Journal Article10.1109/TITS.2006.869629
Dynamic origin-destination demand estimation using automatic vehicle identification data
Xuesong Zhou,Hani S. Mahmassani +1 more
232
TL;DR: A dynamic origin-destination (OD) estimation method to extract valuable point-to-point split-fraction information from automatic vehicle identification (AVI) counts without estimating market-penetration rates and identification rates of AVI tags is proposed.
read more
Abstract: This paper proposes a dynamic origin-destination (OD) estimation method to extract valuable point-to-point split-fraction information from automatic vehicle identification (AVI) counts without estimating market-penetration rates and identification rates of AVI tags. A nonlinear ordinary least-squares estimation model is presented to combine AVI counts, link counts, and historical demand information into a multiobjective optimization framework. A joint estimation formulation and a one-sided linear-penalty formulation are further developed to take into account possible identification and representativeness errors, and the resulting optimization problems are solved by using an iterative bilevel estimation procedure. Based on a synthetic data set, this study shows the effectiveness of the proposed estimation models under different market-penetration rates and identification rates
read more
Chat with Paper
AI Agents for this Paper
Find similar papers on Google Scholar, PubMed and Arxiv
Write a critical review of this paper
Analyze citations of this paper to find unaddressed research gaps
Citations
Estimating Origin-Destination Flows Using Mobile Phone Location Data
TL;DR: Using an algorithm to analyze opportunistically collected mobile phone location data, the authors estimate weekday and weekend travel patterns of a large metropolitan area with high accuracy.
Traffic Flow Prediction for Road Transportation Networks With Limited Traffic Data
TL;DR: This paper first uses a dynamic traffic simulator to generate flows in all links using available traffic information, estimated demand, and historical traffic data available from links equipped with sensors, and implements an optimization methodology to adjust the origin-to-destination matrices driving the simulator.
370
PEV Fast-Charging Station Siting and Sizing on Coupled Transportation and Power Networks
TL;DR: A mixed-integer linear programming model is formulated for PEV fast-charging station planning considering both transportation and electrical constraints based on CFRLM, which can be solved by deterministic branch-and-bound methods.
318
Contextualized Spatial–Temporal Network for Taxi Origin-Destination Demand Prediction
TL;DR: Wang et al. as discussed by the authors proposed a contextualized spatial-temporal network (CSTN), which consists of three components for the modeling of local spatial context, temporal evolution context, and global correlation context.
248
iBOAT: Isolation-Based Online Anomalous Trajectory Detection
TL;DR: The proposed isolation-based online anomalous trajectory (iBOAT) is evaluated through extensive experiments on large-scale taxi data, and it shows that iBOAT achieves state-of-the-art performance, with a remarkable performance of the area under a curve (AUC) ≥ 0.99.
221
References
Dynamic network traffic assignment and simulation methodology for advanced system management applications
TL;DR: A dynamic traffic assignment (DTA) system for advanced traffic network management is described, built around a traffic simulation-assignment modeling framework, which describes the evolution of traffic patterns in the network for given traffic loading under particular control measures and route guidance information supply strategies to individual motorists.
459
Dynamic Estimators of Origin-Destination Matrices Using Traffic Counts
TL;DR: Different “dynamic” estimators using time-varying traffic counts to obtain (discrete) time- varying OD flows or average OD flows are proposed and tested on the Italian Brescia–Padua motorway, showing that also in the “no a priori information” case significant estimates could be obtained.
406
A new class of dynamic methods for the identification of origin-destination flows
M. Cremer,H. Keller +1 more
TL;DR: Four different methods were developed: an ordinary least squares estimator involving cross-correlation matrices, a constrained optimization method, a simple recursive estimation formula and estimation by Kalman filtering, which are particularly useful for tracking time-variable O-D patterns for on-line identification and control purposes.
297
Recursive estimation of time-varying origin-destination flows from traffic counts in freeway corridors
Gang-Len Chang,Jifeng Wu +1 more
TL;DR: A dynamic system model and its on-line estimation algorithm for time-varying freeway origin-destination (O-D) matrices offers a promising direction for tackling this complex issue.
149
Real-time od estimation using automatic vehicle identification and traffic count data
TL;DR: Results show that using prior observed OD data along with link counts improves estimator accuracy relative to OD estimation based exclusively on link counts, and shows that the incorporation of constraints creates estimators that are less sensitive to limitations such as deterministic modeling errors, unreliable OD data, and assignment error.
111