Open AccessJournal Article
Estimating Link Travel Time Correlation: An Application of Bayesian Smoothing Splines
TLDR
A Bayesian based methodology is developed for estimating the posterior distribution of the correlation of travel times between links along a corridor.Abstract:
The estimation and forecasting of travel times has become an increasingly important topic as Advanced Traveler Information Systems (ATIS) have moved from conceptualization to deployment. This paper focuses on an important, but often neglected, component of ATIS - the estimation of link travel time correlation. Natural cubic splines are used to model the mean link travel time. Subsequently, a Bayesian based methodology is developed for estimating the posterior distribution of the correlation of travel times between links along a corridor. The approach is illustrated on a corridor in Houston, Texas, that is instrumented with an Automatic Vehicle Identification system.read more
Citations
More filters
Journal ArticleDOI
Reliable shortest path finding in stochastic networks with spatial correlated link travel times
TL;DR: A case study using real-world data shows that link travel times are only strongly correlated within the local impact areas; and the proposed limited spatial dependence assumption can well approximate path travel time variance when the size of the impact area is sufficiently large.
Journal ArticleDOI
Continuum modeling of park-and-ride services considering travel time reliability and heterogeneous commuters - A linear complementarity system approach
Bo Du,David Z.W. Wang +1 more
TL;DR: In this article, the authors studied the modeling of multimodal choice in a highway/railway system with continuum park-and-ride services along a corridor, while both auto and rail transit are subject to congestion effects.
Journal ArticleDOI
Application of Lagrangian relaxation approach to α-reliable path finding in stochastic networks with correlated link travel times
TL;DR: In this article, the authors investigated the important problem of determining a reliable path in a stochastic network with correlated link travel times, and the Lagrangian relaxation based framework was used to handle the α-reliable path problem, by which the intractable problem with a non-linear and non-additive structure can be decomposed into several easy-to-solve problems.
Journal ArticleDOI
Lagrangian relaxation for the reliable shortest path problem with correlated link travel times
TL;DR: A novel LR approach based on a new convex problem reformulation, and new methods to update Lagrangian multipliers and handle negative cycles of the resulting shortest path problems are proposed.
Journal ArticleDOI
Exploring traffic congestion correlation from multiple data sources
TL;DR: A three-phase framework to explore the congestion correlation between road segments from multiple real world data finds some important patterns that lead to a high/low congestion correlation, and they can facilitate building various transportation applications.
References
More filters
Book
Bayesian Data Analysis
TL;DR: Detailed notes on Bayesian Computation Basics of Markov Chain Simulation, Regression Models, and Asymptotic Theorems are provided.
BookDOI
Markov Chain Monte Carlo in Practice
TL;DR: The Markov Chain Monte Carlo Implementation Results Summary and Discussion MEDICAL MONITORING Introduction Modelling Medical Monitoring Computing Posterior Distributions Forecasting Model Criticism Illustrative Application Discussion MCMC for NONLINEAR HIERARCHICAL MODELS.
BookDOI
Nonparametric regression and generalized linear models
TL;DR: In this paper, the authors propose that having more aspects to know and understand will lead to becoming a more precious person, and becoming more precious can be situated with the presentation of how your knowledge much.
Book
Nonparametric Regression and Spline Smoothing
TL;DR: A unified account of the most popular approaches to nonparametric regression smoothing can be found in this article, including boundary corrections for trigonometric series estimators, detailed asymptotics for polynomial regression, testing goodness-of-fit, estimation in partially linear models, practical aspects, problems and methods for co