References of "Castignani, German 50001206"
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See detailRevisiting Gaussian Mixture Models for Driver Identification
Jafarnejad, Sasan UL; Castignani, German UL; Engel, Thomas UL

in Proceedings of IEEE International Conference on Vehicular Electronics and Safety (ICVES) (ICVES 2018) (2018, September)

The increasing penetration of connected vehicles nowadays has enabled driving data collection at a very large scale. Many telematics applications have been also enabled from the analysis of those datasets ... [more ▼]

The increasing penetration of connected vehicles nowadays has enabled driving data collection at a very large scale. Many telematics applications have been also enabled from the analysis of those datasets and the usage of Machine Learning techniques, including driving behavior analysis predictive maintenance of vehicles, modeling of vehicle health and vehicle component usage, among others. In particular, being able to identify the individual behind the steering wheel has many application fields. In the insurance or car-rental market, the fact that more than one driver make use of the vehicle generally triggers extra fees for the contract holder. Moreover being able to identify different drivers enables the automation of comfort settings or personalization of advanced driver assistance (ADAS) technologies. In this paper, we propose a driver identification algorithm based on Gaussian Mixture Models (GMM). We show that only using features extracted from the gas pedal position and steering wheel angle signals we are able to achieve near 100 accuracy in scenarios with up to 67 drivers. In comparison to the state-of-the-art, our proposed methodology has lower complexity, superior accuracy and offers scalability to a larger number of drivers. [less ▲]

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See detailNon-intrusive Distracted Driving Detection Based on Driving Sensing Data
Jafarnejad, Sasan UL; Castignani, German UL; Engel, Thomas UL

in 4th International Conference on Vehicle Technology and Intelligent Transport Systems (VEHITS 2018) (2018, March)

Nowadays Internet-enabled phones have become ubiquitous, and we all witness the flood of information that often arrives with a notification. Most of us immediately divert our attention to our phones even ... [more ▼]

Nowadays Internet-enabled phones have become ubiquitous, and we all witness the flood of information that often arrives with a notification. Most of us immediately divert our attention to our phones even when we are behind the wheel. Statistics show that drivers use their phone on 88% of their trips and on 2015 in the UnitedKingdom 25% of the fatal accidents were caused by distraction or impairment. Therefore there is need to tackle this issue. However, most of the distraction detection methods either use expensive dedicated hardware and/or they make use of intrusive or uncomfortable sensors. We propose distracted driving detection mechanism using non-intrusive vehicle sensor data. In the proposed method 9 driving signals are used. The data is collected, then two sets of statistical and cepstral features are extracted using a sliding window process, further a classifier makes a prediction for each window frame, lastly, a decision function takes the last l predictions and makes the final prediction. We evaluate the subject independent performance of the proposed mechanism using a driving dataset consisting of 13 drivers. We show that performance increases as the decision window become larger.We achieve the best results using a Gradient Boosting classifier with a decision window of total duration 285seconds which yield ROC AUC of 98.7%. [less ▲]

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See detailPoster: Characterizing Driving Behaviors Through a Car Simulation Platform
Faye, Sébastien UL; Jafarnejad, Sasan UL; Costamagna, Juan UL et al

Poster (2017, November 27)

Human mobility has opened up to many themes in recent years. Human behavior and how a driver might react to certain situations, whether dangerous (e.g. an accident) or simply part of the evolution of new ... [more ▼]

Human mobility has opened up to many themes in recent years. Human behavior and how a driver might react to certain situations, whether dangerous (e.g. an accident) or simply part of the evolution of new technologies (e.g. autonomous driving), leaves many avenues to be explored. Although experiments have been deployed in real situations, it remains difficult to encounter the conditions that certain studies may require. For this reason, we have set up a driving simulator (comprising several modules) that is able to reproduce a realistic driving environment. Although, as the literature has already demonstrated, the conditions are often far from reality, simulation platforms are nonetheless capable of reproducing an incredibly large number of scenarios on the fly. In this poster, we explain how we conceived the simulator, as well as the system we developed for collecting metrics on both the driver and the simulation environment. In addition, we take advantage of this conference to publicly share a dataset consisting of 25 drivers performing the same road circuit on the "Project Cars" game. [less ▲]

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See detailTowards a Real-Time Driver Identification Mechanism Based on Driving Sensing Data
Jafarnejad, Sasan UL; Castignani, German UL; Engel, Thomas UL

in 20th International Conference on Intelligent Transportation Systems (ITSC) (2017)

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See detailSmartphone-based Adaptive Driving Maneuver Detection: A large-scale Evaluation Study
Castignani, German UL; Derrmann, Thierry UL; Frank, Raphaël UL et al

in IEEE Transactions on Intelligent Transportation Systems (2017)

The proliferation of connected mobile devices together with advances in their sensing capacity has enabled a new distributed telematics platform. In particular, smartphones can be used as driving sensors ... [more ▼]

The proliferation of connected mobile devices together with advances in their sensing capacity has enabled a new distributed telematics platform. In particular, smartphones can be used as driving sensors to identify individual driver behavior and risky maneuvers. However, in order to estimate driver behavior with smartphones, the system must deal with different vehicle characteristics. This is the main limitation of existing sensing platforms, which are principally based on fixed thresholds for different sensing parameters. In this paper, we propose an adaptive driving maneuver detection mechanism that iteratively builds a statistical model of the driver, vehicle, and smartphone combination using a multivariate normal model. By means of experimentation over a test track and public roads, we first explore the capacity of different sensor input combinations to detect risky driving maneuvers, and we propose a training mechanism that adapts the profiling model to the vehicle, driver, and road topology. A large-scale evaluation study is conducted, showing that the model for maneuver detection and scoring is able to adapt to different drivers, vehicles, and road conditions. [less ▲]

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See detailTowards Characterizing Bluetooth Discovery in a Vehicular Context
Bronzi, Walter UL; Derrmann, Thierry UL; Castignani, German UL et al

in Vehicular Networking Conference (VNC), 2016 IEEE (2016, December)

Bluetooth has, in recent years, gained more and more momentum. New commodity objects and wearables im- plementing Bluetooth Smart technology (Low Energy) are re- leased everyday. In particular, the ever ... [more ▼]

Bluetooth has, in recent years, gained more and more momentum. New commodity objects and wearables im- plementing Bluetooth Smart technology (Low Energy) are re- leased everyday. In particular, the ever increasing number of discoverable devices both inside and outside a populated area gives us an encouraging insight on future research directions for this technology. In this paper, based on a sensing system developed as an Android application, we evaluate Bluetooth Classic and Low Energy discovery characteristics from a vehic- ular perspective. By recording information about devices nearby (e.g. the number of discovered devices, their signal strength, manufacturer information) and the GPS location we can derive interesting information about a driver’s situation, as well as his/her environment. Presented results indicate that the amount of discovered devices and signal strengths are dependent on velocity and road category. Finally, future work and discussions address potential use-case applications based only on Bluetooth discovery, such as low energy and privacy friendly road and traffic context awareness. The sensing system used in this article is free online under the MIT License. [less ▲]

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See detailTowards Privacy-Neutral Travel Time Estimation from Mobile Phone Signalling Data
Derrmann, Thierry UL; Frank, Raphaël UL; Faye, Sébastien UL et al

in Proceedings of the 2016 IEEE International Smart Cities Conference (ISC2) (2016, September)

Today’s mobile penetration rates enable cellular signaling data to be useful in diverse fields such as transportation planning, the social sciences and epidemiology. Of particular interest for these ... [more ▼]

Today’s mobile penetration rates enable cellular signaling data to be useful in diverse fields such as transportation planning, the social sciences and epidemiology. Of particular interest for these applications are mobile subscriber dwell times. They express how long users stay in the service range of a base station. In this paper, we want to evaluate whether dwell time distributions can serve as predictors for road travel times. To this end, we transform floating car data into synthetic dwell times that we use as weights in a graph-based model. The model predictions are evaluated using the floating car ground truth data. Additionally, we show a potential link between handover density and travel times. We conclude that dwell times are a promising predictor for travel times, and can serve as a valuable input for intelligent transportation systems. [less ▲]

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See detailValidation study of risky event classification using driving pattern factors
Castignani, German UL; Derrmann, Thierry UL; Frank, Raphaël UL et al

Scientific Conference (2015, November 24)

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See detailHandover triggering in IEEE 802.11 Networks
Montavont, Nicolas; Blanc, Alberto; Navas, Renzo et al

in 16th IEEE International Symposium on a World of Wireless, Mobile and Multimedia Networks (2015, June 14)

The current and future IEEE 802.11 deployment could potentially offer wireless Internet connectivity to mobile users. The limited AP radio coverage forces mobile devices to perform frequent handovers ... [more ▼]

The current and future IEEE 802.11 deployment could potentially offer wireless Internet connectivity to mobile users. The limited AP radio coverage forces mobile devices to perform frequent handovers while current operating systems lack efficient mechanisms to manage AP transition. Thus we propose an anticipation-based handover solution that uses a Kalman filter to predict the short term evolution of the received power. This mechanism allows a mobile device to proactively start scanning and executing a handover as soon as better APs are available. We implement our mechanism in Android and we show that our solution provides a better wireless connection. [less ▲]

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See detailDetection of Population Mobility Anomalies in Senegal from Base Station Profiles
Melakessou, Foued UL; Derrmann, Thierry UL; Frank, Raphaël UL et al

Scientific Conference (2015, April 08)

The analysis of Call Detail Records has captured the attention of traffic and transportation researchers to optimize people's mobility. In our work, we would like to analyze Call Detail Records in order ... [more ▼]

The analysis of Call Detail Records has captured the attention of traffic and transportation researchers to optimize people's mobility. In our work, we would like to analyze Call Detail Records in order to extract realistic human mobility models adapted to the Senegal use case. In this paper, we describe our analysis of the available D4D datasets. The first contribution is the modeling of the daily traffic demand profile of each antenna, by considering voice and short message services. The evaluation of mobility models will help to better design and develop future infrastructures in order to better support the actual demand. A classification has been performed into urban, suburban and rural modes. An algorithm has been developed to detect traffic anomalies in 2013, based on the daily profiles. The second contribution corresponds to the generation of inter-antennas and inter-arrondissements mobility graphs for each month of 2013. [less ▲]

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See detailA Cell Dwell Time Model for Synthetic Population Generation from Call Detail Records
Derrmann, Thierry UL; Frank, Raphaël UL; Melakessou, Foued UL et al

Scientific Conference (2015, April 08)

In this work we propose a novel Cell Dwell Time Model that can be used to generate a synthetic population. We introduce two new metrics to define the attractivity of cell sites based on global and ... [more ▼]

In this work we propose a novel Cell Dwell Time Model that can be used to generate a synthetic population. We introduce two new metrics to define the attractivity of cell sites based on global and individual parameters obtained via the analysis of the Data For Development (D4D) Call Detail Records (CDR). We rely on the shortest path road network to interconnect two distant cell sites. The resulting dwell time model can be used to compute accurate user trajectories even with partial information. This work represents a first step towards the generation of a synthetic population that can be used to perform a wide range of simulative studies to evaluate and optimize transportation networks. [less ▲]

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See detailDriver Behavior Profiling Using Smartphones: A Low-Cost Platform for Driver Monitoring
Castignani, German UL; Derrmann, Thierry UL; Frank, Raphaël UL et al

in Intelligent Transportation Systems Magazine, IEEE (2015), 7(1), 91-102

Today's smartphones and mobile devices typically embed advanced motion sensors. Due to their increasing market penetration, there is a potential for the development of distributed sensing platforms. In ... [more ▼]

Today's smartphones and mobile devices typically embed advanced motion sensors. Due to their increasing market penetration, there is a potential for the development of distributed sensing platforms. In particular, over the last few years there has been an increasing interest in monitoring vehicles and driving data, aiming to identify risky driving maneuvers and to improve driver efficiency. Such a driver profiling system can be useful in fleet management, insurance premium adjustment, fuel consumption optimization or CO2 emission reduction. In this paper, we analyze how smartphone sensors can be used to identify driving maneuvers and propose SenseFleet, a driver profile platform that is able to detect risky driving events independently from the mobile device and vehicle. A fuzzy system is used to compute a score for the different drivers using real-time context information like route topology or weather conditions. To validate our platform, we present an evaluation study considering multiple drivers along a predefined path. The results show that our platform is able to accurately detect risky driving events and provide a representative score for each individual driver. [less ▲]

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See detailBluetooth Low Energy for Inter-Vehicular Communications
Bronzi, Walter UL; Frank, Raphaël UL; Castignani, German UL et al

in 2014 IEEE Vehicular Networking Conference (VNC) (2014, December)

Bluetooth Low Energy (BLE) is quickly and steadily gaining importance for a wide range of applications. In this paper we investigate the potential of BLE in a vehicular context. By means of experiments ... [more ▼]

Bluetooth Low Energy (BLE) is quickly and steadily gaining importance for a wide range of applications. In this paper we investigate the potential of BLE in a vehicular context. By means of experiments, we first evaluate the characteristics of the wireless channel, then we define a set of driving scenarios to analyze how BLE is affected by varying speed, distance and traffic conditions. We that found the maximum communication range between two devices can go beyond 100 meters and that a robust connection can be achieved up to a distance of 50 meters even for varying traffic and driving conditions. Next, we present a proof-of-concept mobile application for off-the-shelf smartphones that can be used to transmit data over multiple hops. Finally we discuss the advantages and limitations of BLE for Inter-Vehicular Communications (IVC) and propose potential applications. [less ▲]

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See detailBluetooth Low Energy: An Alternative Technology for VANET Applications
Frank, Raphaël UL; Bronzi, Walter UL; Castignani, German UL et al

in Proceedings of the 11th IEEE/IFIP Annual Conference on Wireless On-demand Network Systems and Services (2014, April)

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See detailCollaborative Traffic Sensing: A Case Study of a Mobile Phone Based Traffic Management System
Frank, Raphaël UL; Weitz, Hervé UL; Castignani, German UL et al

in Proceedings of the 11th IEEE Consumer Communications and Networking Conference (CCNC'14) (2014, January 10)

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See detailA novel Eco-Driving Application to Reduce Energy Consumption of Electric Vehicles
Frank, Raphaël UL; Castignani, German UL; Schmitz, Raoul et al

in Proceedings of the 2nd International Conference on Connected Vehicles & Expo (ICCVE 2013) (2013, December)

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See detailAccelerating short transfers in 802.11 networks
Arcia-Moret, Andres; Montavont, Nicolas; Castignani, German UL

Poster (2013, November 14)

The legacy bandwidth discovery phase of TCP spends an unnecessary number of RTTs for reaching the fair share of the network. In this article we introduce a simple modification at the receiver that splits ... [more ▼]

The legacy bandwidth discovery phase of TCP spends an unnecessary number of RTTs for reaching the fair share of the network. In this article we introduce a simple modification at the receiver that splits the TCP ACKs in a controlled manner. This mechanism allows to fast ramp-up the TCP congestion window. Our experiments performed in a real testbed show benefits not only in the increased data throughput but also in a non-congested uplink (Acknowledgement) path in an 802.11 access. [less ▲]

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See detailA Study of Urban IEEE 802.11 Hotspot Networks: Towards a Community Access Network
Castignani, German UL; Monetti, Juan; Montavont, Nicolas et al

in A Study of Urban IEEE 802.11 Hotspot Networks: Towards a Community Access Network (2013, November 13)

With the increasing demand for faster data connectivity, different wireless technologies have been deployed in the last decade, creating a heterogeneous wireless environment. Such wireless diversity is ... [more ▼]

With the increasing demand for faster data connectivity, different wireless technologies have been deployed in the last decade, creating a heterogeneous wireless environment. Such wireless diversity is mainly composed of 2G/3G/4G cellular base stations, IEEE 802.11 hotspots and Community Networks. Previous work suggests that the increasing popularity of IEEE 802.11 networks would mitigate the overloading of current operator-based cellular deployments. However, the unpredictable characteristics of IEEE 802.11 deployments and its loose coupling to cellular architectures limit its user performance in terms of throughput and mobility capacity. In this paper, we describe an evaluation study of a commercial-grade hotspot network in the city of Luxembourg, namely HOTCITY. Through a set of experiments, we provide a characterization of the hotspot network and give a set of performance indicators. Finally, we evaluate hotspot networks' potential to support cellular offloading through the integration of outdoor hotspots and private access points deployed indoors in a single Community Network. [less ▲]

Detailed reference viewed: 127 (1 UL)