Raphael Frank

CORNER: a realistic urban propagation model for VANET

Recent advances in portable technologies suggest that ad hoc networks will finally move out from the research and military harbors to the commercial world. In particular, vehicular safety and entertainment applications are mature for the market. Several major manufacturer are considering vehicular communications as an opportunity to increase the profitability and marketability of their vehicles. In this phase, simulations are essential to evaluate the performance of protocols and applications large urban Ad Hoc and Vehicular networks. This paper tackles on the long overdue issue of an high fidelity propagation model for urban ad hoc networks. In particular, we propose CORNER a low computational cost yet accurate urban propagation prediction technique for ad hoc networks in urban scenarios. We also provide validation of the model through a side-to-side comparison of real experiments and simulations.

Driver Behavior Profiling Using Smartphones: A Low-Cost Platform for Driver Monitoring

Todays 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.

CORNER: A Radio Propagation Model for VANETs in Urban Scenarios

Advances in portable technologies and emergence of new applications stimulate interest in urban vehicular communications for commercial, military, and homeland defense applications. Simulation is an essential tool to study the behavior and evaluate the performance of protocols and applications in large-scale urban vehicular ad hoc networks (VANET). In this paper, we propose CORNER, a low computational cost yet accurate urban propagation model for mobile networks. CORNER estimates the presence of buildings and obstacles along the signal path using information extrapolated from urban digital maps. A reverse geocoding algorithm is used to classify the propagation situation of any two nodes that need to communicate starting from their geographical coordinates. We classify the relative position of the sender and the receiver as in line of sight (LOS) or nonline of sight (NLOS). Based on this classification, we apply different formulas to compute the path loss (PL) metric. CORNER has been validated through extensive on-the-road experiments, the results show high accuracy in predicting the network connectivity. In addition, on-the-road experiments suggest the need to refine the fading model to differentiate between LOS, and NLOS situations. Finally, we show the impact of CORNER on simulation results for widely used applications.

Luxembourg SUMO Traffic (LuST) Scenario: 24 hours of mobility for vehicular networking research

Different research communities varying from telecommunication to traffic engineering are working on problems related to vehicular traffic congestion, intelligent transportation systems, and mobility patterns using information collected from a variety of sensors. To test the solutions, the first step is to use a vehicular traffic simulator with an appropriate scenario in order to reproduce realistic mobility patterns. Many mobility simulators are available, and the choice is usually done based on the size and type of simulation required, but a common problem is to find a realistic traffic scenario. In order to evaluate and compare new communication protocols for vehicular networks, it is necessary to use a wireless network simulator in combination with a vehicular traffic simulator. This additional step introduces further requirements for the scenario. The aim of this work is to provide a scenario able to meet all the common requirements in terms of size, realism and duration, in order to have a common basis for the evaluations. In the interest of building a realistic scenario, we decided to start from a real city with a standard topology common in mid-size European cities, and real information concerning traffic demands and mobility patterns. In this paper we show the process used to build the Luxembourg SUMO Traffic (LuST) Scenario, and present a summary of its characteristics together with an overview of its possible use cases.

TrafRoute: A different approach to routing in vehicular networks

In the near future vehicular networks based on wireless technology will be part of our lives. Efficient and robust routing algorithms will play a key role in the success of such technology. In this paper we present TrafRoute, an efficient and robust routing scheme for vehicular networks, suitable for both Vehicle-to-Vehicle and Vehicle-to-Infrastructure communications. TrafRoute introduces a novel approach to routing that involves landmark-based routes and forwarder self-election, exploiting the knowledge of the underlying road network. We demonstrate TrafRoutes efficiency and robustness through simulation studies performed with accurate mobility and propagation models.

Bluetooth Low Energy: An alternative technology for VANET applications

Vehicles are getting increasingly connected. Several technologies have emerged over the last decade that allow cars to communicate with each other and with the Internet. In this paper we propose to use the new Bluetooth Low Energy (BLE) standard as an alternative technology to exchange data between vehicles. By the means of experiments we show that smartphones with BLE radios can be used to send information at low latency from one car to another even while driving. A communication range of up to 100m can be achieved depending on the scenario and environment. Those promising first results are then used as basis for discussion to identify the potential of BLE for different types of vehicular applications.

Driver behavior profiling using smartphones

The proliferation of smartphones and mobile devices embedding different types of sensors sets up a prodigious and distributed sensing platform. In particular, in the last years there has been an increasing necessity to monitor drivers to identify bad driving habits in order to optimize fuel consumption, to reduce CO2 emissions or, indeed, to design new reliable and fair pricing schemes for the insurance market. In this paper, we analyze the driver sensing capacity of smartphones. We propose a mobile tool that makes use of the most common sensors embedded in current smartphones and implement a Fuzzy Inference System that scores the overall driving behavior by combining different fuzzy sensing data.

Bluetooth Low Energy performance and robustness analysis for Inter-Vehicular Communications

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 analyse how BLE is affected by varying speed, distance and traffic conditions. We found that the maximum communication range between two devices can go beyond 100?m and that a robust connection, capable of handling sudden signal losses or interferences, can be achieved up to a distance of 50?m even for varying traffic and driving conditions. We then present a proof-of-concept mobile application for off-the-shelf smartphones that can be used to transmit data over multiple hops. Next, we analyse how BLE handles other interferences on the same frequency band by building and validating an interference testbed based on the IEEE 802.11 technology. Finally we discuss the advantages and limitations of BLE for Inter-Vehicular Communications (IVC) and propose potential applications.

A Cooperative Advanced Driver Assistance System to Mitigate Vehicular Traffic Shock Waves

We address the problem of shock wave formation in uncoordinated highway traffic. First, we identify the combination of heavy traffic and small traffic perturbations or unexpected driver actions as the main causes of highway traffic jams. Then we introduce a novel distributed communication protocol that enables us to eliminate upstream shock wave formation even with low system penetration rates. Based on traffic information ahead, we propose a Cooperative Advanced Driver Assistance System (CADAS) that recommends non-intuitive velocity reductions in order to redistribute traffic more uniformly thereby eliminating traffic peaks. Simulation results show that CADAS significantly increases the average velocity and therewith reduces the overall travel time and avoids unnecessary slowdowns.

CORNER: a step towards realistic simulations for VANET

Advances in portable technologies and emergence of new applications stimulate interest in urban vehicular communications for commercial, military, and homeland defense applications. Simulation is an essential tool to study the behavior and evaluate the performance of protocols and applications in large-scale urban vehicular networks. In this paper we propose CORNER a low computational cost yet accurate urban propagation model for mobile networks. CORNER estimates the presence of buildings and obstacles along the signal path using information extrapolated from urban digital maps. A reverse geocoding algorithm is used to classify the propagation situation of any two nodes that need to communicate starting from their geographical coordinates. Sender and Receiver are classified as in Line of Sight if there are no obstacles in between, and as NON in Line of Sight when there are obstacles (i.e. buildings) between them. CORNER has been validated through extensive on-the-road experiments, the results show high accuracy in predicting the network connectivity. In addition, on-the-road experiments suggest the need to refine the fading model to differentiate between Line of Sight, and NON Line of Sight situations. Finally, we show the impact of CORNER on simulation results for widely used applications.