Subhadeep Patra

GRCBox: extending smartphone connectivity in vehicular networks

The low penetration of connectivity-enabled OBUs is delaying the deployment of vehicular networks (VNs) and therefore the development of vehicular delay tolerant network (VDTN) applications, among others. In this paper we present GRCBox, an architecture based on RaspberryPi that allows integrating smartphones in VNs. GRCBox is based on a low-cost device that combines several pieces of software to provide ad hoc and multi-interface connectivity to smartphones. Using GRCBox each application can choose the interface for its data flows, which increases flexibility and will allow developers to easily implement applications based on ad hoc connectivity, such as VDTN applications.

EYES: A Novel Overtaking Assistance System for Vehicular Networks

Developments in the ITS area are received with great expectation by both consumers and industry. Despite their huge potential benefits, ITS solutions suffer from the slow pace of adoption by manufacturers. In this paper we propose EYES, an ITS system that aims at helping drivers in overtaking. The system autonomously creates a network of the devices running EYES, and provides drivers with a video feed from the vehicle located just ahead, thus presenting a better view of any vehicles coming from the opposite direction and the road ahead. This is specially useful when the front view of the driver is blocked by large vehicles, and thus the decision whether to overtake can be taken based on the visuals provided by the application. We have validated EYES, the proposed overtaking assistance system, in both indoor and realistic scenarios involving vehicular network, and preliminary results allow being optimistic about its effectiveness and applicability.

An Intelligent Transportation System Application for Smartphones Based on Vehicle Position Advertising and Route Sharing in Vehicular Ad-Hoc Networks

Alerting drivers about incoming emergency vehicles and their routes can greatly improve their travel time in congested cities, while reducing the risk of accidents due to distractions. This paper contributes to this goal by proposing Messiah, an Android application capable of informing regular vehicles about incoming emergency vehicles like ambulances, police cars and fire brigades. This is made possible by creating a network of vehicles capable of directly communicating between them. The user can, therefore, take driving decisions in a timely manner by considering incoming alerts. Using the support of our GRCBox hardware, the application can rely on vehicular ad-hoc network communications in the 5 GHz band, being V2V (vehicle-to-vehicle) communication provided through a combination of Android-based smartphone and our GRCBox device. The application was tested in three different scenarios with different levels of obstruction, showing that it is capable of providing alerts up to 300 meters, and notifying vehicles within less than one second.

Integration of vehicular network and smartphones to provide real-time visual assistance during overtaking

The Intelligent Transportation Systems area has experienced great developments in the recent past, although suffering from slow adoption ratios thus depriving consumers of many interesting and innovative applications. The only solution to this problem is to develop Intelligent Transportation Systems solutions using the already available technologies that are within the grasp of the common people, to make them cost-effective, quick to deploy and easy to adopt. We have therefore developed an affordable Intelligent Transportation Systems that make use of standard smartphones to assist drivers when overtaking. The system autonomously creates a network among the close-by vehicles and provides drivers with a real-time video feed from the one located just ahead. Our system seamlessly offers a better view of the road, and of any vehicle travelling in the opposite direction, being especially useful when the front view of the driver is blocked by large vehicles. We have validated our overtaking assistance system, in both laboratory environment and realistic scenarios. The laboratory tests involved choosing the most effective video codec between MJPEG and H.264, for providing real-time video streaming. Then, using the chosen codec, we performed the outdoor tests to further tune our application to maximise performance. The preliminary results from our experiments allow being optimistic about the effectiveness and applicability of the proposed system.

An ITS solution providing real-time visual overtaking assistance using smartphones

ITS solutions suffer from the slow pace of adoption by manufacturers despite the interest shown by both consumers and industry. Our goal is to develop ITS applications using already available technologies to make them affordable, quick to deploy, and easy to adopt. In this paper we introduce an ITS system for overtaking assistance that provides drivers with a real-time video feed from the vehicle located just in front. This provides a better view of the road ahead, and of any vehicles travelling in the opposite direction, being especially useful when the front view of the driver is blocked by large vehicles. We evaluated our application using H.264 and MJPEG video encoding formats, and determined the most effective codec choice for our case. Experimental results allow us to be optimistic about the effectiveness and applicability of smartphones in providing overtaking assistance based on video streaming in vehicular networks.

A Forward Collision Warning System for Smartphones Using Image Processing and V2V Communication

In this paper, we present a forward collision warning application for smartphones that uses license plate recognition and vehicular communication to generate warnings for notifying the drivers of the vehicle behind and the one ahead, of a probable collision when the vehicle behind does not maintain an established safe distance between itself and the vehicle ahead. The application was tested in both static and mobile scenarios, from which we confirmed the working of our application, even though its performance is affected by the hardware limitations of the smartphones.

A novel On-Board Unit to accelerate the penetration of ITS services

In-vehicle connectivity has experienced a big expansion in recent years. Car manufacturers have mainly proposed OBU-based solutions, but these solutions do not take full advantage of the opportunities of inter-vehicle peer-to-peer communications. In this paper we introduce GRCBox, a novel architecture that allows OEM user-devices to directly communicate when located in neighboring vehicles. In this paper we also describe EYES, an application we developed to illustrate the type of novel applications that can be implemented on top of the GRCBox. EYES is an ITS overtaking-assistance system that provides the driver with real-time video fed from the vehicle located in front. Finally, we evaluated the GRCbox and the EYES application and showed that, for device-to-device communication, the performance of the GRCBox architecture is comparable to an infrastructure network, introducing a negligible impact.

Determining the relative position of vehicles considering bidirectional traffic scenarios in VANETS

Researchers pertaining to both academia and industry have shown strong interest in developing and improving the existing critical ITS solutions. In some of the existing solutions, specially the ones that aim at providing context aware services, the knowledge of relative positioning of one node by other nodes becomes crucial. In this paper we explore, apart from the conventional use of GPS data, the applicability of image processing to aid in determining the relative positions of nodes in a vehicular network. Experiments conducted show that both the use of location information and image processing works well and can be deployed depending on the requirement of the application. Our experiments show that the results that used location information were affected by GPS errors, while the use of image processing, although producing more accurate results, require significantly more processing power.