Abstract
This paper explores the travel time distribution of different types of urban roads, the link and path average travel time, and variance estimation methods by analyzing the large-scale travel time dataset detected from automatic number plate readers installed throughout Beijing. The results show that the best-fitting travel time distribution for different road links in 15 min time intervals differs for different traffic congestion levels. The average travel time for all links on all days can be estimated with acceptable precision by using normal distribution. However, this distribution is not suitable to estimate travel time variance under some types of traffic conditions. Path travel time can be estimated with high precision by summing the travel time of the links that constitute the path. In addition, the path travel time variance can be estimated by the travel time variance of the links, provided that the travel times on all the links along a given path are generated by statistically independent distributions. These findings can be used to develop and validate microscopic simulations or online travel time estimation and prediction systems.
Highlights
Traffic congestion during peak hours has become unavoidable in numerous cities worldwide because of the rapid increase in car ownerships and the lack of resources for proportionately increasing the supply capacity of road systems
A previous study [1] suggests that travel time reliability may be more important than travel time savings; that is, road users may choose a reliable route over an unreliable one despite the longer travel time of the former
The standard deviation estimation errors are mostly distributed within (–0.1, 0.1), accounting for over 85%; that is, under most traffic situations, the accuracy of the average travel time estimation and standard deviation estimation through normal distribution estimation for various road links is acceptable. These results suggest that the average travel time under most traffic situations can be estimated using normal distribution
Summary
Traffic congestion during peak hours has become unavoidable in numerous cities worldwide because of the rapid increase in car ownerships and the lack of resources for proportionately increasing the supply capacity of road systems This problem is causing travel time to be highly unreliable. Numerous cities have implemented various travel time direct measurement techniques, such as automatic number plate readers (ANPR), automated vehicle identification (AVI) systems, GPS-equipped vehicles, smart phone devices, and Bluetooth [3]. All of these techniques provide accurate individual vehicle travel time data for analysis.
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