AI Based Traffic Flow Prediction Model for Connected and Autonomous Electric Vehicles

What do autonomous vehicles mean to traffic congestion and crash? Network traffic flow modeling and simulation for autonomous vehicles

M2M Billing for Electric Autonomous Vehicles

Electric Autonomous Vehicles (EAVs) promise to be an effective way to solve transportation issues such as accidents, emissions and congestion, and aim at establishing the foundation of Machine-to-Machine (M2M) economy. For this to be possible the market should be able to offer appropriate charging services without involving humans. The state-ofthe-art mechanisms of charging and billing do not m...

Autonomous cars: Breakthrough for electric vehicles

Sometimes the breakthrough for a new technology does not materialize in one of those fields which receive most attention and where everybody expects the solution. When the British needed a practical method for determining a ship's longitude in the 18 century, they spent many decades gazing at the stars, compiling lunar tables and searching for astronomic methods for determining longitude. But t...

Traffic modelling framework for electric vehicles

This paper reviews and improves a recently proposed model of road network dynamics. The model is also adapted and generalised to represent the patterns of battery consumption of electric vehicles traveling in the road network. Simulations from the mobility simulator SUMO are given to support and to illustrate the efficacy of the proposed approach. Applications relevant in the field of electric ...

Benefits of V2V Communication for Autonomous and Connected Vehicles

In this paper, we investigate the benefits of Vehicleto-Vehicle (V2V) communication for autonomous vehicles and provide results on how V2V information helps reduce employable time headway in the presence of parasitic lags. For a string of vehicles adopting a Constant Time Headway Policy (CTHP) and availing the on-board information of predecessor’s vehicle position and velocity, the minimum empl...