Gharavi, Leila (2023): Proactive Motion Planning Codes for Emergency Collision Avoidance in Highway Scenarios. Version 1. 4TU.ResearchData. software. https://doi.org/10.4121/c4c3015e-702a-43dc-9eed-33b9d207604e.v1

Software

x choose version: version 2 - 2025-01-30 (latest)

• Mechanical Engineering
• Other Engineering
• Applied Mathematics
• Interdisciplinary Engineering
• Ground Transport
• Automotive Engineering
• Other Technology
• Engineering
• Transport
• Mathematical Sciences
• Technology

Automated Driving, Collision Avoidance, Emergency Scenarios, Evasive Maneuvers, Model Predictive Control, Motion Planning, Proactive Control, Stochastic Model Predictive Control

MIT

RefWorks, BibTeX, Reference Manager, Endnote, DataCite, NLM, DC, CFF

by Leila Gharavi

This repository includes local motion planners for emergency collision avoidance in automated driving systems. These planners incorporate stochastic prediction models for other road users (e.g. vehicles or static obstacles) and a dynamic prediction model for the ego vehicle. Further, the planners are formulated as model predictive control optimization problems and are designed to find a reference trajectory for the ego vehicle to avoid collision with the road users/obstacles and road boundaries while taking into account the uncertainty in predicting the behavior of other road users.

• 2023-09-21 first online, published, posted

4TU.ResearchData

ZIP file including MATLAB codes

• Control of Evasive Manoeuvres for Automated Driving: Solving the Edge Cases (EVOLVE) (grant code 18484) NWO Open Technology Programme

Delft University of Technology, Faculty Mechanical, Maritime and Materials Engineering (3ME), Delft Center for Systems and Control