Results 261 to 270 of about 8,928,935 (332)

RNTrajRec: Road Network Enhanced Trajectory Recovery with Spatial-Temporal Transformer

IEEE International Conference on Data Engineering, 2022
GPS trajectories are the essential foundations for many trajectory-based applications. Most applications require a large number of high sample rate trajectories to achieve a good performance.
Yuqi Chen, Hanyuan Zhang, Weiwei Sun, B. Zheng   +3 more
semanticscholar   +1 more source

Exploring the resilience assessment framework of urban road network for sustainable cities

Physica A: Statistical Mechanics and its Applications, 2022
Urban space for new transportation facilities cannot meet the increasing traffic demand. Afterward, scholars gradually increased attention to the resilience evaluation of urban road networks.
Zhizhen Liu, Hong Chen, E.‐T. Liu, Wanyu Hu   +3 more
semanticscholar   +1 more source

Robust Road Network Representation Learning: When Traffic Patterns Meet Traveling Semantics

International Conference on Information and Knowledge Management, 2021
In this work, we propose a robust road network representation learning framework called Toast, which comes to be a cornerstone to boost the performance of numerous demanding transport planning tasks. Specifically, we first propose a traffic context aware
Yile Chen, Xiucheng Li, Gao Cong, Z. Bao, Cheng Long, Yiding Liu, A. Chandran, R. Ellison   +7 more
semanticscholar   +1 more source

An Assessment Method for Traffic State Vulnerability Based on a Cloud Model for Urban Road Network Traffic Systems

IEEE transactions on intelligent transportation systems (Print), 2021
Directed against the shortcoming of the vulnerability assessment based on complex network theory for urban road network traffic systems, a state vulnerability assessment method, considering the influence of congestion, is constructed by using a cloud ...
Zhenping Deng, Darong Huang, Jinyu Liu, Bo Mi, Yang Liu   +4 more
semanticscholar   +1 more source

Learning Effective Road Network Representation with Hierarchical Graph Neural Networks

Knowledge Discovery and Data Mining, 2020
Road network is the core component of urban transportation, and it is widely useful in various traffic-related systems and applications. Due to its important role, it is essential to develop general, effective, and robust road network representation ...
Ning Wu, Wayne Xin Zhao, Jingyuan Wang, Dayan Pan   +3 more
semanticscholar   +1 more source

SSGRU: A novel hybrid stacked GRU-based traffic volume prediction approach in a road network

Computer Communications, 2020
As a potential solution to relieve traffic congestions and help build a more safe traffic system, traffic flow prediction methods are given much attention in recent years.
Peng Sun, A. Boukerche, Yanjie Tao
semanticscholar   +1 more source

Schematization of road networks

Proceedings of the seventeenth annual symposium on Computational geometry, 2001
We study the problem of computing schematized versions of network maps , like railroad maps. Every path of the schematized map has two or three links with restricted orientations, and topologically, the schematized map must be equivalent to the input map.
Cabello Justo, S., de Berg, M.T., van Dijk, S.F., van Kreveld, M.J., Strijk, T.W.   +4 more
openaire   +2 more sources

Road Network Reserve Capacity Considering Road Network Service Level

2014 Sixth International Conference on Measuring Technology and Mechatronics Automation, 2014
In order to obtain road network capacity under specified service level, a bi-level programming model of network reserve capacity based on road service level restraint is built. In this model, the basic OD traffic demand multiplier is maximized with service level restraint in the upper problem and a stochastic user equilibrium assignment model is used ...
Lu Rong, Huang Zhongxiang, Shan Liangci
openaire   +1 more source

Road finding for road-network extraction

Proceedings CVPR '88: The Computer Society Conference on Computer Vision and Pattern Recognition, 2003
Automatic extraction of roads from aerial photos has been demonstrated in a number of systems, but the systems which display the better capabilities usually rely on manual selection of road starting points. This interaction with a human operator is eliminated by integrating a road-finding module into a road network extraction system.
Z. Aviad, P.D. Carnine
openaire   +1 more source

Elevated Road Network

Proceedings of the 29th ACM International Conference on Information & Knowledge Management, 2020
Mobile navigation is a critical component in mobile maps. Yawing detection (does a vehicle yaw) is an important task in mobile navigation. In regions containing parallel and close elevated and surface roads, it is hard to detect yawing events using traditional methods, which mainly rely on low-accuracy positions and moving directions.
Xiaobing Zhang, Hailiang Xu, Jian Yang, Jia Sun, Fan Chen, Leiyun Li   +5 more
openaire   +1 more source