Update Delay: A new Information-Centric Metric for a Combined Communication and Application Level Reliability Evaluation of CAM based Safety Applications

Standard network metrics, such as throughput, latency and reception probability, are the most popular performance indicators used in the literature to describe and compare communication protocol variations. However, these “traditional” network-centric PI are not adapted to the distributed, information-centric nature of the beaconing communication pattern, nor do they cover application level reliability or freshness of information. In this paper, we introduce a more suitable metric called Update Delay, represented as a Complementary Cumulative Distribution Function (CCDF). We will show how this single Update Delay performance indicator can be an optimal representation of the freshness and reliability of the information about a certain transmitter, i.e. awareness about vehicles and their current state in the vicinity. This paper extends on the methodological aspects of the approach, as well as introduces several concrete examples

Multihop Beaconing Forwarding Strategies in Congested IEEE 802.11p Vehicular Networks

Multi-hop propagation of situational information is a promising technique for improving beaconing performance and increasing the degree of situational awareness onboard vehicles. However, limitation on beacon size prescribed by standardization bodies implies that only<br> information about 3-4 surrounding vehicles can be piggybacked in a beacon packet. In most traffic situations, the number of vehicles within transmission range is much larger than 3-4, implying that multi-hop forwarding strategies must be devised to select which neighboring<br> vehicle\u27s information to include in a transmitted beacon. In this paper, we investigate the effectiveness of different multi-hop forwarding strategies in delivering fresh situational information to surrounding vehicles. Effectiveness is estimated in terms of both average information age<br> and probability of experiencing a situational-awareness blackout of at least 1 sec. Both metrics are estimated as a function of the hop distance from the transmitting vehicle, and in presence of different level of radio channel congestion. The investigation is based on extensive simulations<br> whose multi-hop communication performance is corroborated by real-world measurements. <br> The results show that network-coding based strategies substantially improve forwarding performance as compared to a randomized strategy, reducing the average information age of up to 60%, the blackout probability of up to two orders of magnitude.<br> We also consider the effect of multi-hop propagation of situational information on the reliability of a forward collision warning application, and show that network-coding based propagation yields a factor three improvement of reliability with respect to a randomized forwarding strategy, and even higher improvements with respect to the case of no propagatio

Adaptive Transmission Power with Vehicle Density for Congestion Control

The Intelligent Transport Systems (ITS) employs the Vehicular Ad-hoc Networks (VANET) technology to prevent and reduce accidents on highways. VANET uses wireless communication technology that includes protocols and applications that provides safety and non-safety features for a safe and comfortable driving experience. A major problem with VANET is that the network channel utilized for the transmission of network packets for awareness becomes congested due to vehicles competing to use the channel leading to packet loss, high transmission delay and unfair resource usage. These problems would eventually lead to the periodic exchange of Basic Safety Messages not being delivered on time, thereby making VANET unreliable. Researchers have focused on numerous approaches for controlling congestion on the network channel such as adapting the rate of transmission of packets i.e. the number of packets that can be sent per second or adjusting the transmission power which is the distance a packet can travel. An approach is proposed in this thesis to adapt the transmission power, based on the vehicle density state of the network, with the aim of reducing congestion on the network channel and improving the performance of VANET. Results indicate that this can lead to improved performance in terms of reduced packet loss and inter-packet delay

Multihop Beaconing Forwarding Strategies in Congested IEEE 802.11p Vehicular Networks

Abstract?Multi-hop propagation of situational information is a promising technique for improving beaconing performance and increasing the degree of situational awareness onboard vehicles. A possible way of achieving this is by piggyback information on the beacon packets that are sent periodically by each vehicle in the network, as prescribed by the DSRC and ETSI standards. However, prescribed limitations on beacon size imply that only information about a very small number of surrounding vehicles can be piggybacked in a beacon packet. In most traffic situations, this number is well below the typical number of vehicles within transmission range, implying that multi-hop forwarding strategies must be devised to select which neighboring vehicle?s information to include in a transmitted beacon. In this paper, we designed different multi-hop forwarding strategies, and assessed their effectiveness in delivering fresh situational information to surrounding vehicles. Effectiveness is estimated in terms of both information age and probability of experiencing a potentially dangerous situational-awareness blackout. Both metrics are estimated as a function of the hop distance from the transmitting vehicle, and in presence of different level of radio channel congestion. The investigation is based on extensive simulations whose multi-hop communication performance is corroborated by real-world measurements. The results show that network-coding based strategies substantially improve forwarding performance as compared to a randomized strategy, reducing the average information age of up to 60%, and the blackout probability of up to two orders of magnitude.We also consider the effect of multi-hop propagation of situational information on the reliability of a forward collision warning application, and show that network-coding based propagation yields a factor three improvement of reliability with respect to arandomized forwarding strategy, and even higher improvements with respect to the case of no propagation

Design and evaluation of safety-critical applications based on inter-vehicle communication

Inter-vehicle communication has a potential to improve road traffic safety and efficiency. Technical feasibility of communication between vehicles has been extensively studied, but due to the scarcity of application-level research, communication\u27s impact on the road traffic is still unclear. This thesis addresses this uncertainty by designing and evaluating two fail-safe applications, namely, Rear-End Collision Avoidance and Virtual Traffic Lights

Serviceorientiertes Mehrkanal-Beaconing in Fahrzeug-Ad-hoc-Netzen

The interconnection of vehicles is an important topic concerning the enhancement of traffic safety and trffic efficiency. Therefore, vehicles exchange position and state information with each other to establish an awareness level for the calculation of collision probabilities with their neighbors. To recognize critical safety situations it is essential to receive information reliably. However, these systems are typically based on wireless ad-hoc networks that cannot guarantee reliable packet transmission. This is especially the case in situations where a high number of communication nodes exist. The aim of this work at hand is the definition of a beaconing algorithm that enables the establishment of a desired awareness level for critical safety situations especially in high density traffic scenarios. First, representative scenarios for collision detection and collision avoidance were specified and metrics for the evaluation of the beaconing algorithms were defined. Based on these metrics the performance of beaconing algorithms with different static periodical update rates was evaluated. It is presented that these kinds of beaconing algorithms cannot provide sfficient results with respect to the required constant information throughput in high density traffic situations. To provide a high awareness level for each vehicle in its individual situation in spite of an unreliable communication channel a service-oriented beaconing approach is dened in this work. It is based on a request/response communication scheme to compensate particular packet loss. Hereby, a broadcast and a unicast occurrence of the algorithm are defined accordingly to the corresponding representative scenarios. It is presented that the service-oriented beaconing approach provides a signicant benefit with respect to the information throughput for low and middle traffic density situations. However, in high density situations the benefit of this approach is decreasing due to the increased communication overhead. This is a result of using one single communication channel. To achieve a high awareness level also in high density trac situations, a signi- cant modification was defined. Therefore, the usage of multiple communication channels was introduced to distribute the communication load over several channels. It is specified to send all service responses on a dedicated service channel to reduce the load on the control channel where the service requests are transmitted. After an extensive evaluation of the multi-channel utilization in vehicle ad-hoc networks using IEEE 802.11p it is shown that the multi-channel version of the service-oriented beaconing approach can achieve significant benefits concerning the information throughput for the collision detection and collision avoidance scenarios even in high density traffic situations.Die Vernetzung von Fahrzeugen untereinander ist ein wichtiger Aspekt im Hinblick auf die Erh�ohung der Verkehrssicherheit und -effizienz. Daf�ur tauschen Fahrzeuge mit ihren Nachbarn Positions- und Zustandsinformationen aus, um eine Wissensbasis zur Berechnung von Kollisionswahrscheinlichkeiten aufzubauen. Um kritische Situationen erkennen zu können, ist es notwendig, Informationen zuverl�assig empfangen zu können. Allerdings werden zur Umsetzung derartiger Systeme typischerweise WLAN-basierte Ad-hoc-Netze verwendet, welche vor allem bei einer hohen Anzahl an Teilnehmern keine zuverlässige Übertragung von Nachrichten gewährleisten. Ziel dieser Arbeit ist es, einen Beaconing-Algorithmus zu entwickeln, welcher es ermöglicht bei jeder Fahrzeugdichte die geforderte Wissensbasis zur Erkennung von sicherheitskritischen Situationen aufzubauen. Aufbauend auf der Spezifizierung der Situationen zur Kollisionserkennung und Kollisionsvermeidung und den damit definierten Metriken zur Beurteilung von Beaconing Algorithmen, wird zun�achst die Güte von Beaconing-Ansätzen mit unterschiedlichen statischen Beacon-Wiederholratn untersucht. Es wird gezeigt, dass dieser Ansatz die Anforderungen nach einem gleichbleibenden Informationsdurchsatz bei hohen Fahrzeugdichten nicht erfüllen kann. Um trotz der unzuverlässigen Nachrichtenübertragung den geforderten Informationsdurchsatz in Abhängigkeit der individuellen Situation eines jeden Fahrzeugs zu gew�ahrleisten, wird in dieser Arbeit ein serviceorientierter Beaconing-Ansatz eingeführt. Hierbei wird jeweils eine Variante für die entsprechende spezifizierte Situation definiert. Es wird gezeigt, dass der serviceorientierte Ansatz unter Nutzung von einem Kommunikationskanal bei niedrigen und mittleren Fahrzeugdichten eine Verbesserung des Informationsdurchsatzes erzielen kann. Bei hohen Fahrzeugdichten sinkt der Mehrwert allerdings aufgrund des hohen Nachrichtenaufkommens. Auf diesen Erkenntnissen wird eine Mehrkanal- Variante des Beaconing-Ansatzes vorgeschlagen. Hierbei sollen zur Serviceerbringung gesonderte Kan�ale genutzt werden, um die Kommunikationslast besser verteilen zu können. Nach einer ausgiebigen Evaluierung der Mehrkanalnutzung in Fahrzeuge-Ad-hoc-Netzen und unter Berücksichtigung der dabei existierenden Einschränkungen kann gezeigt werden, dass die Mehrkanal-Variante des serviceorientierten Beaconing-Ansatzes signifikante Verbesserungen für den Informationsdurchsatz sowohl in der Kollisionserkennungs- als auch Kollisionsvermeidungsphase über alle Fahrzeugdichten erzielen kann

Cooperative Relative Positioning for Vehicular Environments

Fahrerassistenzsysteme sind ein wesentlicher Baustein zur Steigerung der Sicherheit im Straßenverkehr. Vor allem sicherheitsrelevante Applikationen benötigen eine genaue Information über den Ort und der Geschwindigkeit der Fahrzeuge in der unmittelbaren Umgebung, um mögliche Gefahrensituationen vorherzusehen, den Fahrer zu warnen oder eigenständig einzugreifen. Repräsentative Beispiele für Assistenzsysteme, die auf eine genaue, kontinuierliche und zuverlässige Relativpositionierung anderer Verkehrsteilnehmer angewiesen sind, sind Notbremsassitenten, Spurwechselassitenten und Abstandsregeltempomate. Moderne Lösungsansätze benutzen Umfeldsensorik wie zum Beispiel Radar, Laser Scanner oder Kameras, um die Position benachbarter Fahrzeuge zu schätzen. Dieser Sensorsysteme gemeinsame Nachteile sind deren limitierte Erfassungsreichweite und die Notwendigkeit einer direkten und nicht blockierten Sichtlinie zum Nachbarfahrzeug. Kooperative Lösungen basierend auf einer Fahrzeug-zu-Fahrzeug Kommunikation können die eigene Wahrnehmungsreichweite erhöhen, in dem Positionsinformationen zwischen den Verkehrsteilnehmern ausgetauscht werden. In dieser Dissertation soll die Möglichkeit der kooperativen Relativpositionierung von Straßenfahrzeugen mittels Fahrzeug-zu-Fahrzeug Kommunikation auf ihre Genauigkeit, Kontinuität und Robustheit untersucht werden. Anstatt die in jedem Fahrzeug unabhängig ermittelte Position zu übertragen, werden in einem neuartigem Ansatz GNSS-Rohdaten, wie Pseudoranges und Doppler-Messungen, ausgetauscht. Dies hat den Vorteil, dass sich korrelierte Fehler in beiden Fahrzeugen potentiell herauskürzen. Dies wird in dieser Dissertation mathematisch untersucht, simulativ modelliert und experimentell verifiziert. Um die Zuverlässigkeit und Kontinuität auch in "gestörten" Umgebungen zu erhöhen, werden in einem Bayesischen Filter die GNSS-Rohdaten mit Inertialsensormessungen aus zwei Fahrzeugen fusioniert. Die Validierung des Sensorfusionsansatzes wurde im Rahmen dieser Dissertation in einem Verkehrs- sowie in einem GNSS-Simulator durchgeführt. Zur experimentellen Untersuchung wurden zwei Testfahrzeuge mit den verschiedenen Sensoren ausgestattet und Messungen in diversen Umgebungen gefahren. In dieser Arbeit wird gezeigt, dass auf Autobahnen, die Relativposition eines anderen Fahrzeugs mit einer Genauigkeit von unter einem Meter kontinuierlich geschätzt werden kann. Eine hohe Zuverlässigkeit in der longitudinalen und lateralen Richtung können erzielt werden und das System erweist 90% der Zeit eine Unsicherheit unter 2.5m. In ländlichen Umgebungen wächst die Unsicherheit in der relativen Position. Mit Hilfe der on-board Sensoren können Fehler bei der Fahrt durch Wälder und Dörfer korrekt gestützt werden. In städtischen Umgebungen werden die Limitierungen des Systems deutlich. Durch die erschwerte Schätzung der Fahrtrichtung des Ego-Fahrzeugs ist vor Allem die longitudinale Komponente der Relativen Position in städtischen Umgebungen stark verfälscht.Advanced driver assistance systems play an important role in increasing the safety on today's roads. The knowledge about the other vehicles' positions is a fundamental prerequisite for numerous safety critical applications, making it possible to foresee critical situations, warn the driver or autonomously intervene. Forward collision avoidance systems, lane change assistants or adaptive cruise control are examples of safety relevant applications that require an accurate, continuous and reliable relative position of surrounding vehicles. Currently, the positions of surrounding vehicles is estimated by measuring the distance with e.g. radar, laser scanners or camera systems. However, all these techniques have limitations in their perception range, as all of them can only detect objects in their line-of-sight. The limited perception range of today's vehicles can be extended in future by using cooperative approaches based on Vehicle-to-Vehicle (V2V) communication. In this thesis, the capabilities of cooperative relative positioning for vehicles will be assessed in terms of its accuracy, continuity and reliability. A novel approach where Global Navigation Satellite System (GNSS) raw data is exchanged between the vehicles is presented. Vehicles use GNSS pseudorange and Doppler measurements from surrounding vehicles to estimate the relative positioning vector in a cooperative way. In this thesis, this approach is shown to outperform the absolute position subtraction as it is able to effectively cancel out common errors to both GNSS receivers. This is modeled theoretically and demonstrated empirically using simulated signals from a GNSS constellation simulator. In order to cope with GNSS outages and to have a sufficiently good relative position estimate even in strong multipath environments, a sensor fusion approach is proposed. In addition to the GNSS raw data, inertial measurements from speedometers, accelerometers and turn rate sensors from each vehicle are exchanged over V2V communication links. A Bayesian approach is applied to consider the uncertainties inherently to each of the information sources. In a dynamic Bayesian network, the temporal relationship of the relative position estimate is predicted by using relative vehicle movement models. Also real world measurements in highway, rural and urban scenarios are performed in the scope of this work to demonstrate the performance of the cooperative relative positioning approach based on sensor fusion. The results show that the relative position of another vehicle towards the ego vehicle can be estimated with sub-meter accuracy in highway scenarios. Here, good reliability and 90% availability with an uncertainty of less than 2.5m is achieved. In rural environments, drives through forests and towns are correctly bridged with the support of on-board sensors. In an urban environment, the difficult estimation of the ego vehicle heading has a mayor impact in the relative position estimate, yielding large errors in its longitudinal component