Related papers: Selective data collection in vehicular networks fo…
Wireless Sensor Networks (WSNs) enable a wealth of new applications where remote estimation is essential. Individual sensors simultaneously sense a dynamic process and transmit measured information over a shared channel to a central fusion…
Connected vehicles, facilitated by Vehicle-to-Vehicle (V2V) communications, play a key role in enhancing road safety and traffic efficiency. However, V2V communications primarily rely on wireless protocols, such as Wi-Fi, that require…
In this paper, we present a data-driven Model Predictive Controller that leverages a Gaussian Process to generate optimal motion policies for connected autonomous vehicles in regions with uncertainty in the wireless channel. The…
Data collection in Wireless Sensor Networks (WSN) draws significant attention, due to emerging interest in technologies raging from Internet of Things (IoT) networks to simple "Presence" applications, which identify the status of the…
Wireless sensor networks hold a great potential in the deployment of several applications of a paramount importance in our daily life. Video sensors are able to improve a number of these applications where new approaches adapted to both…
Road traffic jams is a most important problem in nearly all cities around the world, especially in developing regions resulting in enormous delays, increased fuel wastage and monetary losses. In this paper, we have obtained an in-sight idea…
Stop-and-go traffic waves are known for reducing the efficiency of transportation systems by increasing traffic oscillations and energy consumption. In this study, we develop an approach to synthesize a class of additive feedback…
Wireless Sensor Networks (WSNs) experiences several technical challenges such as limited energy, short transmission range, limited storage capacities, and limited computational capabilities. Moreover, the sensor nodes are deployed randomly…
As we navigate our daily commutes, the threat posed by a distracted driver is at a large, resulting in a troubling rise in traffic accidents. Addressing this safety concern, our project harnesses the analytical power of Convolutional Neural…
Vehicular networks are one of the cornerstone of an Intelligent Transportation System (ITS). They are expected to provide ubiquitous network connectivity to moving vehicles while supporting various ITS services, some with very stringent…
Vehicular networks will play an important role in enhancing road safety, improving transportation efficiency, and providing seamless Internet service for users on the road. Reaping the benefit of vehicular networks is contingent upon…
Effective applications of vehicular ad hoc networks in traffic signal control require new methods for detection of malicious data. Injection of malicious data can result in significantly decreased performance of such applications, increased…
Autonomous vehicles (AVs) rely on real-time perception systems to understand road environments and ensure safe navigation. However, implementing reliable perception algorithms on resource-constrained embedded platforms remains challenging…
Convolutional Neural Networks (CNNs) are successfully used for the important automotive visual perception tasks including object recognition, motion and depth estimation, visual SLAM, etc. However, these tasks are typically independently…
In recent years, the wireless sensor network (WSN) is playing a key role in sensing, collecting and disseminating information in various applications. An important feature associated with WSN is to develop an efficient data distribution and…
One of the emerging applications that belong to ambient systems is to transparently and directly interconnect vehicles on roads, making an ad hoc network that enables a variety of applications through distributed software without the need…
In this paper we present a sensor network based architecture for urban traffic management, hierarchically structured on three layers: sensing, processing& aggregation and control. On proposed architecture we define traffic decongestion…
Due to the recent advances in vehicular ad hoc networks (VANETs), smart applications have been incorporating the data generated from these networks to provide quality of life services. In this paper, we have proposed taxonomy of data mining…
Recent advancements in Connected Vehicle (CV) technology have prompted research on leveraging CV data for more effective traffic management. Despite the low penetration rate, such detailed CV data has demonstrated great potential in…
Enabling high-definition (HD)-map-assisted cooperative driving among autonomous vehicles (AVs) to improve the navigation safety faces technical challenges due to increased communication traffic volume for data dissemination and increased…