIF) protocol, able to guarantee a greater efficiency (e.g., a smaller number of retransmissions), without penalizing the reliability, and maintaining a comparable latency. Furthermore, we will propose a novel decentralized clustering protocol, denoted as Cluster-Head Election IF (CHE-IF), whose goal is which of exploiting the spontaneous formation of ephemeral clusters of vehicles in VANETs, in a distributed and efficient manner. This result is achieved by enhancing IF with some additional control messages, aimed at the creation of cluster of nodes. Finally, the performance of the proposed protocols will be tested through numerical simulations in realistic vehicular environments, such as highways and urban roads, by using radio interfaces compliant with the IEEE 802.11p standard

PERFORMANCE EVALUATION OF SINGLE-HOP PERIODIC SAFETY BEACONING FOR VEHICLE-TO-VEHICLE COMMUNICATION IN V ANET

Saving human lives on road has become the prime objective of Vehicular Ad hoc Network (VANET). In order to achieve safety, vehicles maintain neighborhood awareness with the help of safety messages. Providing an efficient safety messaging mechanism is a challenging task in V ANET, due to particular characteristics of VANET, i.e. high mobility, limited channel bandwidth, very short communication duration, and highly dynamic topology. In most of the safety messaging schemes proposed so far, Periodic Safety Beacons (PSBs) are generally considered dispensable in comparison with event-driven messages. However in reality, vehicle-to-vehicle (V2V) PSBs are used to collect critical information required by all the safety messaging schemes and cannot be dispensed. Thus, ensuring optimum QoS for V2V single-hop PSBs is essential for achieving acceptable level of safety. However, thorough performance evaluation ofV2V single-hop PSBs is yet to be carried out. This research comprehensively investigates V2V single-hop periodic safety beaconing in the light of tunable parameters i.e. Beacon Generation Interval (BGI), Safety Beacon Size (SBS), and Communication Range (CR) that govern their behavior. Results from exhaustive simulations show that adjusting tunable parameters solely or combined does not fully satisfY the strict QoS criterion required for safety applications. Overall, an acceptable level of end-to-end delay can be achieved by dynamically adjusting tunable parameters with BGI > 1 OOms, but lower BGI is not suitable with larger SBS. In dense traffic conditions strict PDR criterion of 99% is never achieved beyond lOOm target CR. An exclusive comparison between tunable parameters shows that solely adjusting BGI can attain relatively higher PDR than other tunable parameters while SBS remains the least effective parameter. It is also validated that dynamic adjustment of CR and BGI is necessary for optimal output in terms of PDR. Furthermore, optimal combinations of tunable parameters for different highway service levels with respect to safety application requirements are also presented

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