Julio A. Sanguesa

Dr. Julio A. Sanguesa

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Research Focus & Metrics

Academic Career Length

15Years (2012-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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15 March 2021 in Smart Cities
Verified
Journal Article
Open access
PDF file
JSJulio A. Sanguesa
Julio A. Sanguesa
VTVicente Torres-Sanz
Vicente Torres-Sanz
Piedad GarridoPiedad Garrido
Piedad Garrido
Francisco J. MartinezFrancisco J. Martinez
Francisco J. Martinez
JMJohann Marquez-Barja
Johann Marquez-Barja
Electric Vehicles (EVs) are gaining momentum due to several factors, including the price reduction as well as the climate and environmental awareness. This paper reviews the advances of EVs regarding battery technology trends, charging methods, as well as new research challenges and open opportunities. More specifically, an analysis of the worldwide market situation of EVs and their future prospects is carried out. Given that one of the fundamental aspects in EVs is the battery, the paper presents a thorough review of the battery technologies—from the Lead-acid batteries to the Lithium-ion. Moreover, we review the different standards that are available for EVs charging process, as well as the power control and battery energy management proposals. Finally, we conclude our work by presenting our vision about what is expected in the near future within this field, as well as the research aspects that are still open for both industry and academic communities.

9 January 2018 in Applied Sciences
Verified
Journal Article
Open access
PDF file
MFManuel Fogue
Manuel Fogue
JSJulio A. Sanguesa
Julio A. Sanguesa
Francisco J. MartinezFrancisco J. Martinez
Francisco J. Martinez
JMJohann Marquez-Barja
Johann Marquez-Barja
Vehicular networks make use of the Roadside Units (RSUs) to enhance the communication capabilities of the vehicles in order to forward control messages and/or to provide Internet access to vehicles, drivers and passengers. Unfortunately, within vehicular networks, the wireless signal propagation is mostly affected by buildings and other obstacles (e.g., urban fixtures), in particular when considering the IEEE 802.11p standard. Therefore, a crowded RSU deployment may be required to ensure vehicular communications within urban environments. Furthermore, some applications, notably those applications related to safety, require a fast and reliable warning data transmission to the emergency services and traffic authorities. However, communication is not always possible in vehicular environments due to the lack of connectivity even employing multiple hops. To overcome the signal propagation problem and delayed warning notification time issues, an effective, smart, cost-effective and all-purpose RSU deployment policy should be put into place. In this paper, we propose the genetic algorithm for roadside unit deployment (GARSUD) system, which uses a genetic algorithm that is capable of automatically providing an RSU deployment suitable for any given road map layout. Our simulation results show that GARSUD is able to reduce the warning notification time (the time required to inform emergency authorities in traffic danger situations) and to improve vehicular communication capabilities within different density scenarios and complexity layouts.

16 December 2015 in Sensors
Verified
Journal Article
Open access
PDF file
JSJulio A. Sanguesa
Julio A. Sanguesa
JBJavier Barrachina
Javier Barrachina
MFManuel Fogue
Manuel Fogue
Piedad GarridoPiedad Garrido
Piedad Garrido
Francisco J. MartinezFrancisco J. Martinez
Francisco J. Martinez
Pietro ManzoniPietro Manzoni
Pietro Manzoni
Wireless technologies are making the development of new applications and services in vehicular environments possible since they enable mobile communication between vehicles (V2V), as well as communication between vehicles and infrastructure nodes (V2I). Usually, V2V communications are dedicated to the transmission of small messages mainly focused on improving traffic safety. Instead, V2I communications allow users to access the Internet and benefit from higher level applications. The combination of both V2V and V2I, known as V2X communications, can increase the benefits even further, thereby making intelligent transportation systems (ITS) a reality. In this paper, we introduce V2X-d, a novel architecture specially designed to estimate traffic density on the road. In particular, V2X-d exploits the combination of V2V and V2I communications. Our approach is based on the information gathered by sensors (i.e., vehicles and road side units (RSUs)) and the characteristics of the roadmap topology to accurately make an estimation of the instant vehicle density. The combination of both mechanisms improves the accuracy and coverage area of the data gathered, while increasing the robustness and fault tolerance of the overall approach, e.g., using the information offered by V2V communications to provide additional density information in areas where RSUs are scarce or malfunctioning. By using our collaborative sensing scheme, future ITS solutions will be able to establish adequate dissemination protocols or to apply more efficient traffic congestion reduction policies, since they will be aware of the instantaneous density of vehicles.

1 January 2016 in Mobile Information Systems
Verified
Journal Article
Open access
PDF file
JSJulio A. Sanguesa
Julio A. Sanguesa
MFManuel Fogue
Manuel Fogue
PGPiedad Garrido
Piedad Garrido
Francisco J. MartinezFrancisco J. Martinez
Francisco J. Martinez
JCJuan-Carlos Cano
Juan-Carlos Cano
Carlos T. CalafateCarlos T. Calafate
Carlos T. Calafate
Vehicle-to-vehicle (V2V) communications also known as vehicular ad hoc networks (VANETs) allow vehicles to cooperate to increase driving efficiency and safety on the roads. In particular, they are forecasted as one of the key technologies to increase traffic safety by providing useful traffic services. In this scope, vehicle-to-vehicle dissemination of warning messages to alert nearby vehicles is one of the most significant and representative solutions. The main goal of the different dissemination strategies available is to reduce the message delivery latency of such information while ensuring the correct reception of warning messages in the vehicle’s neighborhood as soon as a dangerous situation occurs. Despite the fact that several dissemination schemes have been proposed so far, their evaluation has been done under different conditions, using different simulators, making it difficult to determine the optimal dissemination scheme for each particular scenario. In this paper, besides reviewing the most relevant broadcast dissemination schemes available in the recent literature, we also provide a fair comparative analysis by evaluating them under the same environmental conditions, focusing on the same metrics, and using the same simulation platform. Overall, we provide researchers with a clear guideline of the benefits and drawbacks associated with each scheme.

23 April 2018 in IEEE Access
Verified
Journal Article
Open access
VTVicente Torres-Sanz
Vicente Torres-Sanz
JSJulio A. Sanguesa
Julio A. Sanguesa
Francisco J. MartinezFrancisco J. Martinez
Francisco J. Martinez
Piedad GarridoPiedad Garrido
Piedad Garrido
JMJohann Marquez-Barja
Johann Marquez-Barja
It is essential to establish smart and efficient charging strategies for electric vehicles, due to the increase of their sales, and especially taking into account that many of these vehicles will be recharged in private parking lots, where the charging points features are limited. In this article, we propose four different charging methods: the cheapest (C), the Cheapest Starting (CS), the Low Cost (LC), and the Last Period (LP) schemes, as an alternative to the traditional Plug and Charge (P&C) method. Our objective is to find better strategies for an automatic, efficient, and scheduled electric vehicles’ charging process, avoiding peak power demands and promoting recharges at off-peak hours, where electricity prices are low. According to this, a smart charger could use our proposed methods to enhance the charging process at residential homes. To assess our proposal, we simulate the battery recharging of 1,000 vehicles per day during a full year, considering the use of domestic electrical plugs, and real electricity pricing. Additionally, three different scenarios have been simulated: (i) a regular-demand scenario, (ii) a high-demand scenario, and (iii) an extra-demand scenario, in which the vehicles arrive with an average battery level of only 25%. Simulation results confirm that using our charging methods, we can save between 46.9% to 75.2% in terms of electricity fee while maintaining similar battery levels after the charging process.

1 April 2015 in Computer Communications
Verified
Journal Article
Closed access
JSJulio A. Sanguesa
Julio A. Sanguesa
MFManuel Fogue
Manuel Fogue
PGPiedad Garrido
Piedad Garrido
Francisco J. MartinezFrancisco J. Martinez
Francisco J. Martinez
Juan-Carlos CanoJuan-Carlos Cano
Juan-Carlos Cano
Pietro ManzoniPietro Manzoni
Pietro Manzoni