Araştırma Makalesi
BibTex RIS Kaynak Göster
Yıl 2020, Cilt: 38 Sayı: 4, 1925 - 1937, 05.10.2021

Öz

Kaynakça

  • ⦁ Cambridge Systematics, Inc., (2005) Traffic Congestion and Reliability – Trends and Advanced Strategies for Congestion Mitigation - Final Report, Federal Highway Administration, Washington D.C., USA.
  • ⦁ Kerner, B. S., (2000) Theory of Breakdown Phenomenon at Highway Bottlenecks, Transportation Research Record, 1710(1), 136-144.
  • ⦁ Aydın, Ö. F., (2013) Evaluation of Work Zone Management Strategies: The FSM Bridge Case Study, MSc Thesis, Institute of Graduate Studies in Science and Engineering, Boğaziçi University, İstanbul, Turkey.
  • ⦁ Rashidi, S., Ranjitkar, P., Csaba, O., Hooper, A., (2017) Using Automatic Vehicle Location Data to Model and Identify Determinants of Bus Bunching. Transportation Research Procedia, 25, 1444-1456.
  • ⦁ Hammerle, M., Haynes, M., McNeil, S., (2005) Use of Automatic Vehicle Location and Passenger Count Data to Evaluate Bus Operations: Experience of The Chicago Transit Authority, Illinois. Transportation Research Record, 1903(1), 27-34.
  • ⦁ Ganin, A. A., Mersky, A. C., Jin, A. S., Kitsak, M., Keisler, J. M., Linkov, I., (2019) Resilience in Intelligent Transportation Systems (ITS). Transportation Research Part C: Emerging Technologies, 100, 318-329.
  • ⦁ Zhang, J., Wang, F. Y., Wang, K., Lin, W. H., Xu, X., Chen, C., (2011). Data-Driven Intelligent Transportation Systems: A Survey. IEEE Transactions on Intelligent Transportation Systems, 12(4), 1624-1639.
  • ⦁ Strathman, J. G., Kimpel, T. J., Dueker, K. J., Gerhart, R. L., Callas, S., (2002) Evaluation of Transit Operations: Data Applications of Tri-Met's Automated Bus Dispatching System. Transportation, 29(3), 321-345.
  • ⦁ Kimpel, T. J., Strathman, J. G., Callas, S., (2008) Improving Scheduling Through Performance Monitoring. Computer-Aided Systems in Public Transport (pp. 253-280). Springer, Berlin, Heidelberg.
  • ⦁ Horbury, A. X., (1999) Using Non-Real-Time Automatic Vehicle Location Data to Improve Bus Services. Transportation Research Part B: Methodological, 33(8), 559-579.
  • ⦁ Tilocca, P., Farris, S., Angius, S., Argiolas, R., Obino, A., Secchi, S., Mozzoni, S., Barabino, B., (2017) Managing Data and Rethinking Applications in an Innovative Mid-Sized Bus Fleet. Transportation Research Procedia, 25, 1899-1919.
  • ⦁ Lin, J., Wang, P., Barnum, D. T., (2008) A Quality Control Framework for Bus Schedule Reliability. Transportation Research Part E: Logistics and Transportation Review, 44(6), 1086-1098.
  • ⦁ Mesbah, M., Currie, G., Lennon, C., Northcott, T., (2012) Spatial and Temporal Visualization of Transit Operations Performance Data at a Network Level. Journal of Transport Geography, 25, 15-26.
  • ⦁ Barabino, B., Di Francesco, M., Mozzoni, S., (2015) Rethinking Bus Punctuality by Integrating Automatic Vehicle Location Data and Passenger Patterns. Transportation Research Part A: Policy and Practice, 75, 84-95.
  • ⦁ Cathey, F. W., Dailey, D. J., (2003) A prescription for Transit Arrival/Departure Prediction using Automatic Vehicle Location Data. Transportation Research Part C: Emerging Technologies, 11(3-4), 241-264.
  • ⦁ Chang, G. L., Vasudevan, M., Su, C. C., (1996) Modelling and evaluation of Adaptive Bus-Preemption Control with and without Automatic Vehicle Location Systems. Transportation Research Part A: Policy and Practice, 30(4), 251-268.
  • ⦁ D’Acierno, L., Cartenì, A., Montella, B., (2009) Estimation of Urban Traffic Conditions using an Automatic Vehicle Location (AVL) System. European Journal of Operational Research, 196(2), 719-736.
  • ⦁ Mesbah, M., Lin, J., Currie, G., (2015) “Weather” Transit is Reliable? Using AVL Data to Explore Tram Performance in Melbourne, Australia. Journal of Traffic and Transportation Engineering (English Edition), 2(3), 125-135.
  • ⦁ Zhang, C., Teng, J., (2013) Bus Dwell Time Estimation and Prediction: A Study Case in Shanghai-China. Procedia-Social and Behavioral Sciences, 96, 1329-1340.
  • ⦁ Comi, A., Nuzzolo, A., Brinchi, S., Verghini, R., (2017) Bus Travel Time Variability: Some Experimental Evidences. Transportation Research Procedia, 27, 101-108.
  • ⦁ Bae, S., (1995) Dynamic Estimation of Travel Time on Arterial Roads by Using Automatic Vehicle Location (AVL) Bus as a Vehicle Probe, Doctoral Dissertation, Virginia Polytechnic Institute and State University, Blacksburg, Virginia, USA.
  • ⦁ IBM Co., (2020) Detecting Asset Location Data Anomalies, US Patent No: US 10,656,278 B1, International Business Machines Corporation, Armonk, New York, USA.
  • ⦁ İETT, (2020) https://www.iett.istanbul/tr/main/hatlar/BN2/K%C3%9C%C3%87%C3%9CK%C3%87EKMECE%20-%20EM%C4%B0N%C3%96N%C3%9C-%C4%B0ETT-Otob%C3%BCs-Sefer-Saatleri-ve-Duraklar%C4%B1, Accessed 08/09/2020.
  • ⦁ Dekanová, M., Duchoň, F., Pásztó, P., Adamík, M., Kľúčik, M., (2018) Mobile Robot Localization and Path Planning in Open Street Map, Grant Journal, 7(1), 134-137.
  • [25] Dyer, S. A., Dyer, J. S., (2001) Cubic-Spline Interpolation 1, IEEE Instrumentation & Measurement Magazine, 4(1), 44-46.

DETERMINATION OF HIGHWAY BOTTLENECKS BY USING INTELLIGENT TRANSPORTATION SYSTEMS AND GEOGRAPHIC INFORMATION SYSTEMS

Yıl 2020, Cilt: 38 Sayı: 4, 1925 - 1937, 05.10.2021

Öz

An occurrence of congestion at a highway segment, also named bottleneck, is one of the major problems of traffic. As a result of the bottlenecks, vehicle speeds are transparently decreased and its effects continue on the traffic flow by acting upstream or downstream as an interface for a while. Thus, negative effects are observed over the capacity of the highway segment where the bottleneck occurs until traffic flow returns to normal conditions again. Therefore, traffic engineers aim to avoid this major problem in design and operation of highways.
Intelligent Transportation System (ITS) is an advanced application that is used to utilize existing infrastructure more effectively instead of building new infrastructures. Today, ITS has been one of the trend study fields thanks to the development of technology and through the spread of smart cities. Automatic Vehicle Location (AVL), a powerful tool to manage fleets such as service vehicles, emergency vehicles, or public transit vehicles, is a GPS-based technology within the context of the ITS. So, agencies and organizations can follow vehicles of their fleets by utilizing satellites.
In this study, an AVL dataset, integrated into public transportation systems, and Geographic Information Systems (GIS) are used to detect bottlenecks in a highway segment in Istanbul. The results showed that if the locations of bus stops and traffic signals are known, the segments, where bottlenecks occur and congestion increases, may be determined by using AVL data.

Kaynakça

  • ⦁ Cambridge Systematics, Inc., (2005) Traffic Congestion and Reliability – Trends and Advanced Strategies for Congestion Mitigation - Final Report, Federal Highway Administration, Washington D.C., USA.
  • ⦁ Kerner, B. S., (2000) Theory of Breakdown Phenomenon at Highway Bottlenecks, Transportation Research Record, 1710(1), 136-144.
  • ⦁ Aydın, Ö. F., (2013) Evaluation of Work Zone Management Strategies: The FSM Bridge Case Study, MSc Thesis, Institute of Graduate Studies in Science and Engineering, Boğaziçi University, İstanbul, Turkey.
  • ⦁ Rashidi, S., Ranjitkar, P., Csaba, O., Hooper, A., (2017) Using Automatic Vehicle Location Data to Model and Identify Determinants of Bus Bunching. Transportation Research Procedia, 25, 1444-1456.
  • ⦁ Hammerle, M., Haynes, M., McNeil, S., (2005) Use of Automatic Vehicle Location and Passenger Count Data to Evaluate Bus Operations: Experience of The Chicago Transit Authority, Illinois. Transportation Research Record, 1903(1), 27-34.
  • ⦁ Ganin, A. A., Mersky, A. C., Jin, A. S., Kitsak, M., Keisler, J. M., Linkov, I., (2019) Resilience in Intelligent Transportation Systems (ITS). Transportation Research Part C: Emerging Technologies, 100, 318-329.
  • ⦁ Zhang, J., Wang, F. Y., Wang, K., Lin, W. H., Xu, X., Chen, C., (2011). Data-Driven Intelligent Transportation Systems: A Survey. IEEE Transactions on Intelligent Transportation Systems, 12(4), 1624-1639.
  • ⦁ Strathman, J. G., Kimpel, T. J., Dueker, K. J., Gerhart, R. L., Callas, S., (2002) Evaluation of Transit Operations: Data Applications of Tri-Met's Automated Bus Dispatching System. Transportation, 29(3), 321-345.
  • ⦁ Kimpel, T. J., Strathman, J. G., Callas, S., (2008) Improving Scheduling Through Performance Monitoring. Computer-Aided Systems in Public Transport (pp. 253-280). Springer, Berlin, Heidelberg.
  • ⦁ Horbury, A. X., (1999) Using Non-Real-Time Automatic Vehicle Location Data to Improve Bus Services. Transportation Research Part B: Methodological, 33(8), 559-579.
  • ⦁ Tilocca, P., Farris, S., Angius, S., Argiolas, R., Obino, A., Secchi, S., Mozzoni, S., Barabino, B., (2017) Managing Data and Rethinking Applications in an Innovative Mid-Sized Bus Fleet. Transportation Research Procedia, 25, 1899-1919.
  • ⦁ Lin, J., Wang, P., Barnum, D. T., (2008) A Quality Control Framework for Bus Schedule Reliability. Transportation Research Part E: Logistics and Transportation Review, 44(6), 1086-1098.
  • ⦁ Mesbah, M., Currie, G., Lennon, C., Northcott, T., (2012) Spatial and Temporal Visualization of Transit Operations Performance Data at a Network Level. Journal of Transport Geography, 25, 15-26.
  • ⦁ Barabino, B., Di Francesco, M., Mozzoni, S., (2015) Rethinking Bus Punctuality by Integrating Automatic Vehicle Location Data and Passenger Patterns. Transportation Research Part A: Policy and Practice, 75, 84-95.
  • ⦁ Cathey, F. W., Dailey, D. J., (2003) A prescription for Transit Arrival/Departure Prediction using Automatic Vehicle Location Data. Transportation Research Part C: Emerging Technologies, 11(3-4), 241-264.
  • ⦁ Chang, G. L., Vasudevan, M., Su, C. C., (1996) Modelling and evaluation of Adaptive Bus-Preemption Control with and without Automatic Vehicle Location Systems. Transportation Research Part A: Policy and Practice, 30(4), 251-268.
  • ⦁ D’Acierno, L., Cartenì, A., Montella, B., (2009) Estimation of Urban Traffic Conditions using an Automatic Vehicle Location (AVL) System. European Journal of Operational Research, 196(2), 719-736.
  • ⦁ Mesbah, M., Lin, J., Currie, G., (2015) “Weather” Transit is Reliable? Using AVL Data to Explore Tram Performance in Melbourne, Australia. Journal of Traffic and Transportation Engineering (English Edition), 2(3), 125-135.
  • ⦁ Zhang, C., Teng, J., (2013) Bus Dwell Time Estimation and Prediction: A Study Case in Shanghai-China. Procedia-Social and Behavioral Sciences, 96, 1329-1340.
  • ⦁ Comi, A., Nuzzolo, A., Brinchi, S., Verghini, R., (2017) Bus Travel Time Variability: Some Experimental Evidences. Transportation Research Procedia, 27, 101-108.
  • ⦁ Bae, S., (1995) Dynamic Estimation of Travel Time on Arterial Roads by Using Automatic Vehicle Location (AVL) Bus as a Vehicle Probe, Doctoral Dissertation, Virginia Polytechnic Institute and State University, Blacksburg, Virginia, USA.
  • ⦁ IBM Co., (2020) Detecting Asset Location Data Anomalies, US Patent No: US 10,656,278 B1, International Business Machines Corporation, Armonk, New York, USA.
  • ⦁ İETT, (2020) https://www.iett.istanbul/tr/main/hatlar/BN2/K%C3%9C%C3%87%C3%9CK%C3%87EKMECE%20-%20EM%C4%B0N%C3%96N%C3%9C-%C4%B0ETT-Otob%C3%BCs-Sefer-Saatleri-ve-Duraklar%C4%B1, Accessed 08/09/2020.
  • ⦁ Dekanová, M., Duchoň, F., Pásztó, P., Adamík, M., Kľúčik, M., (2018) Mobile Robot Localization and Path Planning in Open Street Map, Grant Journal, 7(1), 134-137.
  • [25] Dyer, S. A., Dyer, J. S., (2001) Cubic-Spline Interpolation 1, IEEE Instrumentation & Measurement Magazine, 4(1), 44-46.
Toplam 25 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Bölüm Research Articles
Yazarlar

Abdullah Maltaş Bu kişi benim 0000-0002-2595-8536

Halit Ozen Bu kişi benim 0000-0003-4031-7283

Yayımlanma Tarihi 5 Ekim 2021
Gönderilme Tarihi 8 Eylül 2020
Yayımlandığı Sayı Yıl 2020 Cilt: 38 Sayı: 4

Kaynak Göster

Vancouver Maltaş A, Ozen H. DETERMINATION OF HIGHWAY BOTTLENECKS BY USING INTELLIGENT TRANSPORTATION SYSTEMS AND GEOGRAPHIC INFORMATION SYSTEMS. SIGMA. 2021;38(4):1925-37.

IMPORTANT NOTE: JOURNAL SUBMISSION LINK https://eds.yildiz.edu.tr/sigma/