| 引用本文: | 张盈盈,刘帅,邱志军,姚丹亚,彭黎辉.行人车辆冲突参数分析与安全评价[J].哈尔滨工业大学学报,2012,44(12):123.DOI:10.11918/j.issn.0367-6234.2012.12.022 |
| ZHANG Ying-ying,LIU Shuai,QIU Zhi-jun,YAO Dan-ya,PENG Li-hui.Pedestrian-vehicle conflict parameter analysis and safety evaluation[J].Journal of Harbin Institute of Technology,2012,44(12):123.DOI:10.11918/j.issn.0367-6234.2012.12.022 |
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| 行人车辆冲突参数分析与安全评价 |
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张盈盈1, 刘帅1, 邱志军2, 姚丹亚1, 彭黎辉1
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(1.清华大学 自动化系,100084 北京; 2.阿尔伯塔大学 土木与环境系,T6G2W2 加拿大 阿尔伯塔);1.清华大学 自动化系,100084 北京;2.阿尔伯塔大学 土木与环境系,T6G2W2 加拿大 阿尔伯塔
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| 摘要: |
| 为了评价混合交通环境中的行人和车辆冲突的安全性,对比分析了目前常用的行人车辆冲突参数,提出了个体行人和车辆之间冲突的安全评价模型,并将模型应用于不同的混合交通场景,验证模型的鲁棒性和适用性．结果表明,冲突时间差(Time difference to collision,TDTC)和车辆速度对行人车辆冲突的安全性影响最大．TDTC越接近于零,行人越危险;车辆速度越快,行人越危险．以此建立的行人车辆冲突评价模型可正确评估86.2％的行人车辆冲突安全,对于危险冲突的漏检率为2.1％． |
| 关键词: 行人车辆冲突 冲突时间差(TDTC) 车辆速度 行人安全 |
| DOI：10.11918/j.issn.0367-6234.2012.12.022 |
| 分类号:TP29 |
| 基金项目:国家自然科学基金资助项目(3,1); 国家高技术研究发展计划项目(2011AA1,2AA112305). |
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| Pedestrian-vehicle conflict parameter analysis and safety evaluation |
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ZHANG Ying-ying1, LIU Shuai1, QIU Zhi-jun2, YAO Dan-ya1, PENG Li-hui1
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(1.Dept. of Automation, Tsinghua University, 100084 Beijing, China; 2.Dept. of Civil and Environmental Engineering, University of Alberta, T6G2W2 Alberta,Canada);1.Dept.of Automation, Tsinghua University, 100084 Beijing, China ;2.Dept.of Civil and Environmental Engineering, University of Alberta, T6G2W2 Alberta,Canada
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| Abstract: |
| To evaluate the pedestrian-vehicle conflict safety in mixed traffic condition, this paper analyzes and compares the commonly used parameters on traffic conflict and presents a model to classify independent pedestrian-vehicle conflict safety. The model is validated by using video data from two different traffic scenes. The result shows that the pedestrian-vehicle conflict safety is highly sensitive to the Time Difference to Collision (TDTC) parameter and the vehicle speed. The closer to zero a TDTC value is and the faster a vehicle is, the more dangerous a pedestrian-vehicle conflict may be. Comparing with independent observation, the model can correctly classify about 86.2％ conflicts; only 2.1％ conflicts are classified as safer by the model. |
| Key words: pedestrian-vehicle conflict time difference to collision (TDTC) vehicle speed pedestrian safety |
