Coasting advice based on the analytical solutions of the train motion model

A large variety of supervision, data analysis and communication algorithms monitor trains, exploiting most of their available computational power. On-board eco-driving algorithms such as Driver Advisory Systems are no exception, as the computational power available can limit their complexity and features. This was the case of Roltijd, the in...

Real-Time Predictive Speed Control for Eco-Driving at Signalized Intersections Considering Queue Constraints

Speed trajectories considerably influence vehicular fuel consumption, particularly on signalized roads. To minimize fuel consumption, sharp acceleration/deceleration maneuvers and idling events at signalized intersections should be prevented. By taking advantage of the technological developments in infrastructure-to-vehicle communication, the...

Optimisation of Speed Trajectories to Improve the Energy Economy of Electric Vehicles

Electric vehicles are a cleaner and more efficient means of transport. However, the sub-energy-optimal acceleration and deceleration inputs of drivers result in speed trajectories that cause superfluous expenditure of the stored electrical energy in battery. Optimising the speed trajectories to minimise the consumption of stored energy is a...

Online Optimization of Gear Shift and Velocity for Eco-Driving using Adaptive Dynamic Programming

In this paper a learning-based optimization method for online gear shift and velocity control is presented to reduce the fuel consumption and improve the driving comfort in a car-following process. The continuous traction force and the discrete gear shift are optimized jointly to improve both the powertrain operation and the longitudinal...

Multivariate and location-specific correlates of fuel consumption: A test track study

Current predictors of fuel consumption are typically based on computer simulations or data collections in real traffic, where the route and vehicle type are not under the researcher's control. Here, we predicted fuel consumption using test track data, an approach that allowed for location-specific predictions. Ninety-one drivers drove a total...