Paper Info
Title
Assessing the Accuracy Benefits of On-the-Fly Trajectory Selection in Fine-Grained Travel-Time Estimation
Abstract
Today's one-size-fits-all approach to travel-time computation in spatial networks proceeds in two steps. In a preparatory off-line step, a set of distributions, e.g., one per hour of the day, is computed for each network segment. Then, when a path and a departure time are provided, a distribution for the path is computed on-line from pertinent pre-computed distributions. Motivated by the availability of massive trajectory data from vehicles, we propose a completely on-line approach, where distributions are computed from trajectories on-the-fly, i.e., when a query arrives. This new approach makes it possible to use arbitrary sets of underlying trajectories for a query. Specifically, we study the potential for accuracy improvements over the one-size-fits-all approach that can be obtained using the on-the-fly approach and report findings from an empirical study that suggest that the on-the-fly approach is able to improve accuracy significantly and has the potential to replace the current one-size-fits-all approach.
Year
DOI
Venue
2017
10.1109/MDM.2017.40
2017 18th IEEE International Conference on Mobile Data Management (MDM)
Keywords
Field
DocType
accuracy benefits assessment,on-the-fly trajectory selection,fine-grained travel-time estimation,one-size-fits-all approach,travel-time computation,spatial networks,preparatory offline step,departure time,path distribution,trajectory data,vehicles,query,on-the-fly approach
Data mining,Histogram,Network segment,Convolution,Computer science,On the fly,Global Positioning System,Trajectory,Empirical research,Computation
Conference
ISSN
ISBN
Citations 
1551-6245
978-1-5386-3933-7
1
PageRank 
References 
Authors
0.39
10
4
Name
Order
Citations
PageRank
Robert Waury111.06
Jilin Hu2745.69
Bin Yang370634.93
Christian S. Jensen4106511129.45