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Analysis of residents' travel characteristics along beijing rail transit line based on binary choice model

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Języki publikacji
EN
Abstrakty
EN
From ancient to modern times, in the historical process of urban development, urban transportation has been developing along with the development of the city's political, economic and cultural industries, and the relationship between each other has always been a topic constantly discussed by planning scholars. The development of urban transportation promotes the urban population gathering and industrial development, and promotes the development of urban geographical space. At the same time, it also brings endless convenience to urban residents, so that they can complete the displacement from the beginning to the destination with relatively low cost. However, with the rapid development of urban scale and the rapid growth of urban population, the problems of traffic congestion and land resource shortage in big cities of China seriously restrict the improvement of the quality of life of residents and the further development of the city. In this context, compact city is the inevitable choice for future urban development, while the transportation system supporting compact city form can only be public transportation. As a high-volume, efficient and rapid public transport mode, rail transit can not only solve the traffic congestion problem in high-density areas of cities, but also optimize the development and utilization of urban land and adjust the urban spatial layout, which is of great significance for the sustainable development of cities. The network of rail transit in Beijing becomes the backbone of public passenger transport system, and play an irreplaceable role in guiding the urban space layout adjustment, population migration and the transformation of traffic structure. The study of travel characteristics of the residents who live along the rail transit, in-depth analysis the relationship of the rail transit, the population migration and commuter travel, it is of great significance providing decision support for urban planning. Based on binary choice model, establishing the residents' travel choice model, rail transit impact model of different crowds. Study the relationship between rail transit and residents' travel characteristics, predict the rail transit to guide the trend of population migration.
Rocznik
Strony
19--27
Opis fizyczny
Bibliogr. 23 poz., rys., wzory
Twórcy
autor
  • Architecture School, Tianjin University, Tianjin, China
autor
  • Architecture School, Tianjin University, Tianjin, China
Bibliografia
  • [1] AMBROZIAK, T. & JACYNA, M., 2002. Queueing theory approach to transport process dynamics. Part 1. Dynamics of transport network connections. Archives of Transport, 14(4), pp. 5-20.
  • [2] CHMIELEWSKI, J. & SZCZURASZEK, T., 2004. Simulation model of distribution of passenger traffic streams into public transport lines. Archives of Transport, 16(4), pp. 5-23.
  • [3] COM, 2007. Green paper. Towards a new culture of urban mobility. Brussels.
  • [4] COM, 2011. White paper 2011. Roadmap to a Single European Transport Area - Towards a competitive and resource efficient transport system. Brussels.
  • [5] DEGANG, D. & FAN, Z., 2013. Study on the classification of urban rail stations from the per-spective of land use optimization. Urban Planning, 9, pp. 39-45.
  • [6] FANYU, M. & WENBIN, F., 2007. Study on the spatial coordination of urban living and employment. Urban Development Research, 62(4), pp. 387-396.
  • [7] GARLING, T. & STEG, L., 2007. Threats from car traffic to the quality of urban life. Oxford: Elsevier.
  • [8] JACYNA, M., 1999. Multicriteria evaluation of traffic flow distribution in a multimodal transport corridor, taking into account logistics base service. Archives of Transport, 11(3-4), pp. 43-66.
  • [9] JACYNA, M., 2009. Modelowanie i ocena systemów transportowych. Warsaw: Oficyna Wydawnicza Politechniki Warszawskiej.
  • [10] JACYNA, M. & MERKISZ, J., 2014. Proecological approach to modelling traffic organization in national transport system. Archives of Transport, 30(2), pp. 31-42.
  • [11] JACYNA, M., WASIAK, M., LEWCZUK, K. & KLODAWSKI, M., 2014. Simulation model of transport system of Poland as a tool for developing sustainable transport. Archives of Transport, 31(2), pp. 17-30.
  • [12] JIAN, F. & YIXING, Z., 2004. The internal relocation of Beijing city and related space behavior in the process of suburbanization. Geographical Research, 3(2), pp. 227-242.
  • [13] JINGSHUAI, Y. & DIANYE, Z., 2008. Study on reasonable attraction of urban rail transit stations. Urban Rail Transit, 3, pp. 72-75.
  • [14] LEE, Y., KIM, K. H., RHO, J. H., et al., 2016. Investigation on aerodynamic drag of Korean high speed train due to roof apparatus for electrical device. Journal of Mechanical Science and Technology, 30(4), pp. 1611-1616.
  • [15] LOUKOPOULOS, P., 2007. A classification of travel demand management measures. In: GARLING, T., STEG, L. Threats from car traffic to the quality of urban life: problems, causes and solutions. Oxford: Elsevier, pp. 275-292.
  • [16] MEYER, M. D., 1999. Demand management as an element of transportation policy: using carrots and sticks to influence travel behaviour. Transportation Research Part A, 33, pp. 575- 599.
  • [17] PAZ, C., SUÁREZ, E., GIL, C., et al., 2015. Numerical study of the impact of windblown sand particles on a high-speed train. Journal of Wind Engineering and Industrial Aerodynamics, 145, pp. 87-93.
  • [18] STRADLING, S. G., MEADOWS, M. L. & BEATTY, S., 2000. Helping drivers out of their cars. Integrating transport policy and social psychology for sustainable change. Transport Policy, 7, pp. 207-215.
  • [19] TAYLOR, M. A. P. & AMPT, E. S., 2003. Travelling smarter down under: Policies for voluntary travel behaviour change in Australia. Transport Policy, 10, pp. 165-177.
  • [20] TUANSHENG, C., 2007. Study on characteristics and analysis methods of commuting behavior of commuters. Beijing Jiaotong University, pp. 30-37.
  • [21] YANFANG, Z., LEISHAN, Z. & YIXIANG, L., 2010. Study on the influence of traffic flow in urban rail transit. Integrated Transport, 6, pp.67-70.
  • [22] YUAN, C., WU, Q., YUAN, H. & FENG, Z., 2014. Optimization of Urban Public Transport Network Considering Rail Transit Interaction Effect. Journal of Highway & Transportation Research & Development, 31(8), pp. 119-125.
  • [23] ZOCHOWSKA, R. & KARON, G., 2016. ITS Services Packages as a Tool for Managing Traffic Congestion in Cities. In: A. SLADKOWSKI and W. PAMULA, eds., Intelligent Transportation Systems-Problems and Perspectives. Springer International Publishing, pp. 81 -103.
Uwagi
PL
Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2019).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-4a18058c-d781-44ae-89e9-73887443e667
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