| Multistep traffic forecasting by dynamic graph convolution: Interpretations of real-time spatial correlations G Li, VL Knoop, H Van Lint Transportation Research Part C: Emerging Technologies 128, 103185, 2021 | 89 | 2021 |
| Large Car-following Data Based on Lyft level-5 Open Dataset: Following Autonomous Vehicles vs. Human-driven Vehicles G Li, Y Jiao, VL Knoop, SC Calvert, JWC van Lint 2023 IEEE 26th International Conference on Intelligent Transportation …, 2023 | 52 | 2023 |
| Continual driver behaviour learning for connected vehicles and intelligent transportation systems: Framework, survey and challenges Z Li, C Gong, Y Lin, G Li, X Wang, C Lu, M Wang, S Chen, J Gong Green Energy and Intelligent Transportation 2 (4), 100103, 2023 | 44 | 2023 |
| Unravelling uncertainty in trajectory prediction using a non-parametric approach G Li, Z Li, VL Knoop, H van Lint Transportation Research Part C: Emerging Technologies 163, 104659, 2024 | 40* | 2024 |
| Estimate the limit of predictability in short-term traffic forecasting: An entropy-based approach G Li, VL Knoop, H van Lint Transportation Research Part C: Emerging Technologies 138, 103607, 2022 | 29 | 2022 |
| How predictable are macroscopic traffic states: a perspective of uncertainty quantification G Li, VL Knoop, H Van Lint Transportmetrica B: transport dynamics 12 (1), 2314766, 2024 | 14 | 2024 |
| Lateral conflict resolution data derived from Argoverse-2: analysing safety and efficiency impacts of autonomous vehicles at intersections G Li, Y Jiao, SC Calvert, JWCH van Lint Transportation Research Part C: Emerging Technologies 167, 104802, 2024 | 14* | 2024 |
| Beyond behavioural change: Investigating alternative explanations for shorter time headways when human drivers follow automated vehicles Y Jiao, G Li, SC Calvert, S van Cranenburgh, H van Lint Transportation Research Part C: Emerging Technologies 164 (104673), 2024 | 14 | 2024 |
| How far ahead should autonomous vehicles start resolving predicted conflicts? Exploring uncertainty-based safety-efficiency trade-off G Li, Z Li, VL Knoop, JWC van Lint IEEE Transactions on Intelligent Transportation Systems 25 (10), 14183-14195, 2024 | 8 | 2024 |
| Dynamic graph filters networks: A gray-box model for multistep traffic forecasting LI Guopeng, VL Knoop, H van Lint 2020 IEEE 23rd international conference on intelligent transportation …, 2020 | 8 | 2020 |
| Analysis of stochasticity and heterogeneity of car-following behavior based on data-driven modeling Y Shiomi, G Li, VL Knoop Transportation research record 2677 (12), 604-619, 2023 | 7 | 2023 |
| Interpretable Representation and Customizable Retrieval of Traffic Congestion Patterns Using Causal Graph-Based Feature Associations TT Nguyen, SC Calvert, G Li, H van Lint Data Science for Transportation 6 (3), 18, 2024 | 1 | 2024 |
| Distil the informative essence of loop detector data set: Is network-level traffic forecasting hungry for more data? G Li, VL Knoop, H van Lint Transportation Research Board 103rd Annual Meeting Transportation Research Board, 2023 | 1 | 2023 |
| Pattern retrieval of traffic congestion using graph-based associations of traffic domain-specific features TT Nguyen, SC Calvert, G Li, H van Lint arXiv preprint arXiv:2311.17256, 2023 | | 2023 |
| A Conflict Resolution Dataset Derived from Argoverse-2: Analysis of the Safety and Efficiency Impacts of Autonomous Vehicles at Intersections G Li, Y Jiao, SC Calvert, JWC van Lint arXiv preprint arXiv:2308.13839, 2023 | | 2023 |
| Uncertainty Quantification and Predictability Analysis for Traffic Forecasting at Multiple Scales G Li | | 2023 |
Victor L. Knoopassociate professor Delft University of TechnologyVerified email at tudelft.nl
