Dynamic Demand Input Preparation for Planning Applications

作者: Klayut Jintanakul

DOI:

关键词: Sampling (statistics)Dynamic demandComputer scienceMicrosimulationMathematical modelMathematical optimizationSimulationMonte Carlo methodTraffic engineeringTransportation planningTraffic simulation

摘要: Author(s): Jintanakul, Klayut | Abstract: A spectrum of traffic engineering and modern transportation planning problems requires the knowledge underlying trip pattern, commonly represented by dynamic Origin- Destination (OD) tables. In view fact that direct survey pattern is technically problematic economically infeasible, there have been a great number methods proposed in literature for updating existing OD tables from counts and/or other data sources. Unfortunately, remain several common theoretical practical aspects which impact estimation accuracy limit use these most real-world applications. This dissertation itemizes examines critical issues. Then, presents developments, evaluations, applications two new frameworks intended to be used with current near-future data, respectively.The first framework offers systematic procedure preparing demand inputs microscopic simulation under an module based solely on counts. Under this framework, traditional model augmented filter step, captures important spatial-temporal characteristics route patterns within large surrounding network, improve flow estimates entering leaving final network. bounded solution algorithm solving problem are also proposed.The second utilizes additional information small probe samples collected over multiple days. There steps framework. The step includes suite empirical hierarchical Bayesian models estimating time dependent travel distributions, destination fractions, fractions data. These provide multi-level posterior parameters tend moderate extreme toward overall mean magnitude depending their precision, thus overcoming due non-uniform (over space) sampling rates. involves construction initial tables, route-link via Monte Carlo simulation, using formulation can take into account stochastic properties assignment matrix.

参考文章(68)
Jean Diebolt, Christian P. Robert, Estimation of Finite Mixture Distributions Through Bayesian Sampling Journal of the Royal Statistical Society: Series B (Methodological). ,vol. 56, pp. 363- 375 ,(1994) , 10.1111/J.2517-6161.1994.TB01985.X
M Cremer, H Keller, A SYSTEMS DYNAMICS APPROACH TO THE ESTIMATION OF ENTRY AND EXIT O-D FLOWS Papers presented during the Ninth International Symposium on Transportation and Traffic Theory held in Delft the Netherlands, 11-13 July 1984.. ,(1984)
Hani S Mahmassani, Hossein Tavana, ESTIMATION OF DYNAMIC ORIGIN-DESTINATION FLOWS FROM SENSOR DATA USING BI-LEVEL OPTIMIZATION METHOD Transportation Research Board 80th Annual Meeting. ,(2001)
S Nguyen, ESTIMATING ORIGIN DESTINATION MATRICES FROM OBSERVED FLOWS Publication of: Elsevier Science Publishers BV. ,(1984)
Folke Snickars, Jörgen W. Weibull, A minimum information principle Regional Science and Urban Economics. ,vol. 7, pp. 137- 168 ,(1977) , 10.1016/0166-0462(77)90021-7