Zobrazeno 1 - 10
of 329
pro vyhledávání: '"Zheng, Ou"'
Autor:
Suo, Dajiang, Li, Heyi, Bhattacharyya, Rahul, Wang, Zijin, Ding, Shengxuan, Zheng, Ou, Valderas, Daniel, Melià-Seguí, Joan, Abdel-Aty, Mohamed, Sarma, Sanjay E.
The EPC GEN 2 communication protocol for Ultra-high frequency Radio Frequency Identification (RFID) has offered a promising avenue for advancing the intelligence of transportation infrastructure. With the capability of linking vehicles to RFID reader
Externí odkaz:
http://arxiv.org/abs/2311.00280
Publikováno v:
IEEE Transactions on Intelligent Vehicles
Accurate Vehicle Trajectory Prediction is critical for automated vehicles and advanced driver assistance systems. Vehicle trajectory prediction consists of two essential tasks, i.e., longitudinal position prediction and lateral position prediction. T
Externí odkaz:
http://arxiv.org/abs/2308.00533
Large Language Models (LLMs) have shown remarkable effectiveness in various general-domain natural language processing (NLP) tasks. However, their performance in transportation safety domain tasks has been suboptimal, primarily attributed to the requ
Externí odkaz:
http://arxiv.org/abs/2307.15311
Accurately detecting and predicting lane change (LC)processes of human-driven vehicles can help autonomous vehicles better understand their surrounding environment, recognize potential safety hazards, and improve traffic safety. This paper focuses on
Externí odkaz:
http://arxiv.org/abs/2304.13732
Autor:
Ding, Shengxuan, Abdel-Aty, Mohamed, Barbour, Natalia, Wang, Dongdong, Wang, Zijin, Zheng, Ou
Vehicles equipped with automated driving capabilities have shown potential to improve safety and operations. Advanced driver assistance systems (ADAS) and automated driving systems (ADS) have been widely developed to support vehicular automation. Alt
Externí odkaz:
http://arxiv.org/abs/2303.17788
The application of Computer Vision (CV) techniques massively stimulates microscopic traffic safety analysis from the perspective of traffic conflicts and near misses, which is usually measured using Surrogate Safety Measures (SSM). However, as video
Externí odkaz:
http://arxiv.org/abs/2303.15231
Autor:
Huang, Hanyao, Zheng, Ou, Wang, Dongdong, Yin, Jiayi, Wang, Zijin, Ding, Shengxuan, Yin, Heng, Xu, Chuan, Yang, Renjie, Zheng, Qian, Shi, Bing
Publikováno v:
Int J Oral Sci. 2023 Jul 28;15(1):29
The ChatGPT, a lite and conversational variant of Generative Pretrained Transformer 4 (GPT-4) developed by OpenAI, is one of the milestone Large Language Models (LLMs) with billions of parameters. LLMs have stirred up much interest among researchers
Externí odkaz:
http://arxiv.org/abs/2304.03086
Crash data of autonomous vehicles (AV) or vehicles equipped with advanced driver assistance systems (ADAS) are the key information to understand the crash nature and to enhance the automation systems. However, most of the existing crash data sources
Externí odkaz:
http://arxiv.org/abs/2303.12889
The utilization of traffic conflict indicators is crucial for assessing traffic safety, especially when the crash data is unavailable. To identify traffic conflicts based on traffic flow characteristics across various traffic states, we propose a fra
Externí odkaz:
http://arxiv.org/abs/2303.16651
ChatGPT embarks on a new era of artificial intelligence and will revolutionize the way we approach intelligent traffic safety systems. This paper begins with a brief introduction about the development of large language models (LLMs). Next, we exempli
Externí odkaz:
http://arxiv.org/abs/2303.05382