Non-intrusive Distracted Driving Detection Based on Driving Sensing Data

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 ▲]

Machine Learning for Reliable Network Attack Detection in SCADA Systems

in 17th IEEE International Conference On Trust, Security And Privacy In Computing And Communications (IEEE TrustCom-18) (2018)

Poster: Performance Evaluation of an Open-Source Audio-Video Bridging/Time-Sensitive Networking Testbed for Automotive Ethernet

Poster (2018)

Automotive Ethernet (AE) is becoming more and more relevant to the automotive industry due to its support of emerging in-car applications, which have high bandwidth demands and stringent requirements in ... [more ▼]

Automotive Ethernet (AE) is becoming more and more relevant to the automotive industry due to its support of emerging in-car applications, which have high bandwidth demands and stringent requirements in terms of latency and time synchronization. One of the standards under consideration for AE is IEEE 802.1 Audio Video Bridging (AVB)/Time Sensitive Networking (TSN) that provides deterministic data link layer and bounded latency to real-time traffic classes. So far, this protocol stack has only been evaluated using either simulations or proprietary and expensive platforms. In this paper, we design a real testbed system for AE using general-purpose single-board computers and conduct experiments to assess the real-time performance of an open-source AVB/TSN implementation. Our preliminary results show that even under heavy load, AVB/TSN can fulfil the latency requirements of AE while keeping a constant latency variation. [less ▲]

Demo: MAMBA: A Platform for Personalised Multimodal Trip Planning

Software (2017)

In recent years, multimodal transportation has become a challenging approach to route planning. Most existing planning systems usually rely on data sourced from different organisations, enabling the user ... [more ▼]

In recent years, multimodal transportation has become a challenging approach to route planning. Most existing planning systems usually rely on data sourced from different organisations, enabling the user to select a limited number of routing strategies. As part of the MAMBA project, developed in Luxembourg until 2017, we have been interested in the potential benefits of multimodal mobility systems. A key factor has been integrated into our studies: the need for a personalised experience at user level, whether when selecting the means of transport or describing user habits (e.g. route style, environment). In this context, we have developed a platform for planning personalised multimodal trips, broken down into the three main modules presented in this demonstration. More importantly, this platform has been developed to facilitate the daily mobility of people in Luxembourg, and considers datasets and characteristics that are specific to this region, which has an exceptionally high volume of daily commuting between Luxembourg and neighbouring countries. [less ▲]

Characterizing Driving Environments Through Bluetooth Discovery

Scientific Conference (2017, October)

Within the world of wireless technologies, Bluetooth has recently been at the forefront of innovation. It is becoming increasingly relevant for vehicles to become aware of their surroundings. Therefore ... [more ▼]

Within the world of wireless technologies, Bluetooth has recently been at the forefront of innovation. It is becoming increasingly relevant for vehicles to become aware of their surroundings. Therefore, having knowledge of nearby Bluetooth devices, both inside and outside other vehicles, can provide the listening vehicles with enough data to learn about their environment. In this paper, we collect and analyze a dataset of Bluetooth Classic (BC) and Low Energy (BLE) discoveries. We evaluate their respective characteristics and ability to provide context-aware information from a vehicular perspective. By taking a look at data about the encountered devices, such as GPS location, quantity, quality of signal and device class information, we infer distinctive behaviors between BC and BLE relative to context and application. For this purpose, we propose a set a features to train a classifier for the recognition of different driving environments (i.e. road classes) from Bluetooth discovery data alone. Comparing the performance of our classifier with different sampling parameters, the presented results indicate that, with our feature selection, we are able to predict with reasonable confidence up to three classes (Highway, City, Extra-Urban) by using only discovery data and no geographical information. This outcome gives promising results targeted at low energy and privacy-friendly applications and can open up a wide range of research directions. [less ▲]

A centralized approach for setting floating content parameters in VANETs

in A centralized approach for setting floating content parameters in VANETs (2017, July 20)

Floating Content (FC) has recently been proposed as an attractive application for mobile networks, such as VANETs, to operate opportunistic and distributed content sharing over a given geographic area ... [more ▼]

Floating Content (FC) has recently been proposed as an attractive application for mobile networks, such as VANETs, to operate opportunistic and distributed content sharing over a given geographic area, namely Anchor Zone (AZ). FC performances are tightly dependent on the AZ size, which in literature is classically chosen by the node that generates the floating message. In the present work, we propose a method to improve FC performances by optimizing the AZ size with the support of a Software Defined Network (SDN) controller, which collects mobility information, such as speed and position, of the vehicles in its coverage range. [less ▲]

An Efficient Service Channel Allocation Scheme in SDN-enabled VANETs

in An Efficient Service Channel Allocation Scheme in SDN-enabled VANETs (2017, June)

Providing infotainment services in Vehicular Adhoc Networks (VANETs) is a key functionality for the future intelligent transportation systems. However, the unique features of vehicular networks such as ... [more ▼]

Providing infotainment services in Vehicular Adhoc Networks (VANETs) is a key functionality for the future intelligent transportation systems. However, the unique features of vehicular networks such as high velocity, intermittent communication links and dynamic density can induce severe performances degradation for infotainment services running on the six Service Channels (SCHs) available in the Dedicated Short Range Communication (DSRC). Although, the Wireless Access in the Vehicular Environment (WAVE) has been proposed for VANETs to support these applications and guarantee the QoS by proposing four different access categories, no service channel scheme has been proposed to ensure fair and interference-aware allocation. To fill this gap, in this work we propose ESCiVA, an Efficient Service Channel allocation Scheme in SDN-enabled VAnets to balance service traffic on the six SCHs and mitigate interferences between services provided on adjacent channels. Extensive simulation results confirm that ESCiVA outperforms the basic SCH allocation method, defined in the WAVE standard [less ▲]

Smartphone-based Adaptive Driving Maneuver Detection: A large-scale Evaluation Study

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 ▲]

Characterizing User Mobility Using Mobile Sensing Systems

in International Journal of Distributed Sensor Networks (2017), 13(8),

Recent technological advances and the ever-greater developments in sensing and computing continue to provide new ways of understanding our daily mobility. Smart devices such as smartphones or smartwatches ... [more ▼]

Recent technological advances and the ever-greater developments in sensing and computing continue to provide new ways of understanding our daily mobility. Smart devices such as smartphones or smartwatches can, for instance, provide an enhanced user experience based on different sets of built-in sensors that follow every user action and identify its environment. Monitoring solutions such as these, which are becoming more and more common, allows us to assess human behavior and movement at different levels. In this article, extended from previous work, we focus on the concept of human mobility and explore how we can exploit a dataset collected opportunistically from multiple participants. In particular, we study how the different sensor groups present in most commercial smart devices can be used to deliver mobility information and patterns. In addition to traditional motion sensors that are obviously important in this field, we are also exploring data from physiological and environmental sensors, including new ways of displaying, understanding, and analyzing data. Furthermore, we detail the need to use methods that respect the privacy of users and investigate the possibilities offered by network traces, including Wi-Fi and Bluetooth communication technologies. We finally offer a mobility assistant that can represent different user characteristics anonymously, based on a combination of Wi-Fi, activity data, and graph theory. [less ▲]

Coordination Mechanisms for Floating Content in Realistic Vehicular Scenario

in Coordination Mechanisms for Floating Content in Realistic Vehicular Scenario (2017)

The increasing interest in vehicular communications draws attention to scalability and network congestion problems and therefore on techniques to offload the traffic, typically carried through the ... [more ▼]

The increasing interest in vehicular communications draws attention to scalability and network congestion problems and therefore on techniques to offload the traffic, typically carried through the infrastructure, to the Vehicle-to-vehicle (V2V) network. Floating content (FC) represents a promising paradigm to share ephemeral content without direct support from infrastructure. It is based on constraining geographically within the Anchor Zone (AZ) the opportunistic replication of a given content among vehicles, in a way that strikes a balance between minimization of resource usage and content availability. Existing works on FC performance modeling are based on standard, homogeneous synthetic mobility models, and it is hence unclear how they actually fit in realistic mobility scenarios. Moreover, the approaches to FC dimensioning they propose assume users have full knowledge of Spatio-temporal mobility patterns, which is hard to achieve in practice. Finally, despite FC is an infrastructure-less communication paradigm, some form of infrastructure support could be available in the vast majority of those application scenarios for which it has been proposed. In this paper, we perform a first attempt at tackling these issues. We focus on how to dimension an Anchor Zone in a realistic vehicular scenario. We propose the first set of simple dimensioning strategies, based on the estimation of some key mobility parameters and of FC performance. We assess such strategies on measurement-based vehicular traces, providing a first indication of their relative performance, and of the feasibility of FC in practical scenarios. [less ▲]