Truck traffic speed prediction under non-recurrent congestion: Based on optimized deep learning algorithms and GPS data

J Zhao, Y Gao, Z Yang, J Li, Y Feng, Z Qin, Z Bai - IEEE Access, 2019 - ieeexplore.ieee.org
Due to the restriction of traffic management measure in large cities, large heavy-haul trucks
can only travel on the circuits and expressways around the city, which often causes …

A special event-based K-nearest neighbor model for short-term traffic state prediction

H Yu, N Ji, Y Ren, C Yang - Ieee Access, 2019 - ieeexplore.ieee.org
Recently, short-term traffic state prediction for urban transportation networks has become a
popular topic. However, due to the uncontrollable and unpredictable elements of special …

Deployment optimization of data centers in vehicular networks

B Huang, W Liu, T Wang, X Li, H Song, A Liu - IEEE Access, 2019 - ieeexplore.ieee.org
Due to the ubiquitous utilization of GPS devices, traffic cameras, and sensing devices, data
are collected more readily in a smart city. If all the cabs of this city are used as data carriers …

A data-driven-based wavelet support vector approach for passenger flow forecasting of the metropolitan hub

M Tang, Z Li, G Tian - Ieee Access, 2019 - ieeexplore.ieee.org
With the rapid development of the construction and operation of mass transit hubs,
passenger data collection, modeling, and prediction for optimal control have become very …

Forecasting traffic volume at a designated cross-section location on a freeway from large-regional toll collection data

P Wang, W Xu, Y Jin, J Wang, L Li, Q Lu, G Wang - Ieee Access, 2019 - ieeexplore.ieee.org
Both road users and administrators are keen to know the traffic volume at the arbitrary point
on the road network. In China, charging systems have been fully established in closed large …

A hybrid model for forecasting traffic flow: Using layerwise structure and Markov transition matrix

S Zhang, Z Kang, Z Zhang, C Lin, C Wang, J Li - Ieee Access, 2019 - ieeexplore.ieee.org
Forecasting the traffic flow is greatly significant for traffic safety, energy conservation, and
environmental protection. However, in the face of many external uncertainties, making …

Infrared multi-pedestrian tracking in vertical view via siamese convolution network

G Shen, L Zhu, J Lou, S Shen, Z Liu, L Tang - IEEE Access, 2019 - ieeexplore.ieee.org
Target tracking has become one of the research hotspots in the field of computer vision in
recent years. In this paper, a new intelligent algorithm of infrared multi-pedestrian tracking in …

An accurate vehicle and road condition estimation algorithm for vehicle networking applications

H Xiong, J Liu, R Zhang, X Zhu, H Liu - IEEE Access, 2019 - ieeexplore.ieee.org
The Internet of Vehicles is essential for building smart cities. By analyzing the big data
collected by vehicle sensors on the road, we can estimate vehicle information and real-time …

Research on customer marketing acceptance for future automatic driving—a case study in China city

H Wang, F You, X Chu, X Li, X Sun - IEEE Access, 2019 - ieeexplore.ieee.org
This paper investigates the acceptance of intelligent driving vehicles in the Chinese market
using Guangzhou City as an example and a field questionnaire investigation based on the …

Discovering transit-oriented development regions of megacities using heterogeneous urban data

X Kong, F Xia, K Ma, J Li, Q Yang - IEEE Transactions on …, 2019 - ieeexplore.ieee.org
Public transport is of great significance in megacities. Transit-oriented development (TOD)
has become a reliable solution to urban sustainable development, which can reshape the …