中文核心期刊
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重庆交通大学学报（自然科学版）

重庆交通大学学报（自然科学版） ›› 2024, Vol. 43 ›› Issue (9): 86-91.DOI: 10.3969/j.issn.1674-0696.2024.09.11

• 交通+大数据人工智能 • 上一篇    

基于改进NaSch模型的网联异质交通流特性分析

张萌萌1,2，宋家恕1,2,3，解树坤1,2   

  1. (1. 山东交通学院 交通与物流工程学院，山东 济南 250357； 2. 山东省智慧交通重点实验室(筹)，山东 济南 250357； 3. 济南轨道交通集团有限公司，山东 济南 250014)
  • 收稿日期:2023-10-13 修回日期:2024-05-22 发布日期:2024-09-25
  • 作者简介:张萌萌(1981—)，女，山东济南人，教授，博士，主要从事智能交通、交通大数据分析方面的研究。E-mail：zhangmengmeng@sdjtu.edu.cn 通信作者：解树坤(2000—)，女，山东泰安人，硕士研究生，主要从事智能交通、交通规划与管理方面的研究。E-mail：1250514957@qq.com
  • 基金资助:
    山东省自然科学基金项目(ZR2021MF019)；山东省自然科学基金项目(青年基金)（ZR2021OF110）；山东省科学技术厅项目（2021TSGC1011）2021TSGC1011；山东省科学技术厅项目（2022TSGC2096）；山东省重点研发计划(软科学)重点项目(2023RZB06052)

Networked Heterogeneous Traffic Flow Characteristics Based on Improved NaSch Model

ZHANG Mengmeng1,2, SONG Jiashu1,2,3, XIE Shukun1,2   

  1. (1. School of Transportation and Logistics Engineering, Shandong Jiaotong University, Jinan 250357, Shandong, China; 2. Shandong Provincial Key Laboratory of Smart Transportation (under Preparation), Jinan 250357, Shandong, China; 3. Jinan Rail Transit Group Co., Ltd., Jinan 250014, Shandong, China)
  • Received:2023-10-13 Revised:2024-05-22 Published:2024-09-25

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摘要： 为研究智能网联环境下异质交通流演变规律，设计典型场景驾驶模拟实验，采集传统车辆（human driven vehicle,HDV）与智能网联车辆(connected vehicle,CV）驾驶行为特征指标，对异质交通流关键参数进行分析和标定；构建考虑HDV与CV驾驶行为差异的异质交通流元胞自动机模型；并基于改进的NaSch模型进行仿真实验，解析智能网联环境下交通流基本图，分析异质交通流特性。研究结果表明：较于HDV，CV驾驶员捕捉道路信息和反应时间提升约11.4%；自由流状态下，CV车速比HDV车速提升了7.4%，且同一车速下安全跟驰距离缩短了18.2%；随着CV所占比例由20%增至80%，交通流基本图显示交通流平均车速显著提升，交通流率增加，时空轨迹图显示局部拥堵状况明显改善。

关键词: 交通工程；智能网联；异质交通流；NaSch模型；元胞自动机；驾驶模拟实验

Abstract: To study the evolution law of heterogeneous traffic flow in the intelligent network connection environment, typical scene driving simulation experiments were designed. The driving behavior characteristic indicators of human driven vehicle (HDV) and connected vehicle (CV) were collected, key parameters of heterogeneous traffic flow were analyzed and calibrated. The heterogeneous traffic flow cellular automata model that took into account the differences in driving behavior between HDV and CV was established. Simulation experiment was carried out on the basis of the improved NaSch model, the basic traffic flow diagram in the intelligent connected environment and the characteristics of heterogeneous traffic flow were analyzed. The research results show that: compared to HDV, CV drivers capture of road information and reaction time increases by about 11.4%. Under free flow conditions, the speed of CV increases by 7.4% compared to HDV, and the safe following distance is shortened by 18.2% at the same speed. As the proportion of CV increases from 20% to 80%, the basic traffic flow map shows a significant increase in average speed, and the traffic flow rate increases. The spatiotemporal trajectory map shows a significant improvement in local congestion.

Key words: traffic engineering; intelligent network connection; heterogeneous traffic flow; NaSch model; cellular automata; driving simulation experiment

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