Assessment of Network Traffic Congestion through Traffic Congestability Value (TCV) : a New Index

• Autorzy: Nilanchal Patel , Alok Bhushan Mukherjee
• Języki publikacji: EN

Abstrakty

EN

Traffic congestion is a major and growing problem in urban areas across the globe. It reduces the effective spatial interaction between different locations. To mitigate traffic congestion, not only the actual status of different routes needs to be known but also it is imperative to determine network congestion in different spatial zones associated with distinct land use classes. In the present paper, a new formula is proposed to quantify traffic congestion in the different spatial zones of a study area characterized by distinct land use classes. The proposed formula is termed the Traffic Congestability Value (TCV). The formula considers three major influencing factors: congestion index value, pedestrian movement and road surface conditions; since these parameters are significantly related to land use in a region. The different traffic congestion parameters, i.e. travel time, average speed and the proportion of time stopped, were collected in real time. Lower values of TCV correspond to a higher degree of congestion in the respective spatial zones and vice-versa and the results were validated in the field. TCV differs from the previous approaches to quantifying traffic congestion since it focuses on the causes of network congestion while in previous works the focus was generally on link flow congestion. (original abstract)

Słowa kluczowe

EN

Road traffic; Road traffic analysis

PL

Ruch drogowy; Analiza ruchu drogowego

• Czasopismo: Bulletin of Geography. Socio-economic Series
• Rocznik: 2015
• Numer: No. 30
• Strony: 123--134

Twórcy

autor

Nilanchal Patel

• Birla Institute of Technology Mesra, Ranchi (JH)

autor

Alok Bhushan Mukherjee

• Birla Institute of Technology Mesra, Ranchi (JH)

Bibliografia

• Anh T.T., 2003: System dynamic applied to study the urban traffic congestion of Hanoi. In: Proceedings of the Eastern Asia Society for Transportation Studies, Vol. 4, pp. 1-1797.
• Boamah S.A., 2010: Spatial and temporal analyses of traffic flow in the city of Almelo: in search for a microscopic fundamental diagram (MFD), M.Sc. Thesis, Faculty of Geo-Information Science and Earth Observation, University of Twente, Enschede, the Netherlands.
• Chen B., Cheng H.H. and Palen J., 2009: Integrating Mobile Agent Technology with Multi-Agent Systems for Distributed Traffic Detection and Management Systems. In: Transportation Research Part C, Vol. 17 (1), pp. 1-10.
• Godescu A. and Zurich E., 2010: The Efficient Pedestrian Flow Hypothesis. In: European Journal of Scientific Research, Vol. 44 (2), pp. 220-227.
• Gwilliam K., 2003: Urban Transport in Developing Countries. In: Transport Reviews: A Transnational Transdisciplinary Journal, Vol. 23 (2). pp. 197-216.
• Hamilton A., Waterson B., Cherrett T., Robinson A. and Snell I., 2012: The Evolution of Urban Traffic Control: Changing Policy and Technology. In: Transportation Planning and Technology, Vol. 36 (1), pp. 24-43.
• Jian S., Qiong L. and Zhongren P., 2011: Research and Analysis on Causality and Spatial-Temporal Evolution of Urban Traffic Congestions- A Case Study on Shenzhen of China. In: Journal of Transportation Systems Engineering and Information Technology, Vol. 11 (5), pp. 86-93.
• Jimenez F. and Cabrera-Monitel W., 2014: System for Road Vehicle Energy Optimization using Real Time Road and Traffic Information. In: Energies, Vol. 7 (6), pp. 3576-3598.
• Joint Transport Research Centre, 2004: Managing Urban Traffic Congestion. In: European conference of ministers of transport. Available from: http://www.internationaltransportforum.org/Pub/pdf/07Congestion.pdf. [DoA: 5 December 2013].
• Koshak N.A., 2006: Developing a Web-Based GIS for Hajj Traffic Plan. In: Journal of Urban Planning Research, Vol. 6 (6), pp. 1-13.
• Lee W.P., Osman M.A., Talib A.Z. and Ismail A.I.M., 2008: Dynamic Traffic Simulation for Traffic Congestion Problem Using an Enhanced Algorithm. In: International Journal of Mathematical, Computational, Physical, Electrical and Computer Engineering (World Academy of Science, Engineering and Technology), Vol. 2 (9), pp. 277-284.
• Li Y. and Tsukaguchi H., 2005: Relationships between Network Topology and Pedestrian Route Choice Behavior. In: Journal of the Eastern Asia Society for Transportation Studies, Vol. 6, pp. 241-248.
• Lindsey C.R. and Verhoef E.T., 2000: Traffic Congestion and Congestion Pricing. Tinbergen Institute Discussion Paper. Available from: http://papers.tinbergen.nl/00101.pdf [DoA: 26 July 2014].
• Liu X. and Ban Y., 2013: Uncovering Spatio-Temporal Patterns using Massive Floating Car Data. In: ISPRS International Journal of Geo-Information, Vol. 2 (2), pp. 371-384.
• Menon I.I., 2005: Application of Geographic Information System in transportation for road network analysis, M.E Thesis, Faculty of Civil Engineering, University Technology, Malaysia.
• Mitsakis E., Aifadopoulou G., Grau J.M.S., Chrysohoou E. and Morfoulaki M., 2014: Combination of Macroscopic and Microscopic Transport Simulation Models: Use Case in Cyprus. In: International Journal for Traffic and Transport Engineering, Vol. 4 (2), pp. 220-233.
• Oort N.V. and Nes R.V., 2009: Regularity Analysis for Optimizing Urban Transit Network Design. In: Public Transport, Vol. 1 (2), pp. 155-168.
• Pratap R.C., Rao A.M., Durai B.K. and Lakshmi S., 2011: GIS application in traffic congestion management. In: Proceedings of International Conference on Recent Trends in Transportation, Environmental and Civil Engineering, pp. 66-70.
• Quingyu L., Zhicai J., Baofeng S. and Hongfei J., 2007: Method Research on Measuring the External Costs of Urban Traffic Congestion. In: Journal of Transportation Systems Engineering and Information Technology, Vol. 7 (3), pp. 9-12.
• Rajagopalan S. and Yu H.L., 2001: Capacity Planning with Congestion Effects. In: European Journal of Operational Research, Vol. 134 (2), pp. 365-377.
• Rao A.M. and Rao K.R., 2012: Measuring Urban Traffic Congestion - A Review. In: International Journal for Traffic and Transport Engineering, Vol. 2 (4), pp. 286-305.
• Ryley T.J. and Zanni A.M., 2013: An Examination of the Relationship between Social Interactions and Travel Uncertainty. In: Journal of Transport Geography, Vol. 31, pp. 249-257.
• Singh S.K., 2005: Review of Urban Transportation in India. In: Journal of Public Transportation, Vol. 8 (1), pp. 79-97.
• Simecki A., Stiener S. and Cokorilo O., 2013: The Accessibility Assessment of Regional Transport in the South East Europe. In: International Journal of Traffic Transport Engineering, Vol. 3 (4), pp. 351-364.
• Sun S. and Zhang C., 2006: A Bayesian Network Approach to Traffic Flow Forecasting. In: IEEE Transaction on Intelligent Transportation System, Vol. 7 (1), pp. 124-132.
• Taylor M.A.P., 1992: Exploring the nature of urban traffic congestion: concepts, parameters, theories and models. In: Proceedings of the 16th Conference of the Australian Road Research Board, Vol.16, pp. 83-104.
• Taylor M.A.P., D'Este M.G. and Zito R., 1999: Using GPS to Measure Traffic System Performance. In: Computer-Aided Civil and Infrastructure Engineering, Vol. 14 (4), pp. 255-265.
• The Indian Road Congress (IRC), 1990: Guidelines for Capacity of Urban Roads in Plain Areas. Available from: http://www.jesa.in/webfiles/IRC Bookss/IRC-106-1990.pdf [DoA: 22 January 2014].
• Triantis K., Sarangi S., Teodorovic D. and Razzolini L., 2011: Traffic Congestion Mitigation: Combining Engineering and Economic Perspectives. In: Transportation Planning and Technology, Vol. 34 (7), pp. 637-645.
• Uang S. and Hwang S., 2003: Effects on Driving Behavior of Congestion Information and of Scale of In-Vehicle Navigation Systems. In: Transportation Research Part C, Vol. 11 (6), pp. 423-438.
• Wen W., 2008: A Dynamic and Automatic Traffic Light Control Expert System for Solving the Road Congestion Problem. In: Expert Systems with Applications, Vol. 34 (4), pp. 2370-2381.
• Xu Z. and Sui D.J., 2007: Small World Characteristics on Transportation Networks: A Perspective from Network Autocorrelation. In: Journal of Geographical System, Vol. 9 (2), pp. 189-205.
• Zhili L., Chunyan L. and Cheng L., 2009: Traffic Impact Analysis of Congestion Charge in Mega Cities. In: Journal of Transportation Systems Engineering and Information Technology, Vol. 9 (6), pp. 57-62.

Identyfikatory

DOI

10.1515/bog-2015-0039