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高速公路交通状况准确检测对动态定价的影响:以 I-95 快速车道为例。

Impact of Accurate Detection of Freeway Traffic Conditions on the Dynamic Pricing: A Case Study of I-95 Express Lanes.

机构信息

Department of Civil & Environmental Engineering, Swanson School of Engineering, University of Pittsburgh, Benedum Hall, 3700 O'Hara Street Pittsburgh, Pittsburgh, PA 15261, USA.

A&P Consulting Transportation Engineers, 8935 NW 35th Ln, Doral, FL 33172, USA.

出版信息

Sensors (Basel). 2021 Sep 7;21(18):5997. doi: 10.3390/s21185997.

DOI:10.3390/s21185997
PMID:34577206
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8468808/
Abstract

Express lanes (ELs) implementation is a proven strategy to deal with freeway traffic congestion. Dynamic toll pricing schemes effectively achieve reliable travel time on ELs. The primary inputs for the typical dynamic pricing algorithms are vehicular volumes and speeds derived from the data collected by sensors installed along the ELs. Thus, the operation of dynamic pricing critically depends on the accuracy of data collected by such traffic sensors. However, no previous research has been conducted to explicitly investigate the impact of sensor failures and erroneous sensors' data on toll computations. This research fills this gap by examining the effects of sensor failure and faulty detection scenarios on ELs tolls calculated by a dynamic pricing algorithm. The paper's methodology relies on applying the dynamic toll pricing algorithm implemented in the field and utilizing the fundamental speed-volume relationship to 'simulate' the sensors' reported data. We implemented the methodology in a case study of ELs on Interstate-95 in Southeast Florida. The results have shown that the tolls increase when sensors erroneously report higher than actual traffic demand. Moreover, it has been found that the accuracy of individual sensors and the number of sensors utilized to estimate traffic conditions are critical for accurate toll calculations.

摘要

快速车道(ELs)的实施是应对高速公路交通拥堵的一种经过验证的策略。动态收费定价方案可有效地实现 ELs 上可靠的旅行时间。典型的动态定价算法的主要输入是从沿 EL 安装的传感器收集的数据得出的车辆数量和速度。因此,动态定价的运作严重依赖于此类交通传感器收集数据的准确性。然而,以前没有研究专门研究传感器故障和错误传感器数据对收费计算的影响。本研究通过检查传感器故障和错误检测场景对动态定价算法计算的 EL 收费的影响来填补这一空白。本文的方法依赖于应用现场实施的动态收费定价算法,并利用基本的速度-流量关系来“模拟”传感器报告的数据。我们在佛罗里达州东南部 I-95 的 EL 案例研究中实施了该方法。结果表明,当传感器错误地报告高于实际交通需求的流量时,收费会增加。此外,还发现,用于估计交通状况的单个传感器的准确性和传感器的数量对于准确的收费计算至关重要。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/acee/8468808/ee5538fcb13d/sensors-21-05997-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/acee/8468808/4bf2a814b99a/sensors-21-05997-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/acee/8468808/ce4a088b37d9/sensors-21-05997-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/acee/8468808/e31d30c4d7c6/sensors-21-05997-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/acee/8468808/7edb79c8afc0/sensors-21-05997-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/acee/8468808/d698ba951fd6/sensors-21-05997-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/acee/8468808/4da24cc80787/sensors-21-05997-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/acee/8468808/f123b3f1c8e6/sensors-21-05997-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/acee/8468808/88a48d8c4e91/sensors-21-05997-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/acee/8468808/ee5538fcb13d/sensors-21-05997-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/acee/8468808/4bf2a814b99a/sensors-21-05997-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/acee/8468808/ce4a088b37d9/sensors-21-05997-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/acee/8468808/e31d30c4d7c6/sensors-21-05997-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/acee/8468808/7edb79c8afc0/sensors-21-05997-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/acee/8468808/d698ba951fd6/sensors-21-05997-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/acee/8468808/4da24cc80787/sensors-21-05997-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/acee/8468808/f123b3f1c8e6/sensors-21-05997-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/acee/8468808/88a48d8c4e91/sensors-21-05997-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/acee/8468808/ee5538fcb13d/sensors-21-05997-g005.jpg

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