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Public transport demand estimation by calibrating the combined trip distribution-mode choice (TDMC) model from passenger counts
Abstract
The conventional method to estimate the O-D matrices require very large surveys and very expensive. The need for inexpensive methods, which require low-cost data, generally called as 'unconventional method'. The development of techniques for calibrating the trip distribution models from traffic volumes to obtain the O-D matrices is well advanced. However, the previous research still in a burden condition of "All or Nothing" which is not realistic for some congested road networks in urban area. So, the main objective and contribution of this research is the estimation of origin-destination matrices by calibrating the combined gravity with multinomial logit under equilibrium assignment. The estimation methods, namely: Non-Linear-Least-Squares (NLLS) will be used to estimate the parameters of transport demand models. The combined model and its calibration method have been implemented. The model was able to obtain the calibrated parameters which can then be used for forecasting purposes. The advantageous and the applicability of the model are given.
... Transportation is a system consisting of activity, network, movement, institutional and environment, while urban as a system consisting of the economic, social-political and administrative (Kusbiantoro, 2004). Challenges and problems public transport passengers in Indonesia by (Tamin & Sulistyorini, 2009) them are undisciplined, driver transport owners want the maximum extent by, load passengers as much as possible through the exclusion of the interests of passengers from security and quick and passengers who want public transport available in many with a tariff, cheap fast, safe, and comfortable. ...
... Otros ejemplos son los modelos «probit», descriptivos de elección binaria y discreta: el conjunto de elección se reduce a 2 alternativas mutuamente excluyentes, registradas por cuestionarios sujetos a análisis estadístico, que permite realizar un análisis desagregado de las elasticidades de la demanda y del valor subjetivo del tiempo de los viajeros (Tamin y Sulistyorini, 2009). Las fuentes de información en modelos desagregados son las preferencias reveladas y las preferencias declaradas. ...
El sistema de tren ligero referido en el presente trabajo es un sistema eficiente y popular de transporte público que sirve en extensas áreas de la zona metropolitana del Valle de México. Encuestas a los pasajeros muestran que la demora en los trenes es el reto más importante a satisfacer. La demanda de pasajeros es el dato más relevante para la programación del servicio. Ha habido pocos intentos por abordar esta problemática: la carencia de información confiable ha sido una fuerte limitante. El propósito de esta investigación fue modelar la demanda diaria de pasajeros utilizando los datos obtenidos por los dispositivos de entrada (torniquetes) a las estaciones, prescindiendo de técnicas tradicionales para describir la afluencia de pasajeros. De manera que la investigación se orientó a obtener funciones de distribución continuas que se ajustaran a la demanda de pasajeros en una línea particular y sus estaciones. Se obtuvieron y analizaron datos correspondientes al flujo del año 2010 y se introdujeron en una base de datos compatible con software estadístico. Los modelos propuestos fueron obtenidos por estimación de máxima verosimilitud y corresponden a funciones de distribución de probabilidad continuas, con soporte en los reales positivos.
... They tested their model of generation–distribution–modal split–assignment on a small test network, and a medium-size real network in Italy, and reported very satisfactory results in reproducing the counted flows, as well as parameter values. Tamin and Sulistyorini [14] discussed some models of estimating transport demand based on passenger counts. They examined gravity type distribution and multinomial logit mode choice models, and attempted to estimate the combined model parameters using traffic counts on links, for a real case of 145 zones and 74 link counts on a network of 653 nodes and 2279 one-way links in Indonesia. ...
This paper introduces a new procedure to forecast the future O/D demand. It is a hybrid of logit and Fratar model. The hybrid model has the long run, policy sensitive, characteristic of a logit model, calibrated at sector-level with little/no zero O/D cells. This feature, joint with a Fratar-type operation at zonal level within a sector, gives a better performance to this model than either of the two types of the models alone. The performance of the hybrid model is contrasted with a neural network model, and shows encouraging results in a real case. Copyright © 2010 John Wiley & Sons, Ltd.
The paper is written based on research on 'Dynamic Origin-Destination Matrices From Real-Time Traffic Count Information'. The latest development in automatic traffic count data collection enables us to obtain the traffic count information in a real time or short-time-interval basis. For example, ATCS (Area Traffic Control System) already installed in several large cities in Indonesia, such as: DKI-Jakarta (since 1994), Bandung (since 1997), and Surabaya (since 1998) provided us the real-time or short-time-interval traffic count information for all signalised intersections. This traffic data is updated periodically in a short-time-interval basis (e.g. 5, 15, or 30 minutes time interval). This information is provided at the Traffic Control Centre (TCC) of ATCS project and can be directly and easily accessed at a very low cost through internet. This data is the main input for the short-time-interval Origin-Destination (OD) matrix estimation. Before this type of traffic data is used in the OD matrix estimation process; firstly, these data have to be processed in the Data Processing Interface (DPI). Having it processed; the traffic data will then be ready for estimating the short-time-interval OD matrices. The output of short-time-interval OD matrices together with several practical applications will be the main input for the Real-Time Integrated Traffic Information System (RITIS). This information will be stored in a Website designed specifically and informatively for the purposes of user needs (numerical and graphical). One of the most important information is the best routes from each origin zone to each destination zone which have already considered the effect of congestion. This information will be the main data for the development of the Route Guidance System (RGS) so that each driver can choose his best route through the road network. The best route information will be changed in a short-time-interval basis depending on the traffic condition. This short-time-interval traffic system information will become the public-domain information which can be directly and freely accessed through internet by the users (e.g. Planning Authorities, Traffic Authorities, Department of Public Works, Consultants, Police, drivers, radio stations, and TV stations, other related agencies, etc). Moreover, this approach can also be extended to provide the short-time-interval environmental information.
Having accepted the need for the development of simpler and less cumbersome transport demand models, the paper concentrates on one possible line for simplification: estimation of trip matrices from link volume counts. Traffic counts are particularly attractive as a data basis for modelling because of their availability, low cost and nondisruptive character. It is first established that in normal conditions it may be possible to find more than one trip matrix which, when loaded onto a network, reproduces the observed link volumes. The paper then identifies three approaches to reduce this underspecification problem and produce a unique trip matrix consistent with the counts. The first approach consists of assuming that trip-making behaviour can be explained by a gravity model whose parameters can be calibrated from the traffic counts. Several forms of this gravity model have been put forward and they are discussed in Section 3. The second approach uses mathematical programming techniques associated to equilibrium assignment problems to estimate a trip matrix in congested areas. This method can also be supplemented by a special distribution model developed for small areas. The third approach relies on entropy and information theory considerations to estimate the most likely trip matrix consistent with the observed flows. A particular feature of this group is that they can include prior, perhaps outdated, information about the matrix.
These three approaches are then compared and their likely areas for application identified. Problems for further research are discussed and finally an assessment is made of the possible role of these models vis-a-vis recent developments in transport planning.
The traffic model described has a simultaneous calculation of trip generation, trip distribution and assignment, giving a feedback from interzonal travel times to trip generation. The model is a rapid and inexpensive means of obtaining results with modified road networks and land-use patterns. The calibration method has been tested in a rural area.
This paper contains some suggestions on how to use traffic counts on links in networks and non-linear regression in order to estimate parameters in models for traffic prediction, for example gravity-distribution models. The suggested method has the advantage that it is straight-forward and does not require an O-D Survey which is usually very expensive.