Zobrazeno 1 - 10
of 115
pro vyhledávání: '"Macfarlane, Jane"'
Traffic signals play an important role in transportation by enabling traffic flow management, and ensuring safety at intersections. In addition, knowing the traffic signal phase and timing data can allow optimal vehicle routing for time and energy ef
Externí odkaz:
http://arxiv.org/abs/2308.02370
Traffic forecasting is an important issue in intelligent traffic systems (ITS). Graph neural networks (GNNs) are effective deep learning models to capture the complex spatio-temporal dependency of traffic data, achieving ideal prediction performance.
Externí odkaz:
http://arxiv.org/abs/2305.00985
Single occupancy vehicles are the most attractive transportation alternative for many commuters, leading to increased traffic congestion and air pollution. Advancements in information technologies create opportunities for smart solutions that incenti
Externí odkaz:
http://arxiv.org/abs/2304.03697
Accurate traffic forecasting is vital to an intelligent transportation system. Although many deep learning models have achieved state-of-art performance for short-term traffic forecasting of up to 1 hour, long-term traffic forecasting that spans mult
Externí odkaz:
http://arxiv.org/abs/2209.13123
The rapid introduction of mobile navigation aides that use real-time road network information to suggest alternate routes to drivers is making it more difficult for researchers and government transportation agencies to understand and predict the dyna
Externí odkaz:
http://arxiv.org/abs/2207.12580
Deep-learning-based data-driven forecasting methods have produced impressive results for traffic forecasting. A major limitation of these methods, however, is that they provide forecasts without estimates of uncertainty, which are critical for real-t
Externí odkaz:
http://arxiv.org/abs/2204.01618
Publikováno v:
In International Journal of Transportation Science and Technology September 2024 15:155-169
Using the data from loop detector sensors for near-real-time detection of traffic incidents in highways is crucial to averting major traffic congestion. While recent supervised machine learning methods offer solutions to incident detection by leverag
Externí odkaz:
http://arxiv.org/abs/2112.09792
Location data is collected from users continuously to understand their mobility patterns. Releasing the user trajectories may compromise user privacy. Therefore, the general practice is to release aggregated location datasets. However, private inform
Externí odkaz:
http://arxiv.org/abs/2112.08487
Publikováno v:
Transportation Letters (2023) 1-18
Technological advancements are rapidly changing traffic management in cities. Massive adoption of mobile devices and cloud-based applications have created new mechanisms for urban traffic control and management. Specifically, navigation applications
Externí odkaz:
http://arxiv.org/abs/2111.06059