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Fang Liu
Inner Mongolia Agricultural University
StatisticsTraffic flowMathematicsComputer scienceFuzzy logic
20Publications
12H-index
572Citations
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Publications 22
Newest
#1Jinjun TangH-Index: 15
#2Fan GaoH-Index: 1
Last. Xinqiang ChenH-Index: 3
view all 4 authors...
1 CitationsSource
#1Jinjun TangH-Index: 15
#2Fan GaoH-Index: 1
Last. Yong QiH-Index: 1
view all 5 authors...
Taxis are an important part of the urban public transit system. Understanding the spatio-temporal variations of taxi travel demand is essential for exploring urban mobility and patterns. The purpose of this study is to use the taxi Global Positioning System (GPS) trajectories collected in New York City to investigate the spatio-temporal characteristic of travel demand and the underlying affecting variables. We analyze the spatial distribution of travel demand in different areas by extracting the...
1 CitationsSource
#1Jinjun Tang (CSU: Central South University)H-Index: 15
#2Shaowei Yu (China Mobile)H-Index: 1
Last. Helai Huang (CSU: Central South University)H-Index: 16
view all 5 authors...
Abstract Lane changing behavior generally expresses uncertainty due to the impact of environmental factors, and unreasonable lane changes can cause serious collisions. High precision prediction of lane changing intent is helpful to enhance proactivity in driving safety protection. This study proposed a lane-changing prediction model based on Fuzzy C-means clustering algorithm and adaptive Neural Network (FCMNN), which introduced a new prediction process: (1) Unsupervised learning method: categor...
3 CitationsSource
Source
#1Jinjun Tang (CSU: Central South University)H-Index: 15
#2Jian Liang (CSU: Central South University)H-Index: 2
Last. Fang Liu (Inner Mongolia Agricultural University)H-Index: 12
view all 5 authors...
Abstract Use of taxi vehicles as mobile sensors to collect traffic information has become an important and emerging approach to relieve congestion. Global Positioning System (GPS) trajectory data allow for abundant temporal and spatial information to be collected that reflect the mobility and activity of drivers. In this paper, we present a probabilistic model to predict driving trip paths based on a Hidden Markov Model (HMM). The first step in our approach was to detect the stays or destination...
31 CitationsSource
#1Jinjun Tang (CSU: Central South University)H-Index: 15
#2Shen Zhang (HIT: Harbin Institute of Technology)H-Index: 9
Last. Yajie Zou (Tongji University)H-Index: 17
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Abstract Understanding Origin–Destination distribution of taxi trips is very important for improving effects of transportation planning and enhancing quality of taxi services. This study proposes a new method based on Entropy-Maximizing theory to model OD distribution in Harbin city using large-scale taxi GPS trajectories. Firstly, a K -means clustering method is utilized to partition raw pick-up and drop-off location into different zones, and trips are assumed to start from and end at zone cent...
36 CitationsSource
#1Jinjun Tang (CSU: Central South University)H-Index: 15
#2Fang Liu (Inner Mongolia Agricultural University)H-Index: 12
Last. Yajie Zou (Tongji University)H-Index: 17
view all 5 authors...
Abstract Lane changing maneuver is one of the most important driving behaviors. Unreasonable lane changes can cause serious collisions and consequent traffic delays. High precision prediction of lane changing intent is helpful for improving driving safety. In this study, by fusing information from vehicle sensors, a lane changing predictor based on Adaptive Fuzzy Neural Network (AFFN) is proposed to predict steering angles. The prediction model includes two parts: fuzzy neural network based on T...
45 CitationsSource
#1Jinjun Tang (CSU: Central South University)H-Index: 15
#2Shen Zhang (HIT: Harbin Institute of Technology)H-Index: 9
Last. Fang Liu (Inner Mongolia Agricultural University)H-Index: 12
view all 4 authors...
An improved hierarchical fuzzy inference method based on C-measure map-matching algorithm is proposed in this paper, in which the C-measure represents the certainty or probability of the vehicle traveling on the actual road. A strategy is firstly introduced to use historical positioning information to employ curve-curve matching between vehicle trajectories and shapes of candidate roads. It improves matching performance by overcoming the disadvantage of traditional map-matching algorithm only co...
6 CitationsSource
#1Jinjun Tang (CSU: Central South University)H-Index: 15
#2Fang Liu (Inner Mongolia Agricultural University)H-Index: 12
Last. Yinhai Wang (UW: University of Washington)H-Index: 31
view all 5 authors...
This paper proposes a new method in construction fuzzy neural network to forecast travel speed for multi-step ahead based on 2-min travel speed data collected from three remote traffic microwave sensors located on a southbound segment of a fourth ring road in Beijing City. The first-order Takagi–Sugeno system is used to complete the fuzzy inference. To train the evolving fuzzy neural network (EFNN), two learning processes are proposed. First, a K-means method is employed to partition input sa...
94 CitationsSource
#1Jinjun Tang (UW: University of Washington)H-Index: 15
#2Shen Zhang (HIT: Harbin Institute of Technology)H-Index: 9
Last. Yinhai Wang (UW: University of Washington)H-Index: 31
view all 6 authors...
This study explores urban mobility from a network-based perspective. The data samples used in study were collected from more than 1100 taxi drivers during a half year period in the city of Harbin in China. We extract trips from the original dataset and analyze operational efficiency. Then, by constructing travel networks based on occupied and vacant taxi trips, we calculate some statistical properties of the network such as degree, strength, edge weight, betweenness, clustering coefficient and n...
14 CitationsSource
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