Arterial Coordination Optimization Based on Trajectory Data

被引:0
|
作者
Zhang, Weibin [1 ]
Bai, Zishuai [1 ]
Li, Xiying [2 ]
机构
[1] Nanjing Univ Sci & Technol, Sch Elect & Opt Engn, Nanjing, Peoples R China
[2] Sun Yat Sen Univ, Sch Intelligent Syst Engn, Guangzhou, Peoples R China
来源
INTERNATIONAL CONFERENCE ON TRANSPORTATION AND DEVELOPMENT 2020 - TRAFFIC AND BIKE/PEDESTRIAN OPERATIONS | 2020年
基金
中国国家自然科学基金;
关键词
Trunk timing optimization; Trajectory data; Delay time prediction;
D O I
暂无
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
With the rapid development of urban traffic, the problem of urban traffic congestion is becoming more and more serious. Solving the traffic congestion of the main arterials of urban area is of great significance to alleviate the urban traffic congestion. Arterial coordination optimization is an effective method to improve arterial capacity, service level, and alleviate the urban traffic congestion. In this paper, an arterial coordination optimization model has been proposed with the analysis and processing of the vehicle trajectory. First, the characteristic trajectories are extracted according to the velocity distribution of the arterial line. Then, the intersection delay model is established to optimize the characteristic trajectories to obtain the phase difference for each intersection. The simulation result by SUMO software shows our method has 45.48% improvement in parking delay and 14.08% improvement in the average queue length at each intersection, which proves effectiveness of the proposed method.
引用
收藏
页码:181 / 193
页数:13
相关论文
共 50 条
  • [31] Real-time detection of traffic congestion based on trajectory data
    Yang, Qing
    Yue, Zhongwei
    Chen, Ru
    Zhang, Jingwei
    Hu, Xiaoli
    Zhou, Ya
    JOURNAL OF ENGINEERING-JOE, 2019, 2019 (11): : 8251 - 8256
  • [32] MaritimeDS: a data service framework for unsupervised maritime traffic monitoring based on trajectory big data
    Yang X.
    Wang G.
    Gao J.
    Journal of Reliable Intelligent Environments, 2022, 8 (01) : 3 - 19
  • [33] THBase: A Coprocessor-Based Scheme for Big Trajectory Data Management
    Qin, Jiwei
    Ma, Liangli
    Niu, Jinghua
    FUTURE INTERNET, 2019, 11 (01):
  • [34] Abnormal driving behavior thresholds of highway minibuses based on trajectory data
    Zhou, Rong-Gui
    Gao, Pei
    Li, Yu-Xuan
    Zhou, Jian
    Jilin Daxue Xuebao (Gongxueban)/Journal of Jilin University (Engineering and Technology Edition), 2024, 54 (09): : 2581 - 2587
  • [35] A Data Model and Predicate Logic for Trajectory Data
    Bornholdt, Johann
    Chondrogiannis, Theodoros
    Grossniklaus, Michael
    ADVANCES IN DATABASES AND INFORMATION SYSTEMS, ADBIS 2024, 2024, 14918 : 18 - 31
  • [36] A Conceptual Data Model for Trajectory Data Mining
    Bogorny, Vania
    Heuser, Carlos Alberto
    Alvares, Luis Otavio
    GEOGRAPHIC INFORMATION SCIENCE, 2010, 6292 : 1 - +
  • [37] On the use of trajectory data for tackling data scarcity
    Pons, Gerard
    Bilalli, Besim
    Abello, Alberto
    Sanchez, Santiago Blanco
    INFORMATION SYSTEMS, 2025, 130
  • [38] Optimization Strategy of Lane-changing Trajectory Based on Vehicle Powertrain and Steering System
    Liao P.
    Tang T.-Q.
    Jiaotong Yunshu Xitong Gongcheng Yu Xinxi/Journal of Transportation Systems Engineering and Information Technology, 2022, 22 (01): : 98 - 105and114
  • [39] A Generalization-Based Approach for Personalized Privacy Preservation in Trajectory Data Publishing
    Komishani, Elahe Ghasemi
    Abadi, Mahdi
    2012 SIXTH INTERNATIONAL SYMPOSIUM ON TELECOMMUNICATIONS (IST), 2012, : 1129 - 1135
  • [40] Design and Application of an Attractiveness Index for Urban Hotspots Based on GPS Trajectory Data
    Cai, Li
    Jiang, Fang
    Zhou, Wei
    Li, Keqin
    IEEE ACCESS, 2018, 6 : 55976 - 55985