Vehicular networks allow vehicles to share information and are expected to be an integral part of future intelligent transportation systems (ITS). To guide and validate the design process, analytical expressions of key performance metrics such as packet reception probabilities and throughput are necessary, in particular for accident-prone scenarios such as intersections. In this paper, we present a procedure to analytically determine the packet reception probability and throughput of a selected link, taking into account the relative increase in the number of vehicles (i.e., possible interferers) close to an intersection. We consider both slotted Aloha and CSMA/CA MAC protocols, and show how the procedure can be used to model different propagation environments of practical relevance. The procedure is validated for a selected set of case studies at low traffic densities.

The current road transport system has problems with both safety and efficiency. Future intelligent transportation systems (ITS) are envisioned to alleviate these problems. In particular, cooperative ITS, where vehicles are connected to each other and the cloud, will allow vehicles to collaborate and share both sensor and control information. This will significantly expand the possibilities of optimizing traffic flow and increasing safety. However, as both communication and sensing are unreliable, a key challenge in cooperative ITS is how to accommodate for communication and sensing impairments. This requires an understanding of what the limitations of communication and sensing systems are, and how their uncertainties affect the control and coordination task. The contribution of this thesis lies on the intersection of the fields of communication, sensing, and control, and can be summarized as follows.

First of all, through the use of stochastic geometry, we analyze the impact of interference in vehicular networks, and propose a general procedure to analytically determine key performance metrics such as packet reception probabilities and throughput. Along with this procedure, we provide a model repository that can be used to adapt to both rural and urban propagation characteristics, and different medium access control protocols. The procedure can be used to gain fundamental insights about the performance of vehicular communication systems in a variety of scenarios of practical relevance.

Secondly, when it comes to sensing uncertainties, we use Fisher information theory to provide bounds on the achievable performance of cooperative positioning solutions. We thereby characterize how the composition of the vehicle fleet, and the penetration rate of vehicles with extensive sensing capabilities affects positioning and mapping performance. While the analysis is generally applicable, we present simulation results from a multi-lane freeway scenario, which indicate that introducing a small fraction of cooperating vehicles with high-end sensors significantly improves the positioning quality of the entire fleet, but may not be enough to meet the stringent demands posed by safety-critical applications.

Finally, we study how communication and sensing uncertainties impact cooperative intersection coordination. We show that the requirements on control, communication and sensing are stringent if they are treated separately and that they could be relaxed if the individual systems are made aware of each other. This awareness is explored in two ways: we provide a communication system analysis for a centralized intersection coordination scheme using stochastic geometry, which can be used to provide guidelines on how to design the communication system to guarantee a control-dependent communication quality. We also propose a collision aware resource allocation strategy, which proactively reduces channel congestion by only assigning communication resources to vehicles that are in critical configurations, i.e., when there is a risk for future collisions.

This thesis, through the use of several mathematical tools, thus sheds new insights into the communication, sensing and control performance of cooperative ITS.

Cooperative localization is a promising solution to the vehicular high-accuracy localization problem. Despite its high potential, exhaustive measurement and information exchange between all adjacent vehicles are expensive and impractical for applications with limited resources. Greedy policies or hand-engineering heuristics may not be able to meet the requirement of complicated use cases. In this paper, we formulate a scheduling problem to improve the localization accuracy (measured through the Cramér-Rao lower bound) of every vehicle up to a given threshold using the minimum number of measurements. The problem is cast as a partially observable Markov decision process and solved using decentralized scheduling algorithms with deep reinforcement learning, which allow vehicles to optimize the scheduling (i.e., the instants to execute measurement and information exchange with each adjacent vehicle) in a distributed manner without a central controlling unit. Simulation results show that the proposed algorithms have a significant advantage over random and greedy policies in terms of both required numbers of measurements to localize all nodes and achievable localization precision with limited numbers of measurements.

A promising solution to meet the demands on accurate positioning and real-time situational awareness in future intelligent transportation systems (ITSs) is cooperative positioning, where vehicles share sensor information over the wireless channel. However, the sensing and communication technologies required for this will be gradually introduced into the market, and it is, therefore, important to understand what performance we can expect from cooperative positioning systems as we transition to a more modern vehicle fleet. In this paper, we study what effects a gradual market penetration has on cooperative positioning applications, through a Fisher information analysis. The simulation results indicate that solely introducing a small fraction of automated vehicles with high-end sensors significantly improves the positioning quality but is not enough to meet the stringent demands posed by safety critical ITS applications. Furthermore, we find that retrofitting vehicles with low-cost satellite navigation receivers and communication have marginal impact when the positioning requirements are stringent and that the longitudinal road position can be estimated more accurately than lateral. © 2013 IEEE.

Intersection management of automated vehicles relies on wireless communication, whereby communication resources should be allocated to vehicles while maintaining safety. We present a collision-aware resource allocation (CARA) strategy for coordination of automated and connected vehicles by a centralized intersection manager. The proposed strategy is based on a self-triggered approach and proactively reduces the risk of channel congestion by only assigning communication resources to vehicles that are in critical configurations, i.e., when there is a risk for a future collision. Compared with collision-agnostic communication strategies, typically considered for automated intersection management, the CARA strategy aims to bridge the gap between control, sensing, and communication. It is shown to significantly reduce the required amount of communication (albeit with a slight increase in the control cost), without compromising safety. Furthermore, control cost can be reduced by allowing more frequent communication, which we demonstrate through a trade-off analysis between control performance and communication load. Hence, CARA can operate in communication-limited scenarios, but also be modified for scenarios where the control cost is of primary interest.

Many traffic-related applications require the nodes in a vehicular ad-hoc network (VANET) to periodically broadcast their state information. As measurements campaigns or simulations to evaluate the reliability of packet transmission are slow and scenario-specific, we present an analytic performance assessment tool that accounts for the spatial statistics of the nodes on a road, in a scenario of crossing roads and fast fading. Based on stochastic geometry, our tool is able to capture a static two-dimensional road geometry and the effect of interference due to node clustering in the vicinity of an intersection. Numerical results reveal how packet transmission is affected as the receiver gets closer to the intersection.

Speed information from GPS is increasingly used and provides an alternative to conventional methods such as wheel speed sensors. We investigate the possibility to use GPS derived speed as a reference when verifying laser and radar-based speed measuring devices used in traffic enforcement. We have set up a realistic test scenario where a GPS equipped vehicle was driven at three different speeds (40, 90 and 130 km/h) through a pre-defined measurement zone. An independent and traceable reference speed was calculated by accurately measuring the length of the measurement zone (approximately 15 metres), and the time it took to pass through it. The reference speed was compared to the average GPS speed for each passage. This comparisons show that the standard uncertainty of such GPS speed measurements is less than 0.05 km/h. Hence, GPS derived speed meets the accuracy requirements for verification of laser and radar based speed measuring devices.

Coordination of autonomous cooperative vehicles is an important challenge for future intelligent transportation systems. In particular, coordination to cross intersections captures the inherent and connected challenges among control and communication. While intersection coordination and vehicular wireless communication have both received extensive treatment in their respective communities, few works consider their interaction. We provide a communication system analysis for the specific problem of centralized intersection crossing coordination, leading to design guidelines for both uplink (whereby vehicles send intentions to the central controller) and downlink (where the controller prescribes vehicles of safe control actions).