A team of transport modellers at Michigan Technological University have released a study which once again confirms that having cars with some driverless capabilities on the roads reduces congestion and makes roads safer.
In the catchily named paper “A distributionally robust stochastic optimisation-based model predictive control with distributionally robust chance constraints for cooperative adaptive cruise control under uncertain traffic conditions” they explain how they modelled Cooperative Adaptive Cruise Control (CACC) of a string of vehicles under uncertain traffic conditions.
They then look at how that effects traffic flow as a whole and found that other vehicles around the automated ones change their driving habits.
“The experimental results and analyses demonstrate that the proposed model can obtain string-stable, robust, and safe longitudinal cooperative automated driving control of CAVs by proper settings, including the driving-dynamics prediction model, prediction horizon lengths, and time headways,” the researchers say. “Computational analyses are conducted to validate the efficiency of the proposed methods for solving the DRSO-DRCC model for real-time automated driving applications within proper settings.”
The model suggests that helping cars maintain constant time gaps between themselves reduced congestion and emissions by reducing the amount of acceleration and braking.