Vehicle-to-Everything (V2X) communication is essential for facilitating connected and automated driving, where vehicles and other road traffic participants share data instantaneously and cooperate to solve tricky traffic situations in milliseconds. This paper proposes two stochastic models for the V2X standard IEEE 802.11p to characterize amongst other things the Age of Information (AoI), a recently-proposed metric that measures the freshness of information. The first model is based on renewal process analysis of a tagged station with mean field approximation, while the second one adopts Markov chain approach with network level view. Analytical results show that IEEE 802.11p, given its adaptability to event-triggered and aperiodic messaging, supports advanced cooperative driving scenarios.

Vehicular networking enables a wide range of emerging Cooperative Intelligent Transportation System (C-ITS) applications, from safety to traffic efficiency and infotainment. Many of these applications depend on the reliability and timeliness of status information periodically exchanged among vehicles on the same wireless communication channel. A major effort has been spent, especially by standardization bodies, to define congestion control algorithms for the vehicular networking environment. The picture is, however, more complex than simply controlling the load level on the channel, given the non-trivial interplay of delivery reliability, system throughput, and timeliness of updates. In this paper, we provide a comprehensive performance evaluation of the main state-of- the-art broadcast rate control algorithms from the point of view of channel load, utilization efficiency, and information freshness. We evaluate these algorithms in a realistic simulation environment and describe a centralized approach to define a bound on the performance. We show that controlling the congestion based on either channel load or information freshness only leads to sub-optimal performance.

Decentralized Congestion Control (DCC) is one the central components of inter-vehicular communications protocol stack enabling Cooperative Intelligent Transportation System (C-ITS). In this letter we first present an analytical framework that allows to tune parameters of the DCC algorithm specified by ETSI. Then we suggest two approaches to optimize the DCC configuration using our framework. Finally, we evaluate the performance of the proposed approaches using detailed simulation experiments. We demonstrate that proposed approaches are able to control channel busy ratio stably, while proposed analytical model precisely estimates application level metrics. © 2019 IEEE

Drive-thru-Internet is a scenario in cooperative intelligent transportation systems (C-ITSs), where a road-side unit (RSU) provides multimedia services to vehicles that pass by. Performance of the drive-thru-Internet depends on various factors, including data traffic intensity, vehicle traffic density, and radio-link quality within the coverage area of the RSU, and must be evaluated at the stage of system design in order to fulfill the quality-of-service requirements of the customers in C-ITS. In this paper, we present an analytical framework that models downlink traffic in a drive-thru-Internet scenario by means of a multidimensional Markov process: the packet arrivals in the RSU buffer constitute Poisson processes and the transmission times are exponentially distributed. Taking into account the state space explosion problem associated with multidimensional Markov processes, we use iterative perturbation techniques to calculate the stationary distribution of the Markov chain. Our numerical results reveal that the proposed approach yields accurate estimates of various performance metrics, such as the mean queue content and the mean packet delay for a wide range of workloads. © 2019 IEEE.

To enable testing and performance evaluation of new connected and autonomous driving functions, it is important to characterize packet losses caused by degradation in vehicular (V2X) communication channels. In this paper we suggest an approach to constructing packet loss models based on the socalled Pseudo-Markov chains (PMC). The PMC based model needs only short training sequences, has low computational complexity, and yet provides more precise approximations than known techniques. We show how to learn PMC models from either empirical records of packet receptions, or from analytical models of fluctuations in the received signal strength. In particular, we validate our approach by applying it on (i) V2X packet reception data collected from an active safety test run, which used the LTE network of the AstaZero automotive testing site in Sweden, and (ii) variants of the Rician fading channel models corresponding to two models of correlations of packet losses. We also show that initializing the Baum-Welch algorithm with a second order PMC model leads to a high accuracy model. © 2019 IEEE.

In Cooperative Intelligent Transportation Systems (C-ITSs), vehicles need to wirelessly connect with Roadside units (RSUs) over limited durations when such point-to-point connections are possible. One example of such communications is the downloading of maps to the C-ITS vehicles. Another example occurs in the testing of C-ITS vehicles, where the tested vehicles upload trajectory records to the roadside units. Because of real-time requirements, and limited bandwidths, data are sent as User Datagram Protocol (UDP) packets. We propose an inter-packet error control coding scheme that improves the recovery of data when some of these packets are lost; we argue that the coding scheme has to be one of convolutional coding. We measure performance through the session averaged probability of successfully delivering groups of packets. We analyze two classes of convolution codes and propose a low-complexity decoding procedure suitable for network applications. We conclude that Reed–Solomon convolutional codes perform better than Wyner–Ash codes at the cost of higher complexity. We show this by simulation on the memoryless binary erasure channel (BEC) and channels with memory, and through simulations of the IEEE 802.11p DSRC/ITS-G5 network at the C-ITS test track AstaZero.

An approach to constructing discrete models of packet losses suitable for a wide variety of communication network applications is studied. It is based on estimating parameters of probabilistic automata described via so-called pseudo-Markov chains. The new technique is applied both to approximating a discrete time analog process at the output of known channel models and to the experimental data stream. Comparison of models is performed by computing probabilities of more than m losses out of n transmitted packets (P (≥ m, n)). It is shown that for the Rician fading channel with exponential correlation and correlation determined by a Bessel filter, the obtained rank-two and rank-three discrete modes, respectively, provide high accuracy coincidence of P (≥ m, n) performances. The rank-three discrete model computed on the experimental data stream obtained from the LTE network provides significantly better approximation of P (≥ m, n) performance than that obtained by the Baum-Welch algorithm.

Intelligent Transport Systems (ITS) are aiming to provide innovative services related to different modes of transport and traffic management, and enable various users to be better informed and make safer, more coordinated and smarter use of transport networks. Cooperative-ITS (C-ITS) support connectivity between vehicles, vehicles and roadside infrastructure, traffic signals as well as with other road users. In order to enable vehicular communications European Telecommunication Standards Institute (ETSI) delivered ITS-G5 -- a of set of C-ITS standards. Considering the goals of C-ITS, inter-vehicle communications should be reliable and efficient.

The subject of this thesis is evaluation of the performance, efficiency, and dependability of ITS-G5 communications for cooperative driving applications support. This thesis includes eight scientific papers and extends the research area in three directions: evaluation of the performance of ITS-G5 beaconing protocols; studying the performance of ITS-G5 congestion control mechanisms; and studying the radio jamming Denial-of-Service (DoS) attacks and their detection methods.

First, an overview of currently available and ongoing standardization targeting communications in C-ACC/platooning cooperative driving applications is provided. Then, as part of the first research direction, we demonstrate via a number of studies, that the adaptive beaconing approach where message generation is coupled to the speed variation of the originating ITS-s may lead to a message synchronization effect in the time domain when vehicles follow mobility scenarios that involve cooperative speed variation. We explain in detail the cause of this phenomenon and test it for a wide range of parameters. In relation to the second problem, we, first, study the influence of different available ITS-G5 legitimate setups on the C-ACC/platooning fuel efficiency and demonstrate that proper communication setup may enhance fuel savings. Then we thoroughly study the standardization of the congestion control mechanism for ITS-G5, which will affect the operation of all cooperative driving C-ITS applications as a mandatory component. We study the influence of congestion control on application performance and give recommendations for improvement to make the congestion control to target at optimizing the applications performance metrics. In the scope of the last research direction, we propose two real-time jamming DoS detection methods. The main advantage of our detection techniques is their short learning phase that not exceed a few seconds and low detection delay of a few hundreds of milliseconds. Under some assumptions, the proposed algorithms demonstrates the ability to detect certain types of attacks with high detection probability.

A data mining-based method for real-time detection of radio jamming Denial-of-Service (DoS) attacks in IEEE 802.11p vehicle-to-vehicle (V2V) communications is proposed. The method aims at understanding the reasons for losses of periodic cooperative awareness messages (CAM) exchanged by vehicles in a platoon. Detection relies on a knowledge of IEEE 802.11p protocols rules as well as on historical observation of events in the V2V channel. In comparison to the state-of-the-art method, the proposed method allows operating under the realistic assumption of random jitter accompanying every CAM transmission. The method is evaluated for two jamming models: random and ON-OFF. 

Vehicle-to-vehicle (V2V) communication is the key technology enabling platooning. This paper proposes an analytical framework that combines the characteristics of V2V communication (packet loss probabilities and packet transmission delays) with the physical mobility characteristics of vehicles (speed, distance between vehicles and their brake capacities). First, we present the feasible region of communications delays which guarantees safe emergency braking in platooning scenarios. Second, we derive a bound on the probability of safe braking. The presented framework is applied to understand the performance of the state-of-the-art V2V communication protocol for platooning.