RT Journal Article
A1 Jing Guo
A1 Yaoxin Wu
A1 Xuexi Zhang
A1 Le Zhang
A1 Wei Chen
A1 Zhiguang Cao
A1 Lu Zhang
A1 Hongliang Guo

PB iet
T1 Finding the ‘faster’ path in vehicle routing
JN IET Intelligent Transport Systems
VO 11
IS 10
SP 685
OP 694
AB 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.
K1 binormal distribution modelling
K1 real traffic data
K1 probability density function
K1 theoretical models
K1 bidelta distribution
K1 artificial network
K1 road link
K1 link travel time
K1 vehicle routing
K1 arbitrary path
K1 real road network
DO https://doi.org/10.1049/iet-its.2016.0288
UL https://digital-library.theiet.org/;jsessionid=3nsli0cfv7vke.x-iet-live-01content/journals/10.1049/iet-its.2016.0288
LA English
SN 1751-956X
YR 2017
OL EN