بررسی اثر متغیرهای حمل‌ونقلی بر تغییر استفاده از شیوه سواری شخصی در سفرهای روزانه

حبیبیان, میقات; کرمانشاه, محمد

بررسی اثر متغیرهای حمل‌ونقلی بر تغییر استفاده از شیوه سواری شخصی در سفرهای روزانه

نوع مقاله : علمی - پژوهشی

نویسندگان

¹ دانشکده مهندسی عمران، دانشگاه صنعتی امیرکبیر

² دانشکده مهندسی عمران، دانشگاه صنعتی شریف

چکیده

سیاست گذاران حمل‏ و‏نقل برای بهبود شرایط حمل‏ و‏نقلی جامعه سیاست هایی را اتخاذ می‏کنند، حال آنکه شهروندان در رویارویی با این سیاستها، تصمیماتی را برای بهبود شرایط سفر خود اتخاذ می‏کنند. مطالعات متعددی بیانگر آن است که این تصمیمات غالباً منجر به تحقق نیافتن پیش بینی‌های سیاست‌گذاران، در تجویز سیاستهای مدیریتی حمل‌ونقل برای جامعه می‏شود. در این مقاله با استفاده از رویکردی رفتاری، به بررسی نقش متغیرهای حمل‌ ونقلی در تغییر وسیله استفاده کنندگان از سواری شخصی در سفرهای روزانه به محدوده مرکزی شهر تهران، پرداخته شده است. در این رویکرد با استفاده از مبانی طراحی آزمایش و مدلهای لوجیت، نقش متغیرهای مؤثر بر تغییر شیوه سفر از وسیله نقلیه شخصی به هفت طریقه جایگزین در اثر اعمال سیاست های مدیریت تقاضای حمل‌ ونقل بررسی شده است. بر این اساس متغیرها به دو دسته متغیرهای حمل‌ ونقلی و متغیرهای غیر حمل‌ ونقلی تقسیم شده اند که نتایج مدل‌ها بیانگر آن است که در تمامی طریقه‌های سفر مورد بررسی، نقش متغیرهای غیر حمل‌ ونقلی پررنگ تر است. این مطالعه نشان می‏ دهد که بیشترین سهم متغیرهای حمل‌ ونقلی، در انتخاب گزینه‌های همگانی با دسترسی پیاده با متوسط 43 درصد و تاکسی با متوسط 31 درصد است. پس از آن، موتورسیکلت با 12 درصد، همگانی با دسترسی‌های شخصی و تاکسی هرکدام با 10 درصد قرار داشته و گزینه‌های تاکسی تلفنی و تاکسی با دسترسی شخصی نیز به ترتیب با پنج درصد و یک درصد در مراتب بعدی قرار دارند.

کلیدواژه‌ها

20.1001.1.20086598.1394.7.1.2.4

عنوان مقاله [English]

Contribution of Travel-Related Variables to Car Commuters’ Mode Change

نویسندگان [English]

Mighat Habibian ¹
Mohammad Kermanshah ²

چکیده [English]

Traffic congestion as a source of daily delays, degradation of environmental quality, and nonrenewable energy consumption is said to be a major trouble in most of the world’s cities. Being discontent about traffic congestion usually persuades transportation policymakers to propose measures to reduce it. Many studies have shown that individuals’ responses to urban traffic congestion, as usually assumed by policymakers, are significantly different from their respected actual behavior. This paper adopts a behavioral approach to examine the role of travel-related variables on the mentioned difference using design of experiments principles and logit models. In this approach, five policies namely cordon pricing, parking pricing, increasing fuel cost, transit time reduction, and transit access time reduction were investigated. This study uses the stated preferences of individuals who regularly use their private cars to access their job locations in the Tehran central area to calibrate seven models of non-car mode consideration. Furthermore, the role of travel-related variables is also addressed in such mode change. Analysis of the effects of the travel related variables in considering non-car modes shows that the contribution of socio-economic variables are greater than travel-related variables in all of the investigated modes. The results show that while the contribution of travel-related variables is 43% for walk and ride considerers and 31% for taxi considerers, it is 12% for considering motorcycle, 10% for public transit accessed by either car or taxis, 5% for taxi caught by phone and 1% for taxi accessed by car.

کلیدواژه‌ها [English]

Travel-related variables
Transportation demand management
mode choice model
stated preferences
goodness of fit index

مراجع

-Anon. (2012) “World Data Bank” [Online] Available at: http://databank.worldbank.org/ddp/html-jsp/QuickViewReport.jsp?RowAxis=WDI_Ctry~andColAxis=WDI_Time~andPageAxis=WDI_Series~andPageAxisCaption=Series~andRowAxisCaption=Country~andColAxisCaption=Time~andNEW_REPORT_SCALE=1andNEW_REPORT_PRECISION=0andnewReport=yesandIS_REPORT_ [Accessed 22 July 2012].
-Britannica Online Encyclopedia (2012) “Tehran (Iran) : Introduction”, [Online] Available at: http://www.britannica.com/EBchecked/topic/585619/Tehran [Accessed 21 May 2012].
-Choo, S. and Mokhtarian., P. L. (2007) “Individual response to congestion policies: Modeling consideration of factor-based travel related strategy bundles”, In TRB 86th Annual Meeting Compendium of Papers. CD-ROM. Washington, D.C., 2007. Transportation Research Board of the National Academies.
-Colombo, S., Hanley, N. and Calatrava-Requena, J. (2005) “Designing policy for reducing the off-farm effects of soil erosion using choice experiments”, Journal of Agricultural Economics, 56(1), pp.81-95.
-Eriksson, L., Garvill, J. and Nordlund, A.M. (2008)”Acceptability of single and combined transport policy measures: The importance of environmental and policy specific beliefs”, Transportation Research Part A, 42, pp.1117–1128.
-Eriksson, L., Nordlund, A. M. and Garvill, J. (2010) “Expected car use reduction in response to structural travel demand management measures”, Transportation Research Part F, 13, pp.329–342.
-Giaoutzi, M. and Daminides, L. (1990) “The Greek transport system and environment”, In Button, J.B.a.K. Transport policy and the environment: Six Case Studies. London: Earthscan.
-Graham-Rowe, E., Skippon, S., Gardner, B. and Abraham, C. (2011) “Can we reduce car use and, if so, how? A review of available evidence”, Transportation Research Part A, 45, pp.401-18.
-Habibian, M. (2011) “Designation and assessment of integrated transportation damend management policies”, Ph.D Dissertation. Tehran: Sharif University of Technology.
-Habibian, M., (2012) “Exploring the role of TDM policies on car commuters’ mode change: Subjective vs. Objective Approach”, In Safavi, H.R., ed. 9th International Congress on Civil Engineering. Isfahan, 2012.
-Habibian, M. and Kermanshah, M. (2011) “Exploring the role of transportation demand management policies’ interactions”, Scientia Iranica, 18(5), pp.1037-44.
-Habibian, M. and Kermanshah, M. (2012) “Investigating the contribution of transportation demand management policies to car commuters’ mode change”, Journal of Transportation Engineering, 3(3), pp.181-98.
-Habibian, M. and Kermanshah, M. (In press) “Car commuters’ mode choice in response to TDM measures: Experimental design approach considering two-way interactions”, Iranian Journal of Science and Technology.
-Hauser, J. R. (1978) “Testing the accuracy, usefulness, and significance of probabilistic choice models: An information theoretic approach”, Operations Research, 26(3), pp.406-21.
-Hensher, D. A., Rose, J. M. and Greene, W.H. (2005) “Applied choice analysis, A primer”, New York: Cambridge University Press.
-Iranian Center of Statistics (ICS), (2009) “Information of Iranian States”, [Online] Available at: http://www.amar.org.ir/Upload/Modules/Contents/asset16/tehran/tehpart.html [Accessed 13 November 2009].
-Jakobsson, C., Fujii, S. and Garling, T. (2000) “Determinants of private car users’ acceptance of road pricing”, Transport Policy, 7(2), pp.153–158.
-Litman, T. (2005) “Transportation cost and benefit analysis”, [Online] Available at: http://www.vtpi.org/tca [Accessed September 25 2006].
-Litman, T. (2013) “Online TDM Encyclopedia”, [Online] Available at: http:www.vtpi.org [Accessed 2 February 2013].
-Li, J., Walker, J. L. and Srinivasan, S. (2010) “Modeling private car ownership in China: Investigating the impact of urban form across mega-cities”, In Proceeding of the 89th Annual Transportation Research Board Meeting, CD-ROM. Washington D.C., 2010.
-Loukopoulos, P. (2005) “Future urban sustainable mobility: Implementing and understanding the impacts of policies designed to reduce private automobile usage”, Doctoral dissertation. Gothenburg, Sweden: Goteborg University.
-Mokhtarian, P. L., Raney, E. A. and Salomon, I. (1997) “Behavioral response to congestion: Identifying patterns and socio-economic differences in adoption”, Transport Policy, 4(3), pp.147-60.
-O’Fallon, C., Sullivan, C. and Hensher, D. A. (2004) “Constraints affecting mode choices by morning car commuters”, Transport Policy, 11, pp.17-29.
-Raney, E. A., Mokhtarian, P. L. and Salomon, I. (2000) “Modeling individuals’ consideration of strategies to cope with congestion”, Transportation Research Part F, 3(3), pp.141-65.
-Salomon, I. and Mokhtarian, P. L. (1997) “Coping with congestion: Understanding the gap between policy assumptions and behavior”, Transportation Research D, 2(2), pp.107-23.
-Schade, J. and Schlag, B. (2003) “Acceptability of urban transport pricing strategies”, Transportation Research F, 6, pp.45-61.
-Tertoolen, G., Van Kreveld, D. and Verstraten, B. (1998) “Psychological resistance against attempts to reduce private car use”, Transportation Research A, 32(3), pp.171-81.
-Trading economics (2012) “Passenger cars (per 1;000 people) in Iran”, [Online] Available at: http://www.tradingeconomics.com/iran/passenger-cars-per-1-000-people-wb-data.html [Accessed 17 July 2012].
-Van Exel, N. J. A. and Rietveld, P. (2009) “Could you also have made this trip by another mode? An investigation of perceived travel possibilities of car and train travellers on the main travel corridors to the city of Amsterdam, The Netherlands”, Transportation Research Part A, 43, pp.374-85.
-Viegas, J. (2001) “Making urban road pricing acceptable and effective: searching for quality and equity in urban mobility”, Transport Policy, 8, pp.289–294.
Vlek, C. and Steg, L. (1996) “Societal reasons, conditions and policy strategies for reducing the use of motor vehicles: A behavioral-science perspective and some empirical data”, In International Conference Towards Sustainable Transportation. Vancouver, 1996. OECD (1996), Towards Sustainable Transportation.
-Wikipedia, the Free Encyclopedia (2012) “List of countries by vehicles per capita”, [Online] Available at: http://en.wikipedia.org/wiki/List_of_countries_by_vehicles_per_capita [Accessed 17 July 2012].
-Zareii, H. (2003) “Evaluation of transportation demand management measures effectiveness in the critical air pollution days”, M.Sc. Thesis. Tehran: Sharif University of Technology.