MSWIM

Vehicular ad hoc networks (VANETs) are a fundamental compo- nent of intelligent transportation systems, using real-time data from inter-connected vehicles to provide us faster and safer trips. However, these benefits raise a number of security ...

Federated Learning (FL) protects privacy during autonomous vehicle machine learning (ML) operations. FL enables cooperative training of a single ML model across multiple edge devices, leveraging distributed datasets while maintaining data locality. ...

The proliferation of cellular networks has become instrumental in the implementation of road safety applications due to the extensive penetration rate of this technology among road users and its promise to reduce message exchange latency times. Among ...

Connected and Autonomous Vehicles (CAVs) are emerging as an inevitable trend in the future of the automotive industry, drawing collaborative attention from academia, industry, and government sectors. However, the inherent limitations in the sensing ...

The growth of electric vehicle (EV) adoption is bringing an increased demand for electric vehicle supply equipment (EVSE) infrastructure. With this growth, however, it is inevitable that vulnerabilities are discovered, which motivates an in-depth ...

The tremendous development in battery technology has made the use of electric vehicles (EVs) a reality and the growing usage of autonomous electric vehicles (AEVs) over the past couple of years has posed many serious challenges. To date, much IoT ...

Ensuring the safe and effective path planning of automated vehicles in uncertain conditions hinges on the precise and dependable anticipation of future movements of nearby vehicles, coupled with a comprehensive grasp of the surrounding environment. This ...

Computer-vision algorithms have been used to enhance hands-free user interactions with smart systems. Traditional approaches for object and gesture detection and recognition are through the processing of video frames by convolutional neural networks (...

Situational awareness can help the safety of automated vehicles, which involves understanding and forecasting the motions of nearby road users. Accurate motion forecasting enhances vehicular commutations, road safety, and mobility management. Early ...

This work addresses challenges in IoT data quality management. IoT applications in domains like Smart Cities, Smart Healthcare, and Industry 4.0 rely on the Internet for automated services. However, resource limitations and harsh environments of IoT ...

Vehicle platooning has gained significant attention due to its potential to enhance road safety and efficiency. Leveraging stochastic optimization methods, this paper presents a distributed Stochastic Model Predictive Control (SMPC) controller tailored ...

In recent years, Internet traffic has grown constantly, and new high-throughput applications have been introduced and widely used by mobile users. This has necessitated improvements in the access networks and transport protocols. Beyond 5G and 6G (B5G/...

Vehicle-to-Vehicle (V2V) communication is an essential component of the Intelligent Transportation System (ITS), which enables realtime traffic data sharing and collective awareness among vehicles and promotes a safer, more effective, and ...

\beginabstract Vehicular Edge Computing (VEC) environments require an efficient offloading orchestration between vehicles and the network edge since most of the applications in these scenarios have low latency constraints that stem from both operational ...

We propose a dynamic path planner that uses a multi-agent reinforcement learning (MARL) model with novel reward functions for multi-drone search and rescue (SAR) missions. We design a mission environment where a multi-drone team covers an area to detect ...

This article focuses on the analysis and evaluation of the 802.11p, LTE-V2X mode 4, and NR-V2X mode 2 technologies. The addressed problem is the need to assess the performance of these technologies in meeting the requirements of advanced V2X ...