arXiv subjects

Robert Shorten

Publications and source records attributed to Robert Shorten.

At least 91 records · Page 5Linked to original sources

arXiv2018

On $\mathcal{L}_{\infty}$ string stability of nonlinear bidirectional asymmetric heterogeneous platoon systems

This paper is concerned with the study of bidirectionally coupled platoon systems. The case considered is when the vehicles are heterogeneous and the coupling can be nonlinear and asymmetric. For such systems, a sufficient condition for $\mathcal{L}_{\infty}$ string stability is presented. The effectiveness of our approach is illustrated via a numerical example, where it is shown how our result can be recast as an optimization problem, allowing to design the control protocol for each vehicle independently on the other vehicles and hence leading to a bottom-up approach for the design of string stable systems able to track a time-varying reference speed.

eess.SY↗

arXiv2018

Derandomized Distributed Multi-resource Allocation with Little Communication Overhead

We study a class of distributed optimization problems for multiple shared resource allocation in Internet-connected devices. We propose a derandomized version of an existing stochastic additive-increase and multiplicative-decrease (AIMD) algorithm. The proposed solution uses one bit feedback signal for each resource between the system and the Internet-connected devices and does not require inter-device communication. Additionally, the Internet-connected devices do not compromise their privacy and the solution does not dependent on the number of participating devices. In the system, each Internet-connected device has private cost functions which are strictly convex, twice continuously differentiable and increasing. We show empirically that the long-term average allocations of multiple shared resources converge to optimal allocations and the system achieves minimum social cost. Furthermore, we show that the proposed derandomized AIMD algorithm converges faster than the stochastic AIMD algorithm and both the approaches provide approximately same solutions.

eess.SY↗

arXiv2018

Distributed Ledger Technology, Cyber-Physical Systems, and Social Compliance

This paper describes how Distributed Ledger Technologies can be used to design a class of cyber-physical systems, as well as to enforce social contracts and to orchestrate the behaviour of agents trying to access a shared resource. The first part of the paper analyses the advantages and disadvantages of using Distributed Ledger Technologies architectures to implement certain control systems in an Internet of Things (IoT) setting, and then focuses on a specific type of DLT based on a Directed Acyclic Graph. In this setting we propose a set of delay differential equations to describe the dynamical behaviour of the Tangle, an IoT-inspired Directed Acyclic Graph designed for the cryptocurrency IOTA. The second part proposes an application of Distributed Ledger Technologies as a mechanism for dynamic deposit pricing, wherein the deposit of digital currency is used to orchestrate access to a network of shared resources. The pricing signal is used as a mechanism to enforce the desired level of compliance according to a predetermined set of rules. After presenting an illustrative example, we analyze the control system and provide sufficient conditions for the stability of the network.

eess.SY↗

arXiv2018

Bayesian Classifier for Route Prediction with Markov Chains

We present here a general framework and a specific algorithm for predicting the destination, route, or more generally a pattern, of an ongoing journey, building on the recent work of [Y. Lassoued, J. Monteil, Y. Gu, G. Russo, R. Shorten, and M. Mevissen, "Hidden Markov model for route and destination prediction," in IEEE International Conference on Intelligent Transportation Systems, 2017]. In the presented framework, known journey patterns are modelled as stochastic processes, emitting the road segments visited during the journey, and the ongoing journey is predicted by updating the posterior probability of each journey pattern given the road segments visited so far. In this contribution, we use Markov chains as models for the journey patterns, and consider the prediction as final, once one of the posterior probabilities crosses a predefined threshold. Despite the simplicity of both, examples run on a synthetic dataset demonstrate high accuracy of the made predictions.

cs.LG↗

arXiv2018

Communication-efficient Distributed Multi-resource Allocation

In several smart city applications, multiple resources must be allocated among competing agents that are coupled through such shared resources and are constrained --- either through limitations of communication infrastructure or privacy considerations. We propose a distributed algorithm to solve such distributed multi-resource allocation problems with no direct inter-agent communication. We do so by extending a recently introduced additive-increase multiplicative-decrease (AIMD) algorithm, which only uses very little communication between the system and agents. Namely, a control unit broadcasts a one-bit signal to agents whenever one of the allocated resources exceeds capacity. Agents then respond to this signal in a probabilistic manner. In the proposed algorithm, each agent makes decision of its resource demand locally and an agent is unaware of the resource allocation of other agents. In empirical results, we observe that the average allocations converge over time to optimal allocations.

eess.SY↗

arXiv2018

A context-aware e-bike system to reduce pollution inhalation while cycling

The effect of transport-related pollution on human health is fast becoming recognised as a major issue in cities worldwide. Cyclists, in particular, face great risks, as they typically are most exposed to tail-pipe emissions. Three avenues are being explored worldwide in the fight against urban pollution: (i) outright bans on polluting vehicles and embracing zero tailpipe emission vehicles; (ii) measuring air-quality as a means to better informing citizens of zones of higher pollution; and (iii) developing smart mobility devices that seek to minimize the effect of polluting devices on citizens as they transport goods and individuals in our cities. Following this latter direction, in this paper we present a new way to protect cyclists from the effect of urban pollution. Namely, by exploiting the actuation possibilities afforded by pedelecs or e-bikes (electric bikes), we design a cyber-physical system that mitigates the effect of urban pollution by indirectly controlling the breathing rate of cyclists in polluted areas. Results from a real device are presented to illustrate the efficacy of our system.

eess.SY↗

arXiv2018

A Non-Invasive Method for the Safe Interaction of Cities and Electric Vehicle Fleets

Electric and hybrid vehicles are growing in popularity. While these vehicles produce less pollution, they also produce less audible noise, especially at lower speeds. This makes it harder for pedestrians and cyclists to detect an approaching vehicle. Thus, an additional system is required to detect electric and hybrid vehicles and alert pedestrians and cyclists of their whereabouts, especially while these vehicles are driving at low speeds in cities. This paper introduces one such method based on high frequency audio emissions that are present in EVs, which arise, for example, from the process of magnetostriction. Our method is tested experimentally using 4 different tests vehicles, and a preliminary EV detection algorithm is also presented.

eess.SY↗

arXiv2018

On the Design of an Intelligent Speed Advisory System for Cyclists

Traffic-related pollution is becoming a major societal problem globally. Cyclists are particularly exposed to this form of pollution due to their proximity to vehicles' tailpipes. In a number of recent studies, it is been shown that exposure to this form of pollution eventually outweighs the cardio-vascular benefits associated with cycling. Hence during cycling there are conflicting effects that affect the cyclist. On the one hand, cycling effort gives rise to health benefits, whereas exposure to pollution clearly does not. Mathematically speaking, these conflicting effects give rise to convex utility functions that describe the health threats accrued to cyclists. More particularly, and roughly speaking, for a given level of background pollution, there is an optimal length of journey time that minimises the health risks to a cyclist. In this paper, we consider a group of cyclists that share a common route. This may be recreational cyclists, or cyclists that travel together from an origin to destination. Given this context, we ask the following question. What is the common speed at which the cyclists should travel, so that the overall health risks can be minimised? We formulate this as an optimisation problem with consensus constraints. More specifically, we design an intelligent speed advisory system that recommends a common speed to a group of cyclists taking into account different levels of fitness of the cycling group, or different levels of electric assist in the case that some or all cyclists use e-bikes (electric bikes). To do this, we extend a recently derived consensus result to the case of quasi-convex utility functions. Simulation studies in different scenarios demonstrate the efficacy of our proposed system.

eess.SY↗

arXiv2018

On the design of a decision engine for connected vehicles with an application to congestion management

Vehicles are becoming connected entities. As a result, a likely scenario is that such entities might be literally bombarded with information from a multitude of devices. In this context, a key challenging requirement for both connected and autonomous vehicles is that they will need to become cognitive bodies, able to parse information and use only the pieces of information that are relevant to the vehicle in the context of a given journey. In order to address this fundamental requirement, a decision engine is presented in this paper. The engine makes it possible for the vehicle to understand which pieces of information are really relevant, and subsequently to process only those pieces of information. In order to illustrate the key features of our system, we show that it is possible to build upon the engine to develop a distributed traffic management system, and then we validate such a system via both conventional (numerical and SUMO-based) simulations and a Hardware-in-the-Loop (HIL) platform. Both the conventional simulations and the HIL validation showed that the engine can be effectively used to design a distributed traffic management system.

eess.SY↗

arXiv2018

A Hidden Markov Model for Route and Destination Prediction

We present a simple model and algorithm for predicting driver destinations and routes, based on the input of the latest road links visited as part of an ongoing trip. The algorithm may be used to predict any clusters previously observed in a driver's trip history. It assumes that the driver's historical trips are grouped into clusters sharing similar patterns. Given a new trip, the algorithm attempts to predict the cluster in which the trip belongs. The proposed algorithm has low temporal complexity. In addition, it does not require the transition and emission matrices of the Markov chain to be computed. Rather it relies on the frequencies of co-occurrences of road links and trip clusters. We validate the proposed algorithm against an experimental dataset. We discuss the success and convergence of the algorithm and show that our algorithm has a high prediction success rate.

physics.soc-ph↗

arXiv2017

Distributed Multi-resource Allocation with Little Communication Overhead

We propose a distributed algorithm to solve a special distributed multi-resource allocation problem with no direct inter-agent communication. We do so by extending a recently introduced additive-increase multiplicative-decrease (AIMD) algorithm, which only uses very little communication between the system and agents. Namely, a control unit broadcasts a one-bit signal to agents whenever one of the allocated resources exceeds capacity. Agents then respond to this signal in a probabilistic manner. In the proposed algorithm, each agent is unaware of the resource allocation of other agents. We also propose a version of the AIMD algorithm for multiple binary resources (e.g., parking spaces). Binary resources are indivisible unit-demand resources, and each agent either allocated one unit of the resource or none. In empirical results, we observe that in both cases, the average allocations converge over time to optimal allocations.

cs.DC↗

arXiv2017

A New Take on Protecting Cyclists in Smart Cities

Pollution in urban centres is becoming a major societal problem. While pollution is a concern for all urban dwellers, cyclists are one of the most exposed groups due to their proximity to vehicle tailpipes. Consequently, new solutions are required to help protect citizens, especially cyclists, from the harmful effects of exhaust-gas emissions. In this context, hybrid vehicles (HVs) offer new actuation possibilities that can be exploited in this direction. More specifically, such vehicles when working together as a group, have the ability to dynamically lower the emissions in a given area, thus benefiting citizens, whilst still giving the vehicle owner the flexibility of using an Internal Combustion Engine (ICE). This paper aims to develop an algorithm, that can be deployed in such vehicles, whereby geofences (virtual geographic boundaries) are used to specify areas of low pollution around cyclists. The emissions level inside the geofence is controlled via a coin tossing algorithm to switch the HV motor into, and out of, electric mode, in a manner that is in some sense optimal. The optimality criterion is based on how polluting vehicles inside the geofence are, and the expected density of cyclists near each vehicle. The algorithm is triggered once a vehicle detects a cyclist. Implementations are presented, both in simulation, and in a real vehicle, and the system is tested using a Hardware-In-the-Loop (HIL) platform (video provided).

math.OC↗

arXiv2017

On the stability and convergence of a class of consensus systems with a nonlinear input

We consider a class of consensus systems driven by a nonlinear input. Such systems arise in a class of IoT applications. Our objective in this paper is to determine conditions under which a certain partially distributed system converges to a Lur'e-like scalar system, and to provide a rigorous proof of its stability. Conditions are derived for the non-uniform convergence and stability of such a system and an example is given of a speed advisory system where such a system arises in real engineering practice.

eess.SY↗

arXiv2017

Distributionally Robust Optimisation in Congestion Control

The effects of real-time provision of travel-time information on the behaviour of drivers are considered. The model of Marecek et al. [arXiv:1406.7639, Int. J. Control 88(10), 2015] is extended to consider uncertainty in the response of a driver to an interval provided per route. Specifically, it is suggested that one can optimise over all distributions of a random variable associated with the driver's response with the first two moments fixed, and for each route, over the sub-intervals within the minimum and maximum in a certain number of previous realisations of the travel time per the route.

math.OC↗

arXiv2017

Stability tests for a class of switched descriptor systems with non-homogenous indices

In this paper we derive stability conditions for a switched system where switching occurs between linear descriptor systems of different indices. In particular, our results can be used to analyse the stability of the important case when switching between a standard system and an index one descriptor system, and systems where switching occurs between an index one and and an index two descriptor system. Examples are given to illustrate the use of our results.

math.OC↗

arXiv2017

Hybrid Urban Navigation for Smart Cities

This paper proposes a design for a hybrid, city-wide urban navigation system for moving agents demanding dedicated assistance. The hybrid system combines GPS and vehicle-to-vehicle communication from an ad-hoc network of parked cars, and RFID from fixed infrastructure -such as smart traffic lights- to enable a safely navigable city. Applications for such a system include high-speed drone navigation and directing visually impaired pedestrians.

eess.SY↗

arXiv2017

Pedestrian-Aware Engine Management Strategies for Plug-in Hybrid Electric Vehicles

Electric Vehicles (EVs) and Plug-in Hybrid Electric Vehicles (PHEVs) are increasingly being seen as a means of mitigating the pressing concerns of traffic-related pollution. While hybrid vehicles are usually designed with the objective of minimising fuel consumption, in this paper we propose engine management strategies that also take into account environmental effects of the vehicles to pedestrians outside of the vehicles. Specifically, we present optimisation based engine energy management strategies for PHEVs, that attempt to minimise the environmental impact of pedestrians along the route of the vehicle, while taking account of route dependent uncertainties. We implement the proposed approach in a real PHEV, and evaluate the performance in a hardware-in-the-loop platform. A variety of simulation results are given to illustrate the efficacy of our proposed approach.

eess.SY↗

arXiv2017

On the SPRification of linear descriptor systems via output feedback

We consider input-output systems in descriptor form and ask when such systems can be rendered SPR (strictly positive real) via output feedback. Time and frequency domain conditions are given to determine when and how this is possible. In addition, a synthesis procedure for controller design is also derived. Together, the results provide a complete answer to when a linear descriptor system can be made SPR via output feedback, and give a recipe for design of the feedback controller when it exists. Simple examples are given to illustrate our results and to demonstrate their efficacy.

math.DS↗