Impact Assessing of Traffic Lights via GPS Vehicle Trajectories
Impact Assessing of Traffic Lights via GPS Vehicle Trajectories
复制标题
通过 GPS 车辆轨迹进行交通灯影响评估
DOI：
10.3390/ijgi10110769
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发表时间：
2021-11
影响因子：
3.4
通讯作者：
Aiping Yi
中科院分区：
文献类型：
--
作者：
Zhuhua Liao;Hao Xiao;Silin Liu;Yizhi Liu;Aiping Yi
交通信号灯在车辆交通控制中的适应性严重影响着忙碌城市地区车辆的通过性和交通参与者的出行效率。现有的研究主要集中在交通信号灯的存在，但很少通过分析交通数据来评估交通信号灯的影响，因此没有实用和精确的自调节交通信号灯的解决方案。针对这些问题，提出了一种低成本、快速的交通信号检测与影响评估框架，该框架以监督的方式从GPS轨迹和交叉口特征中检测交通信号灯，并从交叉口轨迹数据段中分析交通信号灯的影响范围和时间。实验结果表明，该方法在ROC标准分类下获得了最佳的AUC值0.95，表明交叉口交通信号灯的影响模式与交通参与者的出行规律高度相关。
The adaptability of traffic lights in the control of vehicle traffic heavily affects the trafficability of vehicles and the travel efficiency of traffic participants in busy urban areas. Existing studies mainly have focused on the presence of traffic lights, but rarely evaluate the impact of traffic lights by analyzing traffic data, thus there is no solution for practicably and precisely self-regulating traffic lights. To address these issues, we propose a low-cost and fast traffic signal detection and impact assessment framework, which detects traffic lights from GPS trajectories and intersection features in a supervised way, and analyzes the impact range and time of traffic lights from intersection track data segments. The experimental results show that our approach gains the best AUC value of 0.95 under the ROC standard classification and indicates that the impact pattern of traffic lights at intersections is high related to the travel rule of traffic participants.
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DOI：
10.3390/ijgi9110652
发表时间：
2020-10
期刊：
ISPRS Int. J. Geo Inf.
影响因子：
--
作者：
Hao Cheng;S. Zourlidou;Monika Sester
通讯作者：
Hao Cheng;S. Zourlidou;Monika Sester
DOI：
10.1016/j.neunet.2021.03.015
发表时间：
2021-03
期刊：
Neural networks : the official journal of the International Neural Network Society
影响因子：
--
作者：
Shantian Yang;Bo Yang;Zhongfeng Kang;Lihui Deng
通讯作者：
Shantian Yang;Bo Yang;Zhongfeng Kang;Lihui Deng
DOI：
10.1109/infocom.2014.6848139
发表时间：
2014-07
期刊：
IEEE INFOCOM 2014 - IEEE Conference on Computer Communications
影响因子：
--
作者：
Yiran Zhao;Yang Zhang;Tuo Yu;Tianyuan Liu;Xinbing Wang;Xiaohua Tian;Xue Liu
通讯作者：
Yiran Zhao;Yang Zhang;Tuo Yu;Tianyuan Liu;Xinbing Wang;Xiaohua Tian;Xue Liu
影响因子：
1.7
作者：
Christopher Pribe;Seth Rogers
通讯作者：
Christopher Pribe;Seth Rogers
影响因子：
5
作者：
Chawla, NV;Bowyer, KW;Kegelmeyer, WP
通讯作者：
Kegelmeyer, WP