Intelligent transportation (eg, intelligent traffic light) makes our travel more convenient and
efficient. With the development of mobile Internet and position technologies, it is reasonable …

Abstract Machine learning (ML) plays the core function to intellectualize the transportation
systems. Recent years have witnessed the advent and prevalence of deep learning which …

One crucial task in intelligent transportation systems is estimating the duration of a potential
trip given the origin location, destination location as well as the departure time. Most existing …

The estimated time of arrival (ETA) is a critical task in the intelligent transportation system,
which involves the spatiotemporal data. Despite a significant amount of prior efforts have …

In this paper, we study the problem of origin-destination (OD) travel time estimation where
the OD input consists of an OD pair and a departure time. We propose a novel neural …

Estimating the travel time of a path is of great importance to smart urban mobility. Existing
approaches are either based on estimating the time cost of each road segment which are …

Origin-destination (OD) matrices are used widely in transportation and logistics to record the
travel cost (eg, travel speed or greenhouse gas emission) between pairs of OD regions …

Given an origin (O), a destination (D), and a departure time (T), an Origin-Destination (OD)
travel time oracle~(ODT-Oracle) returns an estimate of the time it takes to travel from O to D …

Online food ordering and delivery service has widely served people's daily demands
worldwide, eg, it has reached a number of 34.9 million online orders per day in Q3 of 2020 …

Materializing views is an important method to reduce redundant computations in DBMS,
especially for processing large scale analytical queries. However, many existing methods …