"Impact of accurate detection of freeway traffic conditions on the dyna" by Suhaib Alshayeb, Aleksandar Stevanovic et al.
 

Impact of accurate detection of freeway traffic conditions on the dynamic pricing: A case study of I-95 express lanes

Document Type

Article

Publication Date

9-1-2021

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.

Identifier

85114377671 (Scopus)

Publication Title

Sensors

External Full Text Location

https://doi.org/10.3390/s21185997

ISSN

14248220

PubMed ID

34577206

Issue

18

Volume

21

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