@article{ref1,
title="Evaluating signalization and channelization selections at intersections based on an entropy method",
journal="Entropy (Basel, Switzerland)",
year="2019",
author="Shao, Yang and Han, Xueyan and Wu, Huan and Claudel, Christian G.",
volume="21",
number="8",
pages="e808-e808",
abstract="Direct left turns (DLTs) could cause traffic slowdown, delay, stops, and even  accidents on intersections, especially on no-median roads. Channelization and  signalization can significantly diminish negative impact of DLTs. In China, a total  of 56 large and medium-sized cities, including 17 provincial capitals, have adopted  vehicle restriction policies due to traffic congestion, vehicle energy conservation  and emission reduction, which cause travel inconvenience for citizens. This paper  mainly studies signalization and channelization selections at intersections based on  an entropy method. Based on the commonly used three evaluation indexes, the number  of vehicles, CO emissions and fuel consumption have been added. The entropy  evaluation method (EEM) method is innovatively used to objectively calculate the  weight of the six indexes, which carry out the optimal traffic volume combinations  for intersections of present situation, channelization and signalization. A VISSIM  simulation is also used to evaluate the operating status of three conditions. The  results show that EEM could help enormously in choosing different methods at a  certain intersection. With the EEM, six indexes decrease by 20-70% at most.<p /> <p>Language: en</p>",
language="en",
issn="1099-4300",
doi="10.3390/e21080808",
url="http://dx.doi.org/10.3390/e21080808"
}