A brief overview of machine learning methods for short-term traffic forecasting and future directions
Short-term traffic forecasting is a vital part of intelligent transportation systems. Recently, the
combination of unprecedented data availability and the repaid development of machine …
combination of unprecedented data availability and the repaid development of machine …
Multi-task representation learning for travel time estimation
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 …
trip given the origin location, destination location as well as the departure time. Most existing …
HetETA: Heterogeneous information network embedding for estimating time of arrival
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 …
which involves the spatiotemporal data. Despite a significant amount of prior efforts have …
Price-aware real-time ride-sharing at scale: an auction-based approach
Real-time ride-sharing, which enables on-the-fly matching between riders and drivers (even
en-route), is an important problem due to its environmental and societal benefits. With the …
en-route), is an important problem due to its environmental and societal benefits. With the …
Reinforced spatiotemporal attentive graph neural networks for traffic forecasting
The advances in the Internet of Things (IoT) and increased availability of the road sensors
allow for fine-grained traffic forecasting, which is of particular importance toward building an …
allow for fine-grained traffic forecasting, which is of particular importance toward building an …
Last-mile delivery made practical: An efficient route planning framework with theoretical guarantees
Last-mile delivery (LMD) refers to the movement of goods from transportation origins to the
final destinations. It has widespread applications such as urban logistics, e-commerce, etc …
final destinations. It has widespread applications such as urban logistics, e-commerce, etc …
Task matching and scheduling for multiple workers in spatial crowdsourcing
A new platform, termed spatial crowdsourcing, is emerging which enables a requester to
commission workers to physically travel to some specified locations to perform a set of …
commission workers to physically travel to some specified locations to perform a set of …
Spatial-temporal graph convolution network model with traffic fundamental diagram information informed for network traffic flow prediction
Accurate and fine-grained traffic state prediction has always been an important research
field. For long-term traffic flow prediction, the high-dimensional and coupled traffic feature …
field. For long-term traffic flow prediction, the high-dimensional and coupled traffic feature …
Origin-destination travel time oracle for map-based services
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 …
travel time oracle~(ODT-Oracle) returns an estimate of the time it takes to travel from O to D …
Task selection in spatial crowdsourcing from worker's perspective
With the progress of mobile devices and wireless broadband, a new eMarket platform,
termed spatial crowdsourcing is emerging, which enables workers (aka crowd) to perform a …
termed spatial crowdsourcing is emerging, which enables workers (aka crowd) to perform a …