Abstract
Automated Driving Systems (ADS) have received a considerable amount of attention in the last few decades, as part of the Intelligent Transportation Systems (ITS) field. However, this technology still lacks total automation capacities while keeping driving comfort and safety under risky scenarios, for example, overtaking, obstacle avoidance, or lane changing. Consequently, this work presents a novel method to resolve the obstacle avoidance and overtaking problems named Hybrid Planning. This solution combines the passenger’s comfort associated with the smoothness of Bézier curves and the reliable capacities of Model Predictive Control (MPC) to react against unexpected conditions, such as obstacles on the lane, overtaking and lane-change based maneuvers. A decoupled linear-model was used for the MPC formulation to ensure short computation times. The obstacles and other vehicles’ information are obtained via V2X (vehicle communications). The tests were performed in an automated Renault Twizy vehicle and they have shown good performance under complex scenarios involving static and moving obstacles at a maximum speed of 60 kph.
| Original language | English |
|---|---|
| Article number | 595 |
| Pages (from-to) | 1-19 |
| Number of pages | 19 |
| Journal | Sensors |
| Volume | 21 |
| Issue number | 2 |
| DOIs | |
| Publication status | Published - 2 Jan 2021 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
-
SDG 11 Sustainable Cities and Communities
Keywords
- Automated driving systems
- Cooperative connected autonomous vehicles
- Model predictive control
- Overtaking
- Path planning
- Speed profile
Fingerprint
Dive into the research topics of 'A hybrid planning approach based on MPC and parametric curves for overtaking maneuvers'. Together they form a unique fingerprint.Cite this
- APA
- Author
- BIBTEX
- Harvard
- Standard
- RIS
- Vancouver