Konstantinos Katsaros

Performance study of a Green Light Optimized Speed Advisory (GLOSA) application using an integrated cooperative ITS simulation platform

This paper proposes a Green Light Optimized Speed Advisory (GLOSA) application implementation in a typical reference area, and presents the results of its performance analysis using an integrated cooperative ITS simulation platform. Our interest was to monitor the impacts of GLOSA on fuel and traffic efficiency by introducing metrics for average fuel consumption and average stop time behind a traffic light, respectively. For gathering the results we implemented a traffic scenario defining a single route through an urban area including two traffic lights. The simulations are varied for different penetration rates of GLOSA-equipped vehicles and traffic density. Our results indicate that GLOSA systems could improve fuel consumption and reduce traffic congestion in junctions.

CLWPR — A novel cross-layer optimized position based routing protocol for VANETs

In this paper, we propose a novel position-based routing protocol designed to anticipate the characteristics of an urban VANET environment. The proposed algorithm utilizes the prediction of the nodes position and navigation information to improve the efficiency of routing protocol in a vehicular network. In addition, we use the information about link layer quality in terms of SNIR and MAC frame error rate to further improve the efficiency of the proposed routing protocol. This in particular helps to decrease end-to-end delay. Finally, carry-n-forward mechanism is employed as a repair strategy in sparse networks. It is shown that use of this technique increases packet delivery ratio, but increases end-to-end delay as well and is not recommended for QoS constraint services. Our results suggest that compared with GPSR, our proposal demonstrates better performance in the urban environment.

Application of vehicular communications for improving the efficiency of traffic in urban areas

This paper studies the impacts of vehicular communications on efficiency of traffic in urban areas. We consider a Green Light Optimized Speed Advisory application implementation in a typical reference area and present the results of its performance analysis using an integrated cooperative intelligent transportation systems simulation platform. In addition, we study route alternation using vehicle-to-infrastructure and vehicle-to-vehicle communications. Our interest was to monitor the impacts of these applications on fuel and traffic efficiency by introducing metrics for average fuel consumption, average stop time behind a traffic light and average trip time, respectively. For gathering the results, we implemented two traffic scenarios defining routes through an urban area including traffic lights. The simulations are varied for different penetration rates of application-equipped vehicles, drivers compliance to the advised speed and traffic density. Our results indicate that Green Light Optimized Speed Advisory systems could improve fuel consumption, reduce traffic congestion in junctions and the total trip time. Copyright

Effective implementation of location services for VANETs in hybrid network infrastructures

In this paper we propose and evaluate a heterogeneous architecture for location service in vehicular environments. The proposed Location Service utilizes the infrastructure of cellular networks to offload the Dedicated Short Range Communication (DSRC) systems from the signalling overhead required for the location service. We evaluate the performance of such a hybrid solution in terms of overhead and end-to-end delay. The results suggest that a heterogeneous network with an IEEE 802.11p access network for data delivery and a LTE network for Location Service can provide better system performance in high density and high load scenarios.

An evaluation of routing in vehicular networks using analytic hierarchy process

This paper presents a comprehensive study of the performance of routing protocols in distributed vehicular networks. We propose a novel and efficient routing protocol, namely cross-layer, weighted, position-based routing, which considers link quality, mobility and utilisation of nodes in a cross layer manner to make effective position-based forwarding decisions. An analytic hierarchy process approach is utilised to combine multiple decision criteria into a single weighting function and to perform a comparative evaluation of the effects of aforementioned criteria on forwarding decisions. Comprehensive simulations are performed in realistic representative urban scenarios with synthetic and real traffic. Insights on the effect of different communication and mobility parameters are obtained. The results demonstrate that the proposed protocol outperforms existing routing protocols for vehicular ad hoc networks, including European Telecommunications Standards Institute ETSIs proposed greedy routing protocol, greedy traffic aware routing protocol and advanced greedy forwarding in terms of combined packet delivery ratio, end-to-end delay and overhead. Copyright

End-to-End Delay Bound Analysis for Location-Based Routing in Hybrid Vehicular Networks

There is an ongoing debate in the research and industry communities as to whether IEEE 802.11p or Third-Generation Partnership Project (3GPP) Long-Term Evolution (LTE) should be used for vehicular communications. In this paper, we argue that a hybrid vehicular network combining both technologies can increase the performance of the system. We first propose a mechanism to improve location-based routing in a hybrid vehicular network architecture by data and signaling traffic separation on independent wireless networks. We then develop analytical models to calculate the stochastic upper bound of the end-to-end delay (E2ED) for location-based routing in three different networking architecture alternatives based on a) short-range ad hoc only, b) cellular only, and c) the proposed hybrid ad hoc/cellular network. The analytical approach in this paper is based on the stochastic network calculus (SNC) theory, which provides a solid and uniform framework for analysis of the upper bound of the E2ED in communication networks. It is demonstrated that the proposed hybrid network provides a lower E2ED compared with the other two alternatives. Comparisons of realistic simulation results, carried out in NS-3, and analytical results show that the proposed delay bounds provide relatively tight approximations for the E2ED in the three alternative architectures for vehicular networks investigated in this paper.

Performance evaluation of an Adaptive Route Change application using an integrated cooperative ITS simulation platform

In this paper we present simulation results for our implementation of Adaptive Route Change (ARC) application for cooperative Intelligent Transportation Systems (ITS). The general purpose of the application is to generate recommendations for alternative driving routes in order to avoid traffic congestion. The Adaptive Route Change (ARC) application is implemented in an integrated cooperative ITS simulation platform. For the evaluation we chose a reference scenario defining two distinct traffic flows through an urban area that provides four crossings with traffic light controls. We were interested to evaluate the impacts of ARC on fuel and traffic efficiency. For that we introduced five performance metrics (average trip duration, average fuel consumption, average stop duration, maximum queue size and average queue size behind traffic lights) and evaluated ARC in a series of simulations with varied application penetration rates and traffic volume. The results indicate that ARC systems could reduce traffic congestion in intersections and improve fuel consumption. We observe up to one quarter reduction in average trip time and almost one third reduction in average stop time. Fuel consumption is also reduced by up to 17.3%, while average queue size and maximum queue size reduce more than 50%.

A Survey of the State-of-the-Art Localization Techniques and Their Potentials for Autonomous Vehicle Applications

For an autonomous vehicle to operate safely and effectively, an accurate and robust localization system is essential. While there are a variety of vehicle localization techniques in literature, there is a lack of effort in comparing these techniques and identifying their potentials and limitations for autonomous vehicle applications. Hence, this paper evaluates the state-of-the-art vehicle localization techniques and investigates their applicability on autonomous vehicles. The analysis starts with discussing the techniques which merely use the information obtained from on-board vehicle sensors. It is shown that although some techniques can achieve the accuracy required for autonomous driving but suffer from the high cost of the sensors and also sensor performance limitations in different driving scenarios (e.g., cornering and intersections) and different environmental conditions (e.g., darkness and snow). This paper continues the analysis with considering the techniques which benefit from off-board information obtained from V2X communication channels, in addition to vehicle sensory information. The analysis shows that augmenting off-board information to sensory information has potential to design low-cost localization systems with high accuracy and robustness, however, their performance depends on penetration rate of nearby connected vehicles or infrastructure and the quality of network service.

A Conceptual 5G Vehicular Networking Architecture

This chapter presents a thorough investigation on current vehicular networking architectures (access technologies and overlay networks) and their (r)evolution towards the 5G era. The main driving force behind vehicular networking is to increase safety, with several other applications exploiting this ecosystem for traffic efficiency and infotainment provision. The most prominent existing candidates for vehicular networking are based on dedicated short range communications (DSRC) and cellular (4G) communications. In addition, the maturity of cloud computing has accommodated the invasion of vehicular space with cloud-based services. Nevertheless, current architectures can not meet the latency requirements of Intelligent Transport Systems (ITS) applications in highly congested and mobile environments. The future trend of autonomous driving pushes current networking architectures further to their limits with hard real-time requirements. Vehicular networks in 5G have to address five major challenges that affect current architectures: congestion, mobility management, backhaul networking, air interface and security. As networking transforms from simple connectivity provision, to service and content provision, fog computing approaches with caching and pre-fetching improve significantly the performance of the networks. The cloudification of network resources through software defined networking (SDN)/network function virtualization (NFV) principles, is another promising enabler for efficient vehicular networking in 5G. Finally, new wireless access mechanisms combined with current DSRC and 4G will enable to bring the vehicles in the cloud.

Analytical model of RTT-aware SCTP

Connected vehicles are promoted with the use of different communication technologies for diverse applications. A host with multiple network devices is referred to as a multi-homed node. Stream Control Transmission Protocol (SCTP) is an IETF standard which supports multi-homing. However, original SCTP multi-homing functionality is only used when the primary address becomes unavailable. This paper presents an analytical model for a modified SCTP with multi-homed hosts, which selects the primary network address using a utility function based on minimum round trip time.