Longitudinal trajectory estimation for lane change assist

​A comparison of model predictive control and curve interpolation using smoothing splines in convex optimization

Presented by Dandan Ge and Anders Hjelmström Sarvik, MPSYS


In this thesis, two algorithms to generate a longitudinal trajectory suitable for a lane change during highway driving are developed and evaluated. One of the algorithms uses the Model predictive control framework to minimize the acceleration and deviation from the desired position while fulfilling physical and design constraints. The other algorithm uses optimal interpolating B-splines to generate a velocity profile. Both methods work in a receding horizon context which solves an optimization problem in each time instant. It is shown in simulations that both algorithms successfully generates trajectories suitable for a lane change.

Examiner: Jonas Fredriksson

Category Student project presentation
Location: Landahlsrummet (room 7430), Hörsalsvägen 11, 7th floor
Starts: 14 June, 2018, 09:00
Ends: 14 June, 2018, 10:00

Published: Mon 04 Jun 2018.