• Huang F, Jiang W and Chen S. (2023). A Multitask Attention Network for Food Delivery Time Prediction. Journal of Circuits, Systems and Computers. 10.1142/S0218126624500257. 33:02. Online publication date: 30-Jan-2024.

    https://www.worldscientific.com/doi/10.1142/S0218126624500257

  • Dai Z, Lyu W, Ding Y, Song Y and Liu Y. (2023). OPTI: Order Preparation Time Inference for On-demand Delivery. ACM Transactions on Sensor Networks. 19:4. (1-18). Online publication date: 30-Nov-2023.

    https://doi.org/10.1145/3592610

  • Wang C, Song Y, Fan G, Jin H, Su L, Zhang F and Wang X. Optimizing Cross-Line Dispatching for Minimum Electric Bus Fleet. IEEE Transactions on Mobile Computing. 10.1109/TMC.2021.3119421. 22:4. (2307-2322).

    https://ieeexplore.ieee.org/document/9568702/

  • Shaji H, Vanajakshi L and Tangirala A. (2023). Effects of Data Characteristics on Bus Travel Time Prediction: A Systematic Study. Sustainability. 10.3390/su15064731. 15:6. (4731).

    https://www.mdpi.com/2071-1050/15/6/4731

  • Alkilane K, Alfateh M and Yanming S. (2022). Travel time prediction based on route links’ similarity. Neural Computing and Applications. 10.1007/s00521-022-07926-7. 35:5. (3991-4007). Online publication date: 1-Feb-2023.

    https://link.springer.com/10.1007/s00521-022-07926-7

  • Ye Y, Zhu Y, Markos C and Yu J. CatETA: A Categorical Approximate Approach for Estimating Time of Arrival. IEEE Transactions on Intelligent Transportation Systems. 10.1109/TITS.2022.3207894. 23:12. (24389-24400).

    https://ieeexplore.ieee.org/document/9905416/

  • Zhu Y, Ye Y, Liu Y and Yu J. Cross-Area Travel Time Uncertainty Estimation From Trajectory Data: A Federated Learning Approach. IEEE Transactions on Intelligent Transportation Systems. 10.1109/TITS.2022.3203457. 23:12. (24966-24978).

    https://ieeexplore.ieee.org/document/9894367/

  • Büchel B and Corman F. (2022). What Do We Know When? Modeling Predictability of Transit Operations. IEEE Transactions on Intelligent Transportation Systems. 23:9. (15684-15695). Online publication date: 1-Sep-2022.

    https://doi.org/10.1109/TITS.2022.3145243

  • Bharathi D, Vanajakshi L and Subramanian S. (2022). Spatio-temporal modelling and prediction of bus travel time using a higher-order traffic flow model. Physica A: Statistical Mechanics and its Applications. 10.1016/j.physa.2022.127086. 596. (127086). Online publication date: 1-Jun-2022.

    https://linkinghub.elsevier.com/retrieve/pii/S0378437122001285

  • Sun Y, Fu K, Wang Z, Zhou D, Wu K, Ye J and Zhang C. CoDriver ETA: Combine Driver Information in Estimated Time of Arrival by Driving Style Learning Auxiliary Task. IEEE Transactions on Intelligent Transportation Systems. 10.1109/TITS.2020.3040386. 23:5. (4037-4048).

    https://ieeexplore.ieee.org/document/9288836/

  • Zhong G, Yin T, Li L, Zhang J, Zhang H and Ran B. Bus Travel Time Prediction Based on Ensemble Learning Methods. IEEE Intelligent Transportation Systems Magazine. 10.1109/MITS.2020.2990175. 14:2. (174-189).

    https://ieeexplore.ieee.org/document/9103532/

  • Dai Z, Lyu W, Ding Y and Song Y. (2021). OPTI: Order Preparation Time Inference for On-demand Delivery 2021 IEEE 27th International Conference on Parallel and Distributed Systems (ICPADS). 10.1109/ICPADS53394.2021.00009. 978-1-6654-0878-3. (26-33).

    https://ieeexplore.ieee.org/document/9763755/

  • Fu K, Meng F, Ye J and Wang Z. CompactETA. Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining. (3337-3345).

    https://doi.org/10.1145/3394486.3403386

  • Hashi A, Hashim S, Anwar T and Ahmed A. (2020). A Robust Hybrid Model Based on Kalman-SVM for Bus Arrival Time Prediction. Emerging Trends in Intelligent Computing and Informatics. 10.1007/978-3-030-33582-3_48. (511-519).

    http://link.springer.com/10.1007/978-3-030-33582-3_48

  • He P, Jiang G, Lam S and Tang D. Travel-Time Prediction of Bus Journey With Multiple Bus Trips. IEEE Transactions on Intelligent Transportation Systems. 10.1109/TITS.2018.2883342. 20:11. (4192-4205).

    https://ieeexplore.ieee.org/document/8568988/

  • He P, Sun Y, Jiang G and Lam S. (2019). Predicting Travel Time of Bus Journeys with Alternative Bus Services 2019 International Conference on Data Mining Workshops (ICDMW). 10.1109/ICDMW.2019.00027. 978-1-7281-4896-0. (114-123).

    https://ieeexplore.ieee.org/document/8955512/

  • Zhang X and Liu Z. (2019). Prediction of Bus Arrival Time based on GPS Data: Taking No. 6 Bus in Huangdao District of Qingdao City as an Example 2019 Chinese Control Conference (CCC). 10.23919/ChiCC.2019.8866558. 978-9-8815-6397-2. (8789-8794).

    https://ieeexplore.ieee.org/document/8866558/

  • Cristóbal T, Padrón G, Quesada-Arencibia A, Alayón F, de Blasio G and García C. (2019). Bus Travel Time Prediction Model Based on Profile Similarity. Sensors. 10.3390/s19132869. 19:13. (2869).

    https://www.mdpi.com/1424-8220/19/13/2869

  • R J, Kumar B, Arkatkar S and Vanajakshi L. (2018). Performance Comparison of Bus Travel Time Prediction Models across Indian Cities. Transportation Research Record: Journal of the Transportation Research Board. 10.1177/0361198118770175. 2672:31. (87-98). Online publication date: 1-Dec-2018.

    https://journals.sagepub.com/doi/10.1177/0361198118770175

  • Wang Z, Fu K and Ye J. Learning to Estimate the Travel Time. Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining. (858-866).

    https://doi.org/10.1145/3219819.3219900

  • Cristobal T, Padron G, Quesada-Arencibia A, Alayon F and Garcia C. Systematic Approach to Analyze Travel Time in Road-Based Mass Transit Systems Based on Data Mining. IEEE Access. 10.1109/ACCESS.2018.2837498. 6. (32861-32873).

    https://ieeexplore.ieee.org/document/8360420/

  • Behera R, Kumar B and Vanajakshi L. (2017). Real Time Identification of Inputs for a BATP System Using Data Analytics. International Journal of Civil Engineering. 10.1007/s40999-017-0210-y. 15:8. (1173-1185). Online publication date: 1-Dec-2017.

    http://link.springer.com/10.1007/s40999-017-0210-y

  • Lee D, Ziolo P, Han W and Powell W. (2017). Optimal online learning in bidding for sponsored search auctions 2017 IEEE Symposium Series on Computational Intelligence (SSCI). 10.1109/SSCI.2017.8285393. 978-1-5386-2726-6. (1-8).

    http://ieeexplore.ieee.org/document/8285393/

  • Lee K, Prokhorchuk A, Dauwels J and Jaillet P. (2017). Estimation of travel time from taxi GPS data 2017 IEEE Symposium Series on Computational Intelligence (SSCI). 10.1109/SSCI.2017.8280963. 978-1-5386-2726-6. (1-6).

    http://ieeexplore.ieee.org/document/8280963/

  • Kumar B, Vanajakshi L and Subramanian S. (2017). Pattern-Based Time-Discretized Method for Bus Travel Time Prediction. Journal of Transportation Engineering, Part A: Systems. 10.1061/JTEPBS.0000029. 143:6. Online publication date: 1-Jun-2017.

    https://ascelibrary.org/doi/10.1061/JTEPBS.0000029

  • Zhu L, Xu C, Guan J and Zhang H. (2017). SEM-PPA. Journal of Network and Computer Applications. 82:C. (35-46). Online publication date: 15-Mar-2017.

    https://doi.org/10.1016/j.jnca.2016.12.033

  • Fadaei M, Cats O and Bhaskar A. (2017). A hybrid scheme for real‐time prediction of bus trajectories. Journal of Advanced Transportation. 10.1002/atr.1450. 50:8. (2130-2149). Online publication date: 1-Dec-2016.

    https://onlinelibrary.wiley.com/doi/10.1002/atr.1450

  • Weng J, Wang C, Huang H, Wang Y and Zhang L. (2016). Real-time bus travel speed estimation model based on bus GPS data. Advances in Mechanical Engineering. 10.1177/1687814016678162. 8:11. (168781401667816). Online publication date: 1-Nov-2016.

    http://journals.sagepub.com/doi/10.1177/1687814016678162

  • He Z, Huang J, Du Y, Wang B and Yu H. (2016). The prediction of passenger flow distribution for urban rail transit based on multi-factor model 2016 IEEE International Conference on Intelligent Transportation Engineering (ICITE). 10.1109/ICITE.2016.7581320. 978-1-4673-9048-4. (128-132).

    http://ieeexplore.ieee.org/document/7581320/

  • Dhivyabharathi B, Kumar B and Vanajakshi L. (2016). Real time bus arrival time prediction system under Indian traffic condition 2016 IEEE International Conference on Intelligent Transportation Engineering (ICITE). 10.1109/ICITE.2016.7581300. 978-1-4673-9048-4. (18-22).

    http://ieeexplore.ieee.org/document/7581300/

  • Moreira-Matias L, Mendes-Moreira J, de Sousa J and Gama J. Improving Mass Transit Operations by Using AVL-Based Systems: A Survey. IEEE Transactions on Intelligent Transportation Systems. 10.1109/TITS.2014.2376772. 16:4. (1636-1653).

    http://ieeexplore.ieee.org/document/7017506/

  • Zhiying He , Wang B, Jianling Huang and Yong Du . (2014). Station passenger flow forecast for urban rail transit based on station attributes 2014 IEEE 3rd International Conference on Cloud Computing and Intelligence Systems (CCIS). 10.1109/CCIS.2014.7175770. 978-1-4799-4720-1. (410-414).

    http://ieeexplore.ieee.org/document/7175770/

  • Kumar B, Vanjakshi L and Subramanian S. (2013). Day-wise Travel Time Pattern Analysis Under Heterogeneous Traffic Conditions. Procedia - Social and Behavioral Sciences. 10.1016/j.sbspro.2013.11.169. 104. (746-754). Online publication date: 1-Dec-2013.

    https://linkinghub.elsevier.com/retrieve/pii/S1877042813045606

  • Zhiying He , Haitao Yu , Yong Du and Wang J. (2013). SVM based multi-index evaluation for bus arrival time prediction 2013 International Conference on ICT Convergence (ICTC). 10.1109/ICTC.2013.6675313. 978-1-4799-0698-7. (86-90).

    http://ieeexplore.ieee.org/document/6675313/