Due to the increase in vehicle transit and congestion in road networks, providing information
about the state of the traffic to commuters has become a critical issue for Advanced Traveller …

Since the early 1980s, short-term traffic forecasting has been an integral part of most
Intelligent Transportation Systems (ITS) research and applications; most effort has gone into …

In the field of transportation, data analysis is probably the most important and widely used
research tool available. In the data analysis universe, there are two 'schools of thought'; the …

Short-term traffic prediction plays a critical role in many important applications of intelligent
transportation systems such as traffic congestion control and smart routing, and numerous …

In this paper, we discuss three problems that occur within short-term traffic prediction when
the information from only a single point loop detector is used. First, we analyze the retrieval …

Mobility services require accurate demand prediction in both space and time to effectively
manage fleet rebalancing, provide quick on-demand responses, and enable advanced ride …

Due to the nature of traffic itself, most traffic forecasting models reported in literature aim at
producing short-term predictions, yet their performance degrades when the prediction …

Burst passenger flow in the public transportation system is serious to public safety. Existing
works mainly focused on prediction and monitoring of regular passenger flow, which are not …

Time series techniques are useful for analyzing transportation data, uncovering past trends
and providing projections. Such analyses are sensitive to the temporal aggregation of the …

This study examines the spatiotemporal dependency between traffic links. We model the
traffic flow of 140 traffic links in a sub-network of the Minneapolis-St. Paul highway system for …