| Dynamic Prediction of the Incident Duration Using Adaptive Feature Set B Ghosh, MT Asif, J Dauwels, U Fastenrath, H Guo IEEE Transactions on Intelligent Transportation Systems 20 (11), 4019-4031, 2018 | 18 | 2018 |
| Bayesian prediction of the duration of non-recurring road incidents B Ghosh, MT Asif, J Dauwels 2016 IEEE Region 10 Conference (TENCON), 87-90, 2016 | 16 | 2016 |
| Comparison of different Bayesian methods for estimating error bars with incident duration prediction B Ghosh, J Dauwels Journal of Intelligent Transportation Systems, 1-17, 2021 | 11 | 2021 |
| Predicting the duration of non-recurring road incidents by cluster-specific models B Ghosh, MT Asif, J Dauwels, W Cai, H Guo, U Fastenrath 2016 IEEE 19th International Conference on Intelligent Transportation …, 2016 | 11 | 2016 |
| Effectiveness of VMS Messages in Influencing the Motorists' Travel Behaviour B Ghosh, Y Zhu, J Dauwels 2018 21st International Conference on Intelligent Transportation Systems …, 2018 | 7 | 2018 |
| Intelligent Mobility for Minimizing the Impact of Traffic Incidents on Transportation Networks G Banishree Augmented Intelligence Toward Smart Vehicular Applications, 175-194, 2020 | 4 | 2020 |
| Analysis and prediction of the queue length for non-recurring road incidents B Ghosh, J Dauwels, U Fastenrath 2017 IEEE Symposium Series on Computational Intelligence (SSCI), 1-8, 2017 | 4 | 2017 |
| A Data-Driven Approach to Estimate and Predict the Traffic Incidents' Queue Length B Ghosh, J Dauwels 2023 IEEE 26th International Conference on Intelligent Transportation …, 2023 | | 2023 |
Justin DauwelsDelft University of TechnologyVerified email at tudelft.nl
