Education Economic Transportation: Aplication of Geoinformation Technologi For The Transportation Demand Estimad
EDUCATION : Economic Transportation
Goodnight fellow steemit partner
allow me tonight to share the disciplines I have in economics. I will share transportation problems in big city cities and some solutions for better development
happy reading may be useful for our development and progress together in overcoming the problem of transportation stains
this time i will discuss about
Estimation Request
abstrak
One of topic issues in estimating transportation demands deals with gathering baseline data and development of transportation models subject to special trips generators, which include large objects of population gathering. Study of characteristics describing operation of such objects in conjunction with application of geoinformation databases can significantly improve the quality of transportation simulation and estimation of transportation demand in the area of special trips generators.
© 2017 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license
(http://creativecommons.org/licenses/by-nc-nd/4.0/).
Peer-review under responsibility of the organizing committee of the 12th International Conference “Organization and Traffic Safety
Management in large cities”
Keywords: transportation planning; transportation simulation; estimation of transportation demand; estimated transportation districts; special trips generators; generation of site visits; geoinformation databases
1. Main text
Development of activities on traffic management requires solutions on some transportation issues at the stage of transportation planning; one of the main challenges is estimating the transportation demand at the network level. The most common problem facing Russian engineers at the stage of transportation planning and simulation deals with the lack of updated source data required to evaluate the total volume of correspondence originating and disappearing in the target transportation areas. Another modern aspect is appearance of special focuses of population gatherings according to cultural and social purposes. In this regard, the modern transportation planning requires
consideration of several types of target transportation districts. Comparing to the Soviet period, when forecasting correspondence was carried out primarily on the basis of labor correspondence, and given characteristics of residential, commercial and industrial areas, now a lot of large commercial facilities have been open while more and more citizens use their own cars, which led to additional traffic loads on the urban traffic network. The working mode of such facilities is different from residential or commercial areas.
Thus, there appears a necessity to take into account special transportation districts (“transportation analysis zone
— TAZ”) in Russian transportation planning; these districts differ in the nature of daily distribution of trips to them in comparison with the total distribution of trips of citizens and have clear morning and evening rush hours (special trips generators).
Special trips generators require classification of design transportation districts into basic, special (may comprise individual objects and groups of related objects similar in terms of total trips generation to major transportation districts), or enlarged (areas of high business activity; development of such areas should focus on using public transport) [Casello and Smith (2006), State department of highways and public transportation (1975)].
Thus, the following matters should be considered by traffic engineers:
x way of description (mode of operation, daily distribution of trips, separation between public and individual transports) and simulation of special design transportation districts;
x way to collect the baseline data to simulate details of transportation model (macro-, meso- and micro-levels) for different cases.
Figure 1 shows an example of a task chain for transportation planning, starting from development of a local model of the road network for the site with a designed large-scale commercial facility, assessment of distribution of traffic flows within the facility site, and selection of planning decisions to access points of the investigated object.
Another example showing the importance of studying the mode of special trips generators (which include military, medical and educational institutions, as well as large commercial objects and any other urban areas under
planning) is the results of investigation of some facilities in Irkutsk, located along a transport corridor, traffic conditions of which affect the quality of transportation service of several districts of the city (Figure 2). Results of such studies provide an essential baseline data to develop the transportation model of an urban transport corridor (a main street, boulevard) and evaluate the transportation demand along it [Abrahamson (1998), Bell (1983)]
In order to increase the efficiency of urban traffic simulation on the basis of the study carried out by Transport research laboratory of Irkutsk National Research Technical University (INRTU) [Levashev (2013), Mikhailov (2000), Tebenkov et al. (2012), Levashev et al. (2013)], an approach allowing meeting all the challenges in assessing the transportation demand in different details was proposed. The approach involves factors of specific generators of various sites visiting and information about parameters of separate sites and facilities (territories and their distribution by types of objects: housing, commercial, administrative offices, etc.) and their geographical association within the boundaries of the territory studied.
The second component of the source data is supposed to be provided by importing geoinformation databases
such as 2GIS and OPEN STREET MAP (Figure 3).
Fig. 4. Distribution of separate objects by the level of visit generating in the center of Irkutsk and specification of their class.
Figure 4 shows distribution of separate objects in the center of Irkutsk taking into account the level of visits generating by each of the objects. The following issues are addressed on the basis of such distribution:
x quick collection of baseline data to assess the total volume of transport trips in target areas of any composition ;
x segregation of design transportation districts in order to improve the quality of transportation models and accuracy of estimation of transportation demand;
x selection of objects and groups of objects with a high level of total visits generating into special designed transportation areas;
x detailed assessment of transportation demand in the local traffic zone using a macro-model of the city.
Constant improvement and updating the existing geoinformation databases, as well as the data exchange interfaces between these databases and availability of specialized software for transportation simulation makes it possible to use this approach for to solve different tasks of transportation simulation. Alongside with that, improvements in application of such techniques require systematic accumulation of the source data and analysis of survey parameters characterizing working modes of special trips generators.
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