| 许耀根,郭建钢,李林,罗文婷.基于行驶区间的快速路入口小型车VSP分布特征分析[J].井冈山大学自然版,2018,(3):68-73 |
| 基于行驶区间的快速路入口小型车VSP分布特征分析 |
| DRIVING SEGMENTS BASED VSP DISTRIBUTION FEATURE ANALYSIS FOR SMALL-SIZED VEHICLES AT THE EXPRESSWAY ENTRANCE |
| 投稿时间：2017-12-13 修订日期：2018-01-05 |
| DOI：10.3969/j.issn.1674-8085.2018.03.014 |
| 中文关键词: 交通能耗 比功率 聚类分析 快速路 汇入车流 小型车 |
| 英文关键词: traffic energy consumption VSP clustering analysis expressway converging traffic flow small-sized vehicles |
| 基金项目:国家自然科学基金项目（51608123）；福建省自然科学基金项目（2017J01682）. |
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| 中文摘要: |
| 为了研究快速路主辅路入口宏观小型车交通流的比功率（VSP）分布特性，在晚高峰时段用无人机拍摄快速路入口段小型车汇入的视频资料。把车辆汇入的行驶路段均分成10个行驶区间，通过Tracker软件获取视频中小型车的逐秒速度和逐秒加速度，计算各个行驶区间内所有驶过机动车的逐秒VSP。应用聚类分析法将所有逐秒VSP划分成12个VSP Bin，并计算和分析在各行驶区间内的VSP分布。结果表明：小型车流汇入过程中，在第1~8行驶区间内的VSP分布呈正态分布；同时，各行驶区间内VSP分布在正值范围的比重均比负值范围的大，且分布在0~5 kw·t-1所占分比重最大，其中在第3行驶区间所占比重达41.46%，但是在第8、第9行驶区间内，VSP分布在负区间的比重明显大于其他行驶区间，分别为42.86%和33.90%。 |
| 英文摘要: |
| To investigate VSP distribution characteristics of small-sized vehicles at expressway entrance, the video data at converging section of expressway entrance were collected using UAV during the evening peak hours. The converging section of traffic flow was equally divided into tendriving segments. The velocity and acceleration of the small-sized vehicles were obtained with tracker software. Subsequently, and VSP per second or VSP/s within driving segments was calculated, and per second based VSP was divided into 12 VSP bins using clustering analysis, and the VSP distribution features for each driving segment were obtained. Results indicated that the VSP distribution for driving segments from 1 to 8belong to normal distribution. The positive range takes a greater proportion than the negative range for the VSP distribution at each driving segment, and the largest proportion is located at the range of 0~5 kw·t-1. Moreover, the proportion of positive ranges up to 41.46%at the 3rd driving segment. However, the negative ranges of VSP distribution for the 8th and 9th driving segments occupy a larger proportion than other driving segments, with a percentage of 42.86% and 33.90% respectively. |
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