Large Car-following Data Based on Lyft level-5 Open Dataset: Following Autonomous Vehicles vs. Human-driven Vehicles

Guopeng Li*, Yiru Jiao, Victor L. Knoop, Simeon C. Calvert, J.W.C. van Lint

*Corresponding author for this work

Research output: Contribution to conferencePaperpeer-review

45 Downloads (Pure)

Abstract

Car-Following (CF), as a fundamental driving behaviour, has significant influences on the safety and efficiency of traffic flow. Investigating how human drivers react differently when following autonomous vs. human-driven vehicles (HV) is thus critical for mixed traffic flow. Research in this field can be expedited with trajectory datasets collected by Autonomous Vehicles (AVs). However, trajectories collected by AVs are noisy and not readily applicable for studying CF behaviour. This paper extracts and enhances two categories of CF data, HV-following-AV (H-A) and HV-following-HV (H-H), from the open Lyft level-5 dataset. First, CF pairs are selected based on specific rules. Next, the quality of raw data is assessed by anomaly analysis. Then, the raw CF data is corrected and enhanced via motion planning, Kalman filtering, and wavelet denoising. As a result, 29k+ H-A and 42k+ H-H car-following segments are obtained, with a total driving distance of 150k+ km. A diversity assessment shows that the processed data cover complete CF regimes for calibrating CF models. This open and ready-to-use dataset provides the opportunity to investigate the CF behaviours of following AVs vs. HVs from real-world data. It can further facilitate studies on exploring the impact of AVs on mixed urban traffic.
Original languageEnglish
Pages5818-5823
Number of pages6
DOIs
Publication statusPublished - 2023
Event26th IEEE International Conference on Intelligent Transportation Systems, ITSC 2023 - Euskalduna Conference Centre, Bilbao, Spain
Duration: 24 Sept 202328 Sept 2023
https://2023.ieee-itsc.org/

Conference

Conference26th IEEE International Conference on Intelligent Transportation Systems, ITSC 2023
Abbreviated titleIEEE ITSC 2023
Country/TerritorySpain
CityBilbao
Period24/09/2328/09/23
Internet address

Bibliographical note

Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care
Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.

Keywords

  • Car-following
  • trajectory dataset
  • autonomous vehicle
  • driving behaviour

Fingerprint

Dive into the research topics of 'Large Car-following Data Based on Lyft level-5 Open Dataset: Following Autonomous Vehicles vs. Human-driven Vehicles'. Together they form a unique fingerprint.

Cite this