Skip to content

A l_1 norm minimization based least-smoothing approach for reconstructing longitudinal trajectories of individual vehicles

Notifications You must be signed in to change notification settings

ximeng96/Two-step-quadratic-programming-for-physically-meaningful-smoothing-of-longitudinal-vehicle-trajector

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

41 Commits
 
 
 
 
 
 
 
 

Repository files navigation

Two-step quadratic programming for physically meaningful smoothing of longitudinal vehicle trajectory

Package requirements

Packages required for codes

  • Pandas
  • Numpy
  • Cvxpy
  • Gurobi
  • Matplotlib
  • Seaborn

Packages required for showing slides version

  • RISE

The codes for replicating the numerical applications in the paper are provided in the folder 'codes'.

Input NGSIM data are accessible in the folder 'datasets', and highD datasets can be accessed at https://www.highd-dataset.com/ upon request.

About

A l_1 norm minimization based least-smoothing approach for reconstructing longitudinal trajectories of individual vehicles

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published