RESEARCH AREAS
Key research areas include Intelligent Transport System (ITS), ML and AI in VANETs, Blockchain and Security in VANETs, and Smart Cities.
Intelligent Transportation System
Our lab research focuses on improving intelligent transportation services. VANET Lab is working towards safety applications for collision avoidance and fast warning message dissemination. Our research focuses on improving intelligent transportation services. We are working towards safety applications for collision avoidance and fast warning message dissemination.
Machine learning and AI in VANETs
VANET Lab works towards cooperative traffic solutions using machine learning methods that improve route discovery and provide Quality of Service (QoS). In this phase, reinforcement learning techniques and deep learning networks are exploited to enhance routing solutions and the autonomy of the vehicular network.
Blockchain and Security in VANET, Smart City
VANET lab also works for IoT and vehicle security. The Lab tries to find optimal secure networks and provide cooperative security solutions. Various security analyses are used to ensure security in intelligent vehicles and IoT devices.
Specialities
EXata Network Emulator Software (QualNet)
VANET laboratory is equipped with licensed EXata Network Emulator Software (QualNet), which helps in network planning, testing and development. The Qualnet Software helps to mimic the real-time communication network and provide an efficient method to evaluate network behaviour and performance.
DuckieTown AI Lab
Duckietown AI setup is an integration of AI and machine learning in transportation networks to perform autonomy of the vehicular network. It helps students to implement real time vehicular network testbeds and test their network. Duckietown is an integration of advanced technologies using electronics, computers, communication and smart sensors.
Open source simulator
Implementation of Real-Time Vehicular Networks Testbed (using OBU & RSU) and open source software such as ns2/ns3 and OmNet ++ among many others are available in the lab. The students also get hands-on with experiments using Network Hardware (i.e., IoT devices, Raspberry Pi, Routers, Switches, Firewalls, PCs, Servers, Laptops, Sensors, and Arduino) which help to monitor network usage, bandwidth, throughput, delay and security attacks.