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Publications & Datasets

ROADVIEW publications and conference proceedings

2025

Chan, P. H., Wei, C., Huggett, A., & Donzella, V. (2025). Raw camera data object detectors: an optimisation for automotive video processing and transmission. IEEE Access. https://doi.org/10.1109/ACCESS.2025.3529287
 
Baris, G., Li, B., Chan, P. H., Avizzano, C. A., & Donzella, V. (2025). Automotive DNN based object detection in the presence of lens obstruction and video compression. IEEE Access. https://doi.org/10.1109/ACCESS.2025.3544773
 
Chan, P. H., Roudposhti, S. S., Ye, X., & Donzella, V. (2025). A noise analysis of 4d radar: robust sensing for automotive?. IEEE Sensors Journal. https://doi.org/10.1109/JSEN.2025.3556518
 
Donzella, V., Chan, P. H., Gummadi, D., Raisuddin, A. M., & Aksoy, E. E. (2025). LiDAR De-Snow Score (DSS): combining quality and perception metrics for optimised de-noising. IEEE Sensors Journal. https://doi.org/10.1109/JSEN.2025.3570478
 
Alshaikh, M. (2025). An Experimental Study on ObjectTracking. https://www.diva-portal.org/smash/record.jsf?pid=diva2%3A1966144&dswid=-6376 
 
Maanpää, J., Pesonen, J., Melekhov, I., Hyyti, H., & Hyyppä, J. (2025, June). Road Grip Uncertainty Estimation Through Surface State Segmentation. In Scandinavian Conference on Image Analysis (pp. 231-244). Cham: Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-95911-0_17
 
Raisuddin, A. M., Gouigah, I., & Aksoy, E. E. (2024). 3d-unoutdet: A fast and efficient unsupervised snow removal algorithm for 3d lidar point clouds. Authorea Preprints. https://doi.org/10.36227/techrxiv.172865969.94242670/v1
 
Rolich, A., Yildiz, M., Turcanu, I., Vinel, A., & Baiocchi, A. (2025, June). On the Trade-off Between AoI Performance and Resource Reuse Efficiency in 5G NR V2X Sidelink. In 2025 IEEE Vehicular Networking Conference (VNC) (pp. 1-8). IEEE. https://doi.org/10.1109/VNC64509.2025.11054234
 
 

2024

Silva, L. C. D., Drechsler, M. F., Poledna, Y., Huber, W., & Fiorentin, T. A. (2023, November). Synthetic extreme weather for ai training: Concept and validation. In 2023 Third International Conference on Digital Data Processing (DDP) (pp. 188-194). IEEE. https://doi.org/10.1109/DDP60485.2023.00044
 
Chan, P. H., Debattista, K., & Donzella, V. (2024, October). Parametric physics-based snow model for automotive cameras. In 2024 IEEE SENSORS (pp. 01-04). IEEE. https://doi.org/10.1109/SENSORS60989.2024.10784836
 
Drechsler, M. F., Poledna, Y., Hjort, M., Kharrazi, S., & Huber, W. (2024, October). Vehicle Dynamics Parameter Estimation Methodology for Virtual Automated Driving Testing. In 2024 IEEE International Automated Vehicle Validation Conference (IAVVC) (pp. 1-7). IEEE. https://doi.org/10.1109/IAVVC63304.2024.10786416
 
Maanpää, J., Pesonen, J., Hyyti, H., Melekhov, I., Kannala, J., Manninen, P., … & Hyyppä, J. (2024, December). Dense road surface grip map prediction from multimodal image data. In International Conference on Pattern Recognition (pp. 387-404). Cham: Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-78447-7_26
 
Herranen, T., Martí, E. H., Chan, P. H., Poledna, Y., Duthon, P., Ben-Daoued, A., … & Donzella, V. (2024, November). Creation of digital models for accelerated and reliable testing of automated systems in adverse weather. In Autonomous Systems for Security and Defence (Vol. 13207, pp. 41-54). SPIE. https://doi.org/10.1117/12.3031473
 
Cortinhal, T., Gouigah, I., & Aksoy, E. E. (2024, June). Semantics-aware LiDAR-only pseudo point cloud generation for 3D object detection. In 2024 IEEE Intelligent Vehicles Symposium (IV) (pp. 3220-3226). IEEE. https://doi.org/10.1109/IV55156.2024.10588782
 
Poledna, Y., Drechsler, M. F., Donzella, V., Chan, P. H., Duthon, P., & Huber, W. (2024, June). REHEARSE: adverse weather dataset for sensory noise models. In 2024 IEEE Intelligent Vehicles Symposium (IV) (pp. 2451-2457). IEEE. https://doi.org/10.1109/IV55156.2024.10588491
 
Raisuddin, A. M., Cortinhal, T., Holmblad, J., & Aksoy, E. E. (2024, June). 3d-outdet: A fast and memory efficient outlier detector for 3d lidar point clouds in adverse weather. In 2024 IEEE Intelligent Vehicles Symposium (IV) (pp. 2862-2868). IEEE. https://doi.org/10.1109/IV55156.2024.10588582
 
Wang, Y., Zhao, H., Debattista, K., & Donzella, V. (2023, September). The effect of camera data degradation factors on panoptic segmentation for automated driving. In 2023 IEEE 26th International Conference on Intelligent Transportation Systems (ITSC) (pp. 2351-2356). IEEE. https://doi.org/10.1109/ITSC57777.2023.10421803
 
Silva, L. C. D., Drechsler, M. F., Poledna, Y., Huber, W., & Fiorentin, T. A. (2023, November). Synthetic extreme weather for ai training: Concept and validation. In 2023 Third International Conference on Digital Data Processing (DDP) (pp. 188-194). IEEE. https://doi.org/10.1109/DDP60485.2023.00044 
 
Chan, P. H., Li, B., Baris, G., Sadiq, Q., & Donzella, V. (2024). The inconvenient truth of ground truth errors in automotive datasets and DNN-based detection. Data-Centric Engineering, 5, e34. https://doi.org/10.1017/dce.2024.39
 
Warg, F., Donzella, V., Chan, P. H., Robinson, J., Poledna, Y., Liandrat, S., … & Aksoy, E. E. (2024). From operational design domain to test cases: A methodology to include harsh weather. Open Research Europe, 4(238), 238. https://doi.org/10.12688/openreseurope.18592.1
 
Shahbeigi, S., Robinson, J., & Donzella, V. (2024). A novel score-based lidar point cloud degradation analysis method. IEEE Access, 12, 22671-22686. https://doi.org/10.1109/ACCESS.2024.3359300
 
Cortinhal, T. (2024). Semantics-aware Multi-modal Scene Perception for Autonomous Vehicles (Doctoral dissertation, Halmstad University Press). https://www.diva-portal.org/smash/record.jsf?pid=diva2%3A1849702&dswid=5514

2023

Ben-Daoued, A., Bernardin, F., & Duthon, P. (2024). A Comparative Review of the SWEET Simulator: Theoretical Verification Against Other Simulators. Journal of Imaging, 10(12), 306. https://doi.org/10.3390/jimaging10120306
 
Ben-Daoued, A., Duthon, P., & Bernardin, F. (2023). Sweet: A realistic multiwavelength 3d simulator for automotive perceptive sensors in foggy conditions. Journal of Imaging, 9(2), 54. https://doi.org/10.3390/jimaging9020054
 
Daoued, A. B., Bernardin, F., & Duthon, P. (2023, January). Simulation numérique de capteurs perceptifs du véhicule autonome sous conditions météorologiques dégradées. In ATEC France. https://hal.science/hal-03972734/

ROADVIEW datasets

Poledna, Y., Dreschler, M., Cristófoli Duarte, L., Duthon, P., Bernardin, F., Donzella, V., Chan, P. H. (2024). REHEARSE: adveRse wEatHEr datAset for sensoRy noiSe modEls. RISE. https://s3.ice.ri.se/roadview-WP3-Warwick/T3.2%20-%20Create%20Dataset/rehearse/index.html

Poledna, Y., Dreschler, M., Hjort, M.,  Kharrazi, S. (2024). Vehicle Dynamics. GitHub. https://github.com/roadview-project/vehicle-dynamics 

Poledna, Y., (2024). Dataset Creator OSI. GitHub. https://github.com/roadview-project/dataset_creator_OSI