Understanding Evolutionary Algorithms through Interactive Graphical Applications

It is very common to observe, especially in Computer Science studies that students have difficulties to correctly understand how some mechanisms based on Artificial Intelligence work. In addition, the scope and limitations of most of these mechanisms are usually presented by professors only in a theoretical way, which does not help students to understand them adequately. In this work, we focus on the problems found when teaching Evolutionary Algorithms (EAs), which imitate the principles of natural evolution, as a method to solve parameter optimization problems. Although this kind of algorithms can be very powerful to solve relatively complex problems, students often have difficulties to understand how they work, and how to apply them to solve problems in real cases. In this paper, we present two interactive graphical applications which have been specially designed with the aim of making Evolutionary Algorithms easy to be understood by students. Specifically, we present: (i) TSPS, an application able to solve the ”Traveling Salesman Problem”, and (ii) FotEvol, an application able to reconstruct a given image by using Evolution Strategies. The main objective is that students learn how these techniques can be implemented, and the great possibilities they offer

Non-emergency patient transport services planning through genetic algorithms

Non-emergency Patient Transport Services (PTS) are provided by ambulance companies for patients who do not require urgent and emergency transport. These patients require transport to or from a health facility like a hospital, but due to clinical requirements are unable to use private or public transport. This task is performed nowadays mainly by human operators, spending a high amount of time and resources to obtain solutions that are suboptimal in most cases. To overcome this limitation, in this paper we present NURA (Non-Urgent transport Routing Algorithm), a novel algorithm aimed at ambulance route planning. In particular, NURA relies on a genetic algorithm to explore the solution space, and it includes a scheduling algorithm to generate detailed routes for ambulances. Experimental results show that NURA is able to outperform human experts in several real scenarios, reducing the time spent by patients in ambulances during non-emergency transportations, increasing ambulance usage, while saving time and money for ambulance companies

Reducing emergence services arrival time by using vehicular communications and Evolution Strategies

Nowadays, traffic jams in urban areas have become a problem that keeps growing every year since the number of vehicles in our cities is continuously increasing. One of the most common causes producing traffic jams are vehicle accidents. Moreover, the arrival time of the emergency services could be raised due to traffic congestion. Intelligent Transportation Systems (ITS) have a key role in order to reduce or mitigate this problem. In this paper, we propose four different approaches addressing the traffic congestion problem, comparing them to obtain the best solution. Using V2I communications, we are able to accurately estimate the traffic density in a certain area, which represents a key parameter to perform efficient traffic redirection, thereby reducing the emergency services arrival time, and avoiding traffic jams when an accident occurs. Specifically, we propose two approaches based on the Dijkstra algorithm, and two approaches based on Evolution Strategies. Notice that, when an accident occurs, time is a critical issue, and the strategies here proposed contribute to find the optimal solution within a short time period.This work was partially supported by the Ministerio de Ciencia e Innovacion, Spain, under Grant TIN2011-27543-C03-01, as well as by the Fundacion Universitaria Antonio Gargallo, the Obra Social de Ibercaja, under Grant 2013/B010, and by the Government of Aragon and the European Social Fund (T91 Research Group).Barrachina, J.; Garrido, P.; Fogue, M.; Martínez, FJ.; Cano Escribá, JC.; Tavares De Araujo Cesariny Calafate, CM.; Manzoni, P. (2014). Reducing emergence services arrival time by using vehicular communications and Evolution Strategies. Expert Systems with Applications. 41(4):1206-1217. https://doi.org/10.1016/j.eswa.2013.08.004S1206121741

Evaluating the impact of a novel message dissemination scheme for vehicular networks using real maps

[EN] In traffic safety applications for vehicular ad hoc networks (VANETs), some warning messages have to be urgently disseminated in order to increase the number of vehicles receiving the traffic warning information. In those cases, redundancy, contention, and packet collisions due to simultaneous forwarding (usually known as the broadcast storm problem) are prone to occur. In the past, several approaches have been proposed to solve the broadcast storm problem in multi-hop wireless networks such as Mobile ad hoc Networks (MANETs). Among them we can find counter-based, distance-based, locationbased, cluster-based, and probabilistic schemes, which have been mainly tested in non-realistic simulation environments. In this paper, we present the enhanced Message Dissemination based on Roadmaps (eMDR), a novel scheme specially designed to increase the percentage of informed vehicles and reduce the notification time; at the same time, it mitigates the broadcast storm problem in real urban scenarios. We evaluate the impact that our scheme has on performance when applied to VANET scenarios based on real city maps, and the results show that it outperforms previous schemes in all situations. 2012 Elsevier Ltd. All rights reserved.This work was partially supported by the Ministerio de Ciencia e Innovacion, Spain, under Grant TIN2011-27543-C03-01, and by the Diputacion General de Aragon, under Grant "subvenciones destinadas a la formacion y contratacion de personal investigador".Fogue, M.; Garrido, P.; Martínez, FJ.; Cano Escribá, JC.; Calafate, CT.; Manzoni, P. (2012). Evaluating the impact of a novel message dissemination scheme for vehicular networks using real maps. Transportation Research Part C: Emerging Technologies. 25(80):61-80. https://doi.org/10.1016/j.trc.2012.04.017S6180258

Using topology and neighbor information to overcome adverse vehicle density conditions

Vehicular networks supporting cooperative driving on the road have attracted much attention due to the plethora of new possibilities they offer to modern Intelligent Transportation Systems. However, research works regarding vehicular networks usually obviate assessing their proposals in scenarios including adverse vehicle densities, i.e., density values that significantly differ from the average values, despite such densities can be quite common in real urban environments (e.g. traffic jams). In this paper, we study the effect of these hostile conditions on the performance of different schemes providing warning message dissemination. The goal of these schemes is to maximize message delivery effectiveness, something difficult to achieve in adverse density scenarios. In addition, we propose the Neighbor Store and Forward (NSF) scheme, designed to be used under low density conditions, and the Nearest Junction Located (NJL) scheme, specially developed for high density conditions. Simulation results demonstrate that our proposals are able to outperform existing warning message dissemination schemes in urban environments under adverse vehicle density conditions. In particular, NSF reduces the warning notification time in low vehicle density scenarios, while increasing up to 23.3% the percentage of informed vehicles. As for high vehicle density conditions, NJL is able to inform the same percentage of vehicles than other existing approaches, while reducing the number of messages up to 46.73%This work was partially supported by the Ministerio de Ciencia e Innovacion, Spain, under Grant TIN2011-27543-C03-01, by the Fundacion Universitaria Antonio Gargallo and the Obra Social de Ibercaja, under Grant 2013/B010, as well as the Government of Aragon and the European Social Fund (T91 Research Group).Sanguesa, JA.; Fogue, M.; Garrido, P.; Martinez, FJ.; Cano Escribá, JC.; Tavares De Araujo Cesariny Calafate, CM. (2014). Using topology and neighbor information to overcome adverse vehicle density conditions. Transportation Research Part C: Emerging Technologies. 42:1-13. https://doi.org/10.1016/j.trc.2014.02.010S1134

An Infrastructureless Approach to Estimate Vehicular Density in Urban Environments

In Vehicular Networks, communication success usually depends on the density of vehicles, since a higher density allows having shorter and more reliable wireless links. Thus, knowing the density of vehicles in a vehicular communications environment is important, as better opportunities for wireless communication can show up. However, vehicle density is highly variable in time and space. This paper deals with the importance of predicting the density of vehicles in vehicular environments to take decisions for enhancing the dissemination of warning messages between vehicles. We propose a novel mechanism to estimate the vehicular density in urban environments. Our mechanism uses as input parameters the number of beacons received per vehicle, and the topological characteristics of the environment where the vehicles are located. Simulation results indicate that, unlike previous proposals solely based on the number of beacons received, our approach is able to accurately estimate the vehicular density, and therefore it could support more efficient dissemination protocols for vehicular environments, as well as improve previously proposed schemes.This work was partially supported by the Ministerio de Ciencia e Innovacion, Spain, under Grant TIN2011-27543-C03-01, as well as by the Fundacion Universitaria Antonio Gargallo (FUAG), and the Caja de Ahorros de la Inmaculada (CAI).Sanguesa, JA.; Fogue, M.; Garrido, P.; Martinez, FJ.; Cano Escribá, JC.; Tavares De Araujo Cesariny Calafate, CM.; Manzoni, P. (2013). An Infrastructureless Approach to Estimate Vehicular Density in Urban Environments. Sensors. 13(2):2399-2418. doi:10.3390/s130202399S2399241813

A system for automatic notification and severity estimation of automotive accidents

© 2013 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.New communication technologies integrated into modern vehicles offer an opportunity for better assistance to people injured in traffic accidents. Recent studies show how communication capabilities should be supported by artificial intelligence systems capable of automating many of the decisions to be taken by emergency services, thereby adapting the rescue resources to the severity of the accident and reducing assistance time. To improve the overall rescue process, a fast and accurate estimation of the severity of the accident represent a key point to help emergency services better estimate the required resources. This paper proposes a novel intelligent system which is able to automatically detect road accidents, notify them through vehicular networks, and estimate their severity based on the concept of data mining and knowledge inference. Our system considers the most relevant variables that can characterize the severity of the accidents (variables such as the vehicle speed, the type of vehicles involved, the impact speed, and the status of the airbag). Results show that a complete Knowledge Discovery in Databases (KDD) process, with an adequate selection of relevant features, allows generating estimation models that can predict the severity of new accidents. We develop a prototype of our system based on off-the-shelf devices and validate it at the Applus+ IDIADA Automotive Research Corporation facilities, showing that our system can notably reduce the time needed to alert and deploy emergency services after an accident takes place.This work was partially supported by the Ministerio de Ciencia e Innovacion, Spain, under Grant TIN2011-27543-C03- 01, and by the Diputacion General de Aragon, under Grant "subvenciones destinadas a la formacion y contratacion de personal investigador."Fogue, M.; Garrido, P.; Martínez, FJ.; Cano Escribá, JC.; Tavares De Araujo Cesariny Calafate, CM.; Manzoni, P. (2014). A system for automatic notification and severity estimation of automotive accidents. IEEE Transactions on Mobile Computing. 13(5):948-963. https://doi.org/10.1109/TMC.2013.35S94896313

Evaluating the feasibility of using smartphones for ITS safety applications

“©2013 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.Driving security and comfort can be improved by applying Intelligent Transportation Systems (ITS) proposals. The low adoption rate of new ITS hardware and software products is slowing down the market introduction of these solutions. In this paper we present a driving safety application for smartphones based on a warning dissemination protocol called eMDR. The use of smartphones minimizes the hardware cost and eliminates most of the adoption barriers; users will no longer have to install new dedicated devices in their vehicles. Instead, they will simply have to install an application in their smartphone. Our application is integrated with a Navigation System which provides access to road maps, current location, and route information. We analyzed the behavior of the wireless channel and the GPS location service under different conditions to assess the feasibility of our proposal. Results showed that, in C2C communications, smartphones are able to provide a reasonable degree of connectivity, and that the degree of precision achieved is enough for certain types of driving safety applications.This work was partially supported by the Ministerio de Ciencia e Innovación, Spain, under Grants TIN2011-27543-C03-01 and BES-2012-052673.Tornell, SM.; Tavares De Araujo Cesariny Calafate, CM.; Cano Escribá, JC.; Manzoni, P.; Fogue, M.; Martínez, FJ. (2013). Evaluating the feasibility of using smartphones for ITS safety applications. IEEE. https://doi.org/10.1109/VTCSpring.2013.6692553

Automatic Accident Detection: Assistance Through Communication Technologies and Vehicles

[EN] The symbiosis between communication technologies and vehicles offer a priceless opportunity to improve assistance to people injured in traffic accidents, providing information about the incident to reduce the response time of emergency services. Determining more accurately the required human and material resources for each particular accident could significantly reduce the number of victims. This paper presents our novel system prototype especially designed to detect and provide faster assistance for traffic accidents, thereby minimizing the consequences on the passengers¿ health. The proposed system requires each vehicle to be endowed with an On-Board Unit responsible for detecting and reporting accident situations to an external Control Unit that estimates its severity, allocating the necessary resources for the rescue operation. The development of our prototype based on off-the-shelf devices, and its validation at the Applus+ IDIADA Automotive Research Corporation facilities, shows that our system could notably reduce the time needed to alert and deploy the emergency services after an accident takes place.This work was partially supported by the Ministerio de Ciencia e Innovación, Spain, under Grant TIN2011-27543-C03-01, and by the Diputación General de Aragón, under Grant subvenciones destinadas a la formación y contratación de personal investigador.Fogue, M.; Garrido, P.; Martínez, FJ.; Cano Escribá, JC.; Tavares De Araujo Cesariny Calafate, CM.; Manzoni, P. (2012). Automatic Accident Detection: Assistance Through Communication Technologies and Vehicles. IEEE Vehicular Technology Magazine. 7(3):90-100. doi:10.1109/MVT.2012.2203877S901007

A novel approach for traffic accidents sanitary resource allocation based on multi-objective genetic algorithms

[EN] The development of communication technologies integrated in vehicles allows creating new protocols and applications to improve assistance in traffic accidents. Combining this technology with intelligent systems will permit to automate most of the decisions needed to generate the appropriate sanitary resource sets, thereby reducing the time from the occurrence of the accident to the stabilization and hospitalization of the injured passengers. However, generating the optimal allocation of sanitary resources is not an easy task, since there are several objectives that are mutually exclusive, such as assistance improvement, cost reduction, and balanced resource usage. In this paper, we propose a novel approach for the sanitary resources allocation in traffic accidents. Our approach is based on the use of multiobjective genetic algorithms, and it is able to generate a list of optimal solutions accounting for the most representative factors. The inputs to our model are: (i) the accident notification, which is obtained through vehicular communication systems, and (ii) the severity estimation for the accident, achieved through data mining. We evaluate our approach under a set of vehicular scenarios, and the results show that a memetic version of the NSGA-II algorithm was the most effective method at locating the optimal resource set, while maintaining enough variability in the solutions to allow applying different resource allocation policies. 2012 Elsevier Ltd. All rights reserved.This work was partially supported by the Ministerio de Ciencia e Innovacion, Spain, under Grant TIN2011-27543-C03-01, and by the Diputacion General de Aragon, under Grant "subvenciones destinadas a la formacion y contratacion de personal investigador".Fogue, M.; Garrido, P.; Martínez, FJ.; Cano Escribá, JC.; Tavares De Araujo Cesariny Calafate, CM.; Manzoni, P. (2013). A novel approach for traffic accidents sanitary resource allocation based on multi-objective genetic algorithms. Expert Systems with Applications. 40(1):323-336. doi:10.1016/j.eswa.2012.07.056S32333640