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 language | English |
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Pages | 5818-5823 |
Number of pages | 6 |
DOIs | |
Publication status | Published - 2023 |
Event | 26th IEEE International Conference on Intelligent Transportation Systems, ITSC 2023 - Euskalduna Conference Centre, Bilbao, Spain Duration: 24 Sept 2023 → 28 Sept 2023 https://2023.ieee-itsc.org/ |
Conference
Conference | 26th IEEE International Conference on Intelligent Transportation Systems, ITSC 2023 |
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Abbreviated title | IEEE ITSC 2023 |
Country/Territory | Spain |
City | Bilbao |
Period | 24/09/23 → 28/09/23 |
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-careOtherwise 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
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Large Car-following Dataset Based on Lyft level-5: Following Autonomous Vehicles vs. Human-driven Vehicles
Li, G. (Creator), Jiao, Y. (Creator), Knoop, V. L. (Creator), Calvert, S. C. (Creator) & van Lint, J. W. C. (Creator), TU Delft - 4TU.ResearchData, 31 May 2023
DOI: 10.4121/1255994C-C64F-40F5-8121-9E952E308C9A
Dataset/Software: Dataset