Robert Shorten

A Nonconservative LMI Condition for Stability of Switched Systems With Guaranteed Dwell Time

Ensuring stability of switched linear systems with a guaranteed dwell time is an important problem in control systems. Several methods have been proposed in the literature to address this problem, but unfortunately they provide sufficient conditions only. This technical note proposes the use of homogeneous polynomial Lyapunov functions in the non-restrictive case where all the subsystems are Hurwitz, showing that a sufficient condition can be provided in terms of an LMI feasibility test by exploiting a key representation of polynomials. Several properties are proved for this condition, in particular that it is also necessary for a sufficiently large degree of these functions. As a result, the proposed condition provides a sequence of upper bounds of the minimum dwell time that approximate it arbitrarily well. Some examples illustrate the proposed approach.

A Large-Scale SUMO-Based Emulation Platform

A hardware-in-the-loop simulation platform for emulating large-scale intelligent transportation systems is presented. The platform embeds a real vehicle into SUMO, a microscopic road traffic simulation package. Emulations, consisting of the real vehicle, and potentially thousands of simulated vehicles, are run in real time. The platform provides an opportunity for real drivers to gain a feel of being in a large-scale connected vehicle scenario. Various applications of the platform are presented.

An edge classification based approach to the post-processing of transform encoded images

Quantisation noise prevalent in transform encoded images becomes increasingly objectionable as the required bit rate is reduced. The perceptual effect of this coding noise is highly dependent on the focal behaviour of the signal upon which it is superimposed. In this paper, a computationally-efficient edge classifier, employing a histogram treatment of image sub-blocks, is proposed. The classifier forms the basis of an adaptive, non-linear postprocessing algorithm incorporating adaptive /spl alpha/-trimmed mean filtering (where the /spl alpha/-value and window size are determined by the output of the edge classifier) and a transform domain dithering technique. Subjective test results confirm the efficacy of the approach.<<ETX>>

On the Design of Campus Parking Systems With QoS Guarantees

Parking spaces are resources that can be pooled together and shared, particularly when there exist complementary daytime and nighttime users. We provide solutions to two design questions. First, given a quality of service requirement, how many spaces should be set aside as contingency during the day for nighttime users? Next, how can we replace the first-come-first-served access method by one that aims for optimal efficiency while keeping user preferences private?

A big-data model for multi-modal public transportation with application to macroscopic control and optimisation

This paper describes a Markov-chain-based approach to modelling multi-modal transportation networks. An advantage of the model is the ability to accommodate complex dynamics and handle huge amounts of data. The transition matrix of the Markov chain is built and the model is validated using the data extracted from a traffic simulator. A realistic test-case using multi-modal data from the city of London is given to further support the ability of the proposed methodology to handle big quantities of data. Then, we use the Markov chain as a control tool to improve the overall efficiency of a transportation network, and some practical examples are described to illustrate the potentials of the approach.

Smart procurement of naturally generated energy (SPONGE) for PHEVs

ABSTRACT In this paper, we propose a new engine management system for hybrid vehicles to enable energy providers and car manufacturers to provide new services. Energy forecasts are used to collaboratively orchestrate the behaviour of engine management systems of a fleet of plug-in hybrid electric vehicle (PHEVs) to absorb oncoming energy in a smart manner. Cooperative algorithms are suggested to manage the energy absorption in an optimal manner for a fleet of vehicles, and the mobility simulator SUMO (Simulation of Urban MObility) is used to demonstrate the efficacy of the proposed idea.

AIMD Dynamics and Distributed Resource Allocation

This is the first comprehensive book on the AIMD algorithm, the most widely used method for allocating a limited resource among competing agents without centralized control. The authors offer a new approach that is based on positive switched linear systems. It is used to develop most of the main results found in the book, and fundamental results on stochastic switched nonnegative and consensus systems are derived to obtain these results. The original and best known application of the algorithm is in the context of congestion control and resource allocation on the Internet, and readers will find details of several variants of the algorithm in order of increasing complexity, including deterministic, random, linear, and nonlinear versions. In each case, stability and convergence results are derived based on unifying principles. Basic and fundamental properties of the algorithm are described, examples are used to illustrate the richness of the resulting dynamical systems, and applications are provided to show how the algorithm can be used in the context of smart cities, intelligent transportation systems, and the smart grid. Audience: The book is suitable for advanced undergraduate and graduate students and researchers.

Smart Procurement of Naturally Generated Energy (SPONGE) for Plug-In Hybrid Electric Buses

We discuss a recently introduced ECO-driving concept known as smart procurement of naturally generated energy (SPONGE) in the context of plug-in hybrid electric buses. Examples are given to illustrate the benefits of this approach to ECO-driving. Finally, distributed algorithms to realize SPONGE are discussed, paying attention to the privacy implications of the underlying optimization problems.

On the design of a route parsing engine for connected vehicles with applications to congestion management systems

In this paper we present a new type of congestion management system to regulate congestion around a single link obstruction. This obstruction will be investigated in two cases: a) a regular obstruction and b) an irregular obstruction. The principle innovations of our system are to utilise a route parsing engine to both predict the likelihood of a vehicle being affected by the obstruction and make decisions ahead of time, and to use this information to make a fair congestion management system.

A Distributed and Privacy-Aware Speed Advisory System for Optimizing Conventional and Electric Vehicle Networks

One of the key ideas to make intelligent transportation systems work effectively is to deploy advanced communication and cooperative control technologies among vehicles and road infrastructures. In this spirit, we propose a consensus-based distributed speed advisory system that optimally determines a recommended common speed for a given area in order that the group emissions, or group battery consumptions, are minimized. Our algorithms achieve this in a privacy-aware manner; that is, individual vehicles do not reveal in-vehicle information to other vehicles or to infrastructure. A mobility simulator is used to illustrate the efficacy of the algorithm, and hardware-in-the-loop tests involving a real vehicle are given to illustrate user acceptability and ease of deployment.