Daniel H. Stolfi

University of Luxembourg · Interdisciplinary Centre for Security, Reliability and Trust

This article proposes a mobility architecture, called Green Swarm, to reduce greenhouse gas emissions from road traffic in smart cities. The traffic flow optimization of four European cities: Malaga, Stockholm, Berlin, and Paris, is addressed with new case studies importing each city's actual roads and traffic lights from OpenStreetMap into the SUM...

Finding an available parking space can be difficult in parts of most cities, especially in city centers. In this article, we address the study of parking occupancy data in Birmingham, Glasgow, Norfolk, and Nottingham in the United Kingdom. We test several prediction strategies, such as polynomial fitting, Fourier series, K-means clustering, and tim...

In this article, we propose a new mobility model, called Attractor Based Inter-Swarm collaborationS (ABISS), for improving the surveillance of restricted areas performed by unmanned autonomous vehicles. This approach uses different types of vehicles which explore an area of interest following unpredictable trajectories based on chaotic solutions of...

In this paper we present a surveillance system for early detection of escapers from a restricted area based on a new swarming mobility model called CROMM-MS (Chaotic Rössler Mobility Model for Multi-Swarms). CROMM-MS is designed for controlling the trajectories of heterogeneous multi-swarms of aerial, ground and marine unmanned vehicles with import...

This article introduces CONcentric Swarm mObiLity modEl (CONSOLE), a novel mobility model for unmanned aerial vehicles (UAVs) to efficiently achieve surveillance and intruder detection missions. It permits to protect a restricted area from intruders using a concentric circles model where simulated UAVs evolve in these so-called security rings. Havi...

Realistic robotic simulations are computationally demanding, especially when considering large swarms of autonomous robots. This makes the optimisation of such systems intractable, thus limiting the instances’ and swarms’ size. In this article we study the viability of using surrogate models based on Gaussian processes, Artificial Neural Networks,...

Optimising a swarm of many robots can be computationally demanding, especially when accurate simulations are required to evaluate the proposed robot configurations. Consequentially, the size of the instances and swarms must be limited, reducing the number of problems that can be addressed. In this article, we study the viability of using surrogate...

In this article, we present a distributed robot 3D formation system optimally parameterised by a hybrid evolutionary algorithm (EA) in order to improve its efficiency and robustness. To achieve that, we first describe the novel distributed formation algorithm3 (DFA3), the proposed EA, and the two crossover operators to be tested. The EA hyperparame...

In this article, we propose SuSy-EnGaD, a surveillance system enhanced by games of drones. We propose three different approaches to optimise a swarm of UAVs for improving intruder detection, two of them featuring a multi-objective optimisation approach, while the third approach relates to the evolutionary game theory where three different strategie...

In this article we address the optimisation of pheromone communication used for the mobility management of a swarm of Unmanned Aerial Vehicles (UAVs) for surveillance applications. A genetic algorithm is proposed to optimise the exchange of pheromone maps used in the CACOC (Chaotic Ant Colony Optimisation for Coverage) mobility model which improves...

In this paper we present the competitive optimisation of a swarm of Unmanned Aerial Vehicles (UAV) protecting a restricted area from a number of intruders following a Predator-Prey approach. We propose a Competitive Coevolutionary Genetic Algorithm (CompCGA) which optimises the parameters of the UAVs (i.e. predators) to maximise the detection of in...

Traffic congestion is one of the main concerns of citizens living in big cities. In this article we propose a novel system, called Yellow Swarm, with the aim of improving road traffic at a low cost and easy implementation by using a set of LED panels placed throughout the city in order to spread road traffic over its streets. The system is optimall...

Unmanned Aerial Vehicles (UAVs) have quickly become one of the promising Internet-of-Things (IoT) devices for smart cities. Thanks to their mobility, agility, and onboard sensors’ customizability, UAVs have already demonstrated immense potential for numerous commercial applications. The UAVs expansion will come at the price of a dense, high-speed a...

Unmanned Aerial Vehicles (UAVs) have quickly become one of the promising Internet-of-Things (IoT) devices for smart cities thanks to their mobility, agility, and onboard sensors' customizability. UAVs are used in many applications expanding beyond the military to more commercial ones, ranging from monitoring, surveillance, mapping to parcel deliver...

In this paper we present the parameterisation and optimisation of the CACOC (Chaotic Ant Colony Optimisation for Coverage) mobility model applied to Unmanned Aerial Vehicles (UAV) in order to perform surveillance tasks. The use of unpredictable routes based on the chaotic solutions of a dynamic system as well as pheromone trails improves the area c...

This paper presents the parameterisation and optimisation of the CACOC (Chaotic Ant Colony Optimisation for Coverage) mobility model used by an Unmanned Aerial Vehicle (UAV) swarm to perform surveillance tasks. CACOC uses chaotic solutions of a dynamical system and pheromones for optimising area coverage. Consequently, several parameters of CACOC a...

This study presents a new technique based on Deep Learning with Recurrent Neural Networks to address the prediction of car park occupancy rate. This is an interesting problem in smart mobility and we here approach it in an innovative way, consisting in automatically design a deep network that encapsulates the behavior of the car occupancy and then...

In this article we present a novel approach for calculating realistic traffic flows for traffic simulators, called Flow Generator Algorithm (FGA). We start with an original map from OpenStreetMap and traffic data collected at different measurement points, published by the city’s authorities, to produce a model consisting of the simulation map and a...

Nowadays, city streets are populated not only by private vehicles but also by public transport, distribution of goods, and deliveries. Since each vehicle class has a maximum cargo capacity, we study in this article how authorities could improve the road traffic by changing the different vehicle proportions: sedans, minivans, full-size vans, trucks,...

This article presents a new set of ideas on how to build bio-inspired algorithms based on the new field of epigenetics. By analyzing this domain and extracting working computational ideas we want to offer a set of tools for the future creation of representations, operators, and search techniques that can competitively solve complex problems. To ill...

GPS navigators are now present in most vehicles and smartphones. The usual goal of these navigators is to take the user in less time or distance to a destination. However, the global use of navigators in a given city could lead to traffic jams as they have a highly biased preference for some streets. From a general point of view, spreading the traf...

In this article we address the study of parking occupancy data published by the Birmingham city council with the aim of testing several prediction strategies (polynomial fitting, Fourier series, k-means clustering, and time series) and analyzing their results. We have used cross validation to train the predictors and then tested them on unseen occu...

In this article we work towards the desired future smart city in which IT and knowledge will hopefully provide a highly livable environment for citizens. To this end, we test a new concept based on intelligent LED panels (the Yellow Swarm) to guide drivers when moving through urban streets so as to finally get rid of traffic jams and protect the en...

Road transportation is becoming a major concern in modern cities. The growth of the number of vehicles is provoking an important increment of pollution and greenhouse gas emissions generated by road traffic. In this paper, we present CTPATH, an innovative smart mobility software system that offers efficient paths to drivers in terms of travel time...

In this article we present a strategy based on an evolutionary algorithm to calculate the real vehicle flows in cities according to data from sensors placed in the streets. We have worked with a map imported from OpenStreetMap into the SUMO traffic simulator so that the resulting scenarios can be used to perform different optimizations with the con...

In this article we propose the Yellow Swarm architecture for reducing travel times, greenhouse gas emissions and fuel consumption of road traffic by using several LED panels to suggest changes in the direction of vehicles (detours) for different time slots. These time intervals are calculated using an evolutionary algorithm, specifically designed f...

En este trabajo proponemos la arquitectura Yellow Swarm dedicada a la reducción de los tiempos de viaje del tráfico rodado mediante la utilización de una serie de paneles LED con el fin de sugerir diferentes cambios de dirección durante determinadas ventanas de tiempo. Estos tiempos son calculados por un algoritmo evolutivo diseñado expresamente pa...

This article presents an innovative approach to solve one of the most relevant problems related to smart mobility: the reduction of vehicles' travel time. Our original approach, called Red Swarm, suggests a potentially customized route to each vehicle by using several spots located at traffic lights in order to avoid traffic jams by using V2I commu...

This article proposes an innovative solution for reducing polluting gas emissions from road traffic in modern cities. It is based on our new Red Swarm architecture which is composed of a series of intelligent spots with WiFi connections that can suggest a customized route to drivers. We have tested our proposal in four different case studies corres...

This article proposes an innovative solution for reducing polluting gas emissions from road traffic in modern cities. It is based on our new Red Swarm architecture which is composed of a series of intelligent spots with WiFi connections that can suggest a customized route to drivers. We have tested our proposal in four different case studies corres...

This work presents an original approach to regulate traffic by using an on-line system controlled by an EA. Our proposal uses computational spots with WiFi connectivity located at traffic lights (the Red Swarm), which are used to suggest alternative individual routes to vehicles. An evolutionary algorithm is also proposed in order to find a configu...