Research graph
References from Multi-stage temporal inference and adaptive windowing for automatic lane-change onset labeling from trajectory data. Local targets link to admitted publications; unresolved targets remain external evidence.
Predicting and explaining lane-changing behaviour using machine learning: a comparative study
10.1016/j.trc.2022.103931 · 2022 · External reference
Calibrating lane-changing models: two data-related issues and a general method to extract appropriate data
10.1016/j.trc.2023.104182 · 2023 · External reference
Detecting, analysing, and modelling failed lane-changing attempts in traditional and connected environments
2020 · External reference
CLACD: a complete lane-changing decision modeling framework for the connected and traditional environments
10.1016/j.trc.2021.103162 · 2021 · External reference
On the new era of urban traffic monitoring with massive drone data: the pNEUMA large-scale field experiment
10.1016/j.trc.2019.11.023 · 2020 · External reference
An integrated method based on wavelet modulus maxima and local hölder exponents for automatic phase detection and labelling of lane-changing execution
10.1016/j.trc.2025.105285 · 2025 · External reference
MITRA: a drone-based trajectory data for an all-traffic-state inclusive freeway with ramps
10.1038/s41597-025-05472-0 · 2025 · External reference
Evaluating the safety and efficiency impacts of forced lane change with negative gaps based on empirical vehicle trajectories
10.1016/j.aap.2024.107622 · 2024 · External reference
Analyzing differences of highway lane-changing behavior using vehicle trajectory data
10.1016/j.physa.2023.128980 · 2023 · External reference
Key feature selection and risk prediction for lane-changing behaviors based on vehicles’ trajectory data
10.1016/j.aap.2019.05.017 · 2019 · External reference
A critical evaluation of the next generation simulation (NGSIM) vehicle trajectory dataset
10.1016/j.trb.2017.09.018 · 2017 · External reference
Unresolved reference
External reference
Multi-modal trajectory prediction of surrounding vehicles with maneuver-based LSTMs
2018 · External reference
Processing, assessing, and enhancing the waymo autonomous vehicle open dataset for driving behavior research
10.1016/j.trc.2021.103490 · 2022 · External reference
The highd dataset: a drone dataset of naturalistic vehicle trajectories on german highways for validation of highly automated driving systems
2018 · External reference
Quantifying risks of lane-changing behavior in highways with vehicle trajectory data under different driving environments
10.1142/s0129183124501419 · 2024 · External reference
Trajectory data-based traffic flow studies: a revisit
10.1016/j.trc.2020.02.016 · 2020 · External reference
An approach for accurately extracting vehicle trajectory from aerial videos based on computer vision
10.1016/j.measurement.2024.116212 · 2025 · External reference
B-spline curve fitting based on adaptive curve refinement using dominant points
10.1016/j.cad.2006.12.006 · 2007 · External reference
Learning vehicle surrounding-aware lane-changing behavior from observed trajectories
2018 · External reference
Modeling duration of lane changes
10.3141/1999-08 · 2007 · External reference
Investigation of discretionary lane-change characteristics using next-generation simulation data sets
10.1080/15472450.2013.810994 · 2014 · External reference
Analysis of discretionary lane-changing behaviours of autonomous vehicles based on real-world data
2025 · External reference
CQSkyEyeX: a drone dataset of vehicle trajectory on chinese expressways
2024 · External reference
Examining lane change gap acceptance, duration and impact using naturalistic driving data
10.1016/j.trc.2019.05.024 · 2019 · External reference
Accurate detection and tracking of small-scale vehicles in high-altitude unmanned aerial vehicle bird-view imagery
2023 · External reference
A novel learning framework for sampling-based motion planning in autonomous driving
2020 · External reference
Recent developments and research needs in modeling lane changing
10.1016/j.trb.2013.11.009 · 2014 · External reference
Applications of wavelet transform for analysis of freeway traffic
10.1016/j.trb.2010.08.002 · 2011 · External reference
On selecting an optimal wavelet for detecting singularities in traffic and vehicular data
10.1016/j.trc.2012.03.006 · 2012 · External reference
Key feature selection and risk prediction for lane-changing behaviors based on vehicles’ trajectory data
10.1016/j.aap.2019.05.017 · ExternalCitation · doi-reference
Evaluating the safety and efficiency impacts of forced lane change with negative gaps based on empirical vehicle trajectories
10.1016/j.aap.2024.107622 · ExternalCitation · doi-reference
B-spline curve fitting based on adaptive curve refinement using dominant points
10.1016/j.cad.2006.12.006 · ExternalCitation · doi-reference
An approach for accurately extracting vehicle trajectory from aerial videos based on computer vision
10.1016/j.measurement.2024.116212 · ExternalCitation · doi-reference
Analyzing differences of highway lane-changing behavior using vehicle trajectory data
10.1016/j.physa.2023.128980 · ExternalCitation · doi-reference
Applications of wavelet transform for analysis of freeway traffic
10.1016/j.trb.2010.08.002 · ExternalCitation · doi-reference
Recent developments and research needs in modeling lane changing
10.1016/j.trb.2013.11.009 · ExternalCitation · doi-reference
A critical evaluation of the next generation simulation (NGSIM) vehicle trajectory dataset
10.1016/j.trb.2017.09.018 · ExternalCitation · doi-reference
On selecting an optimal wavelet for detecting singularities in traffic and vehicular data
10.1016/j.trc.2012.03.006 · ExternalCitation · doi-reference
Examining lane change gap acceptance, duration and impact using naturalistic driving data
10.1016/j.trc.2019.05.024 · ExternalCitation · doi-reference
On the new era of urban traffic monitoring with massive drone data: the pNEUMA large-scale field experiment
10.1016/j.trc.2019.11.023 · ExternalCitation · doi-reference
Trajectory data-based traffic flow studies: a revisit
10.1016/j.trc.2020.02.016 · ExternalCitation · doi-reference
CLACD: a complete lane-changing decision modeling framework for the connected and traditional environments
10.1016/j.trc.2021.103162 · ExternalCitation · doi-reference
Processing, assessing, and enhancing the waymo autonomous vehicle open dataset for driving behavior research
10.1016/j.trc.2021.103490 · ExternalCitation · doi-reference
Predicting and explaining lane-changing behaviour using machine learning: a comparative study
10.1016/j.trc.2022.103931 · ExternalCitation · doi-reference
Calibrating lane-changing models: two data-related issues and a general method to extract appropriate data
10.1016/j.trc.2023.104182 · ExternalCitation · doi-reference
An integrated method based on wavelet modulus maxima and local hölder exponents for automatic phase detection and labelling of lane-changing execution
10.1016/j.trc.2025.105285 · ExternalCitation · doi-reference
MITRA: a drone-based trajectory data for an all-traffic-state inclusive freeway with ramps
10.1038/s41597-025-05472-0 · ExternalCitation · doi-reference
Investigation of discretionary lane-change characteristics using next-generation simulation data sets
10.1080/15472450.2013.810994 · ExternalCitation · doi-reference
Quantifying risks of lane-changing behavior in highways with vehicle trajectory data under different driving environments
10.1142/s0129183124501419 · ExternalCitation · doi-reference
Modeling duration of lane changes
10.3141/1999-08 · ExternalCitation · doi-reference
