Design Strategy for Smart Toll Gate Billing System

Bohra, Varun; Prasad, Deepak; Nidhi, Neha; Tiwari, Anup; Nath, Vijay

doi:10.1007/978-981-10-8234-4_49

Cited by 6 publications

(1 citation statement)

References 1 publication

Supporting

Mentioning

Contrasting

Order By: Relevance

“…[23] claimed that some percentages of heavy vehicles in traffic flow significantly effects queue lengths at toll plazas and confirmed that part of the cause of traffic jams are contributed by toll plazas. In order to ease the amount of time spent at a toll plaza, an automation of billing collection systems were suggested [24]. [25] studied a reversible lane concept for the collection of toll according to demand.…”

Section: Literature Reviewmentioning

confidence: 99%

Prediction of Congestions Using Basic Traffic Unit

Majid

Ramli

Ali

2021

MJCS

View full text Add to dashboard Cite

In any form of traffic, whether it is physical or digital, the main problem that sparks a lot of interest for researchers is congestion. This paper discusses a study of congestion around toll plazas. A newly formulated model called Basic Traffic Unit (BTU) is introduced from previous research. BTU is a representation of a basic network connected to form a larger network. A simulation study is conducted and some queuing theories are applied to calculate the measure of performance. Two sets of data from different modes of toll payment are collected. The same two types of payments are simulated and the measure of performance is recorded. The two types of payments from the collected real data are used to calculate the measure of performance using the formula developed by the BTU. This study demonstrates that the results from simulated data can be used to compare with the results from the real-time data using the formula developed by a static model of BTU to predict possible congestions. Comparing results from both methods validates the claim that BTU is useful for predicting congestions.

show abstract

Section: Literature Reviewmentioning

confidence: 99%