Quantifying the Number of Lane Changes in Traffic

功能(生物学) 流量(计算机网络) 概率密度函数 计算机科学 统计 公里 运输工程 数学 工程类 计算机安全 进化生物学 生物
作者
Victor L. Knoop,Serge P. Hoogendoorn,Yasuhiro Shiomi,Christine Buisson
出处
期刊:Transportation Research Record [SAGE]
卷期号:2278 (1): 31-41 被引量:50
标识
DOI:10.3141/2278-04
摘要

Lane changes are an important aspect of freeway flow. Most models of lane change are microscopic. Lane change behavior of individual vehicles or drivers is described, and, therefore, models are calibrated microscopically. Macroscopic validation often is restricted to the distribution of vehicles across lanes. To the best of the authors' knowledge, no systematic analysis has been made of the number of lane changes as a function of the operational characteristics of the origin and target lane. This paper fills the gap in lane change literature with an analysis of the number of lane changes as a function of several incentives. On the basis of data availability, two “simple” sites were selected, that is, as close as possible to a straight continuous freeway. Statistical analysis at the selected sites revealed that drivers changed lanes on average once per 2 km driven. Furthermore, an analysis of the number of lane changes (per kilometer per hour) as a function of the density in the origin lane and in the target lane showed that the number of lane changes increased with the density in the origin lane for a fixed density in the target lane. The number of lane changes also increased with the density in the target lane for a fixed density in the origin lane. The underlying mechanism was therefore different from gap-acceptance theory. The analyses presented in this paper can be used to verify qualitatively (microscopic and macroscopic) lane change models and to propose better ones.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
一颗柚子完成签到,获得积分10
刚刚
abc完成签到 ,获得积分10
刚刚
PMX发布了新的文献求助10
1秒前
标致小伙发布了新的文献求助10
1秒前
joysa完成签到,获得积分10
1秒前
131343完成签到,获得积分10
1秒前
FashionBoy应助慕子采纳,获得10
2秒前
2秒前
2秒前
L龙发布了新的文献求助10
3秒前
3秒前
善学以致用应助sunwending采纳,获得10
3秒前
东郭秋凌完成签到,获得积分10
3秒前
胤宸完成签到,获得积分10
4秒前
5秒前
5秒前
hohokuz完成签到,获得积分20
5秒前
一切顺遂应助Adian采纳,获得100
5秒前
5秒前
April发布了新的文献求助20
6秒前
Huaiman发布了新的文献求助10
7秒前
科研通AI5应助转角一起走采纳,获得20
7秒前
蛋炒饭完成签到,获得积分10
8秒前
执着完成签到,获得积分10
8秒前
研友_ED5GK发布了新的文献求助10
8秒前
9秒前
绿麦盲区完成签到,获得积分10
9秒前
Yvonne发布了新的文献求助10
9秒前
10秒前
10秒前
minghanl完成签到,获得积分10
11秒前
zhaomr发布了新的文献求助10
11秒前
科目三应助pbf采纳,获得20
12秒前
12秒前
12秒前
same完成签到,获得积分10
13秒前
科研通AI5应助俭朴夜雪采纳,获得30
13秒前
读研好难发布了新的文献求助10
14秒前
Adian完成签到,获得积分10
15秒前
Huaiman完成签到,获得积分10
15秒前
高分求助中
Continuum Thermodynamics and Material Modelling 3000
Production Logging: Theoretical and Interpretive Elements 2700
Social media impact on athlete mental health: #RealityCheck 1020
Ensartinib (Ensacove) for Non-Small Cell Lung Cancer 1000
Unseen Mendieta: The Unpublished Works of Ana Mendieta 1000
Bacterial collagenases and their clinical applications 800
El viaje de una vida: Memorias de María Lecea 800
热门求助领域 (近24小时)
化学 材料科学 生物 医学 工程类 有机化学 生物化学 物理 纳米技术 计算机科学 内科学 化学工程 复合材料 基因 遗传学 物理化学 催化作用 量子力学 光电子学 冶金
热门帖子
关注 科研通微信公众号,转发送积分 3527723
求助须知:如何正确求助?哪些是违规求助? 3107826
关于积分的说明 9286663
捐赠科研通 2805577
什么是DOI,文献DOI怎么找? 1539998
邀请新用户注册赠送积分活动 716878
科研通“疑难数据库(出版商)”最低求助积分说明 709762