Comparison of two simulation approaches to safety assessment : cellular automata and SSAM by Chai, Chen, Wong, Yiik Diew

Subjects: “…Traffic Safety…”
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Trustworthy autonomous driving via defense-aware robust reinforcement learning against worst-case observational perturbations by He, Xiangkun, Huang, Wenhui, Lv, Chen

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A CNN-LSTM-attention model for near-crash event identification on mountainous roads by Zhao, Jing, Yang, Wenchen, Zhu, Feng

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Relationship between highway geometric characteristics and accident risk: a multilayer perceptron model (MLP) approach by Yan, Jie, Zeng, Sheng, Tian, Bijiang, Cao, Yuanwen, Yang, Wenchen, Zhu, Feng

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Driver Behavior in Intelligent Transportation Systems [Guest Editorial] by Li, Guofa, Olaverri-Monreal, Cristina, Qu, Xiaobo, Wu, Sean Changxu, Li, Eben Shengbo, Taghavifar, Hamid, Xing, Yang, Li, Shen

“…To make future ITSs trustworthy for traffic safety and acceptable for travel efficiency, developing industrial ITS applications based on drivers’ reliable behavioral and cognitive intelligence is essential. …”
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A GIS-CA model for planning bikeways upon the footpath network by Zhao, Xu, Zhang, Jie, Zhang, Ning, Wong, Yiik Diew, Zhou, Yufang, Meng, Meng

“…The host value of each CA cell is conditioned upon four indicator variables, namely cycling demand level, land-use nature, social value, and traffic safety. This model gives traffic planners a quick and intuitive framework to develop cycling facilities under limited land resources. …”
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A privacy-preserving and cross-domain group authentication scheme for vehicular in LTE-A networks by Xu, Cheng, Huang, Xiaohong, Ma, Maode, Bao, Hong

“…In order to improve road traffic safety, reduce congestion, improving driving experience, intelligent transportation systems and vehicular networking concepts arises at the historic moment. …”
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Conflict-free four-dimensional path planning for urban air mobility considering airspace occupancy by Dai, Wei, Pang, Bizhao, Low, Kin Huat

“…Preventing the conflict among urban aircraft is crucial to UAM traffic safety, which is a key in enabling large scale UAM operation. …”
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Unsupervised hierarchical methodology of maritime traffic pattern extraction for knowledge discovery by Li, Huanhuan, Lam, Jasmine Siu Lee, Yang, Zaili, Liu, Jingxian, Liu, Ryan Wen, Liang, Maohan, Li, Yan

“…Owing to the space–air–ground integrated networks (SAGIN), seaborne shipping has attracted increasing interest in the research on the motion behavior knowledge extraction and navigation pattern mining problems in the era of maritime big data for improving maritime traffic safety management. This study aims to develop a novel unsupervised methodology for feature extraction and knowledge discovery based on automatic identification system (AIS) data, allowing for seamless knowledge transfer to support trajectory data mining. …”
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Cellular V2X communications in the presence of big vehicle shadowing: performance analysis and mitigation by Nguyen, Hieu T., Md. Noor-A-Rahim, Guan, Yong Liang, Pesch, Dirk

“…In Intelligent Transportation Systems (ITS), vehicular networks are enabling technologies for onboard data services such as traffic safety, user infotainment, etc. Vehicular networks face many challenges when it comes to providing satisfactory quality of service, mainly because of issues that arise from unreliable communication in unfavorable propagation conditions. …”
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Intention prediction-based control for vehicle platoon to handle driver cut-In by Yun, Lu, Huang, Lingying, Yao, Jiarong, Su, Rong

“…In this paper, to handle such cut-ins, we propose an intention prediction-based control method for the VPs by considering the tradeoff between the platoon integrity and traffic safety. Particularly, the proposed method is designed to prevent as many cut-ins as possible while taking care of the road safety. …”
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Comparing resampling algorithms and classifiers for modeling traffic risk prediction by Wang, Bo, Zhang, Chi, Wong, Yiik Diew, Hou, Lei, Zhang, Min, Xiang, Yujie

“…Road infrastructure has significant effects on road traffic safety and needs further examination. In terms of traffic crash prediction, recent studies have started to develop deep learning classification algorithms. …”
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Eco-driving strategy for connected automated vehicles in mixed traffic flow by Liu, Hongjie, Yuan, Tengfei, Zeng, Xiaoqing, Guo, Kaiyi, Wang, Yizeng, Mo, Yanghui, Xu, Hongzhe

“…This coexistence poses a range of challenges, not limited to traffic safety, efficiency, and environmental sustainability. …”
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Exploring the impact of rainfall on vehicle trajectory patterns and sideslip risk: an empirical investigation by Wang, Bo, Wong, Yiik Diew, Zhang, Chi, Zhang, Hong, Gao, Yanyang

“…This study provides an effective approach for monitoring and analyzing the sideslip risk on curved segments, thereby contributing to the enhancement of road design and traffic safety management.…”
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A fine-grained ship-radiated noise recognition system using deep hybrid neural networks with multi-scale features by Liu, Shuai, Fu, Xiaomei, Xu, Hong, Zhang, Jiali, Zhang, Anmin, Zhou, Qingji, Zhang, Hao

“…Fine-grained ship-radiated noise recognition methods of different specific ships are in demand for maritime traffic safety and general security. Due to the high background noise and complex transmission channels in the marine environment, the accurate identification of ship radiation noise becomes quite complicated. …”
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