Open AccessFinding the ‘faster’ path in vehicle routing
Author(s) -
Guo Jing,
Wu Yaoxin,
Zhang Xuexi,
Zhang Le,
Chen Wei,
Cao Zhiguang,
Zhang Lu,
Guo Hongliang
Publication year - 2017
Publication title -
iet intelligent transport systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.579
H-Index - 45
eISSN - 1751-9578
pISSN - 1751-956X
DOI - 10.1049/iet-its.2016.0288
Subject(s) - vehicle routing problem , path (computing) , computer science , equal cost multi path routing , routing (electronic design automation) , transport engineering , computer network , link state routing protocol , engineering , routing protocol
In this study, the authors improve the faster criterion in vehicle routing by extending the bi‐delta distribution to the bi‐normal distribution, which is a reasonable assumption for travel time on each road link. Based on this assumption, theoretical models are built for an arbitrary path and subsequently adopted to evaluate two candidate paths through probabilistic comparison. Experimental results demonstrate the bi‐normal behaviour of link travel time in practice, and verify the faster criterion's superiority in determining the optimal path either on an artificial network with bi‐normal distribution modelling link travel time or on a real road network with real traffic data. This study also validates that when the link number of one path is large, the probability density function of the whole path can be simplified by a normal distribution which approximates the sum of bi‐normal distributions for each link.