A review of travel time estimation and forecasting for advanced traveller information systems
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 …
about the state of the traffic to commuters has become a critical issue for Advanced Traveller …
Short-term traffic forecasting: Where we are and where we're going
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 …
Intelligent Transportation Systems (ITS) research and applications; most effort has gone into …
Statistical methods versus neural networks in transportation research: Differences, similarities and some insights
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 …
research tool available. In the data analysis universe, there are two 'schools of thought'; the …
Short-term traffic prediction based on dynamic tensor completion
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 …
transportation systems such as traffic congestion control and smart routing, and numerous …
The retrieval of intra-day trend and its influence on traffic prediction
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 …
the information from only a single point loop detector is used. First, we analyze the retrieval …
Improving deep-learning methods for area-based traffic demand prediction via hierarchical reconciliation
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 …
manage fleet rebalancing, provide quick on-demand responses, and enable advanced ride …
Adaptive long-term traffic state estimation with evolving spiking neural networks
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 …
producing short-term predictions, yet their performance degrades when the prediction …
Early warning of burst passenger flow in public transportation system
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 …
works mainly focused on prediction and monitoring of regular passenger flow, which are not …
Temporal aggregation in traffic data: implications for statistical characteristics and model choice
E Vlahogianni, M Karlaftis - Transportation Letters, 2011 - Taylor & Francis
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 …
and providing projections. Such analyses are sensitive to the temporal aggregation of the …
Spatiotemporal short-term traffic forecasting using the network weight matrix and systematic detrending
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 …
traffic flow of 140 traffic links in a sub-network of the Minneapolis-St. Paul highway system for …