LSTM-Based Virtual Load Sensor for Heavy-Duty Vehicles.

In this paper, a special recurrent neural network (RNN) called is used to design a virtual load sensor that estimates the mass of heavy vehicles. The estimation algorithm consists of a two-layer LSTM network. The network estimates vehicle mass based on vehicle speed, longitudinal acceleration, engine speed, engine torque, and accelerator pedal position.

How to Stop Disagreeing and Start Cooperatingin the Presence of Asymmetric Packet Loss.

We consider the design of a disagreement correction protocol in multi-vehicle systems. Vehicles broadcast in real-time vital information such as position, direction, speed, acceleration, intention, etc. This information is then used to identify the risks and adapt their trajectory to maintain the highest performance without compromising the safety.