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Stream travel time reliability using GPS-equipped probe vehicles
Travel time reliability (TTR) is an important measure to quantify the variation in travel times. Currently, there is no single reliability metric appropriate across all locations, that is easily understandable and can be used to compare across facilities. Moreover, reliability analysis of facilities from developing countries is limited due to the non-availability of extensive data required for such an analysis. The present study addresses these gaps. It identifies a reliable data source for such analysis of heterogeneous, lane-less traffic, compares existing reliability measures for the data, highlights the advantages and disadvantages, proposes a measure that may be more suitable for such traffic with high variability, and finally illustrates how reliability analysis under such conditions can be done with limited data sources such as GPS-fitted transit vehicles. Using such commonly available data for traffic stream reliability analysis is the ultimate aim of this study. For validation, stream travel time from Wi-Fi scanners is used. The study analyses the performance of various reliability measures and identifies the most suitable ones. Following this, a reliability measure, i.e. capacity buffer index (CBI), is developed to identify the unreliable congested regimes or periods, keeping time taken to travel at capacity conditions as the benchmark. From the results, it has been observed that CBI is in agreement with the real-field conditions in 94% of the cases, whereas it is 75% buffer time index. Finally, the feasibility of using bus probes to measure stream TTR is checked. Results show that bus probes can be an indicator of stream reliability and the developed measure can effectively capture the relationship between stream and bus TTR
Keywords
Bus probes, contingency tables, mixed traffic, travel time reliability, Wi-Fi sensors.
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- Vaziri, M. and Lam, T. N., Perceived factors affecting driver route decisions. J. Transp. Eng., 1983, 109(2), 297–311.
- Chang, Y. B. and Stopher, P. R., Defining the perceived attributes of travel modes for urban work trips. Transp. Plann. Technol., 1981, 7(1), 55–65.
- Prashker, J. N., Direct analysis of the perceived importance of at-tributes of reliability of travel modes in urban travel. Transporta-tion, 1979, 8(4), 329 346.
- Ali, S. S. M., George, B., Vanajakshi, L. and Venkatraman, J., Amultiple inductive loop vehicle detection system for heterogeneous and lane-less traffic. IEEE Trans. Instrument. Measure., 2012, 61(5), 1353–1360.
- Singh, V., Gore, N., Chepuri, A., Arkatkar, S., Joshi, G. and Pulu-gurtha, S., Examining travel time variability and reliability on an urban arterial road using Wi-Fi detections – a case study. J. East.Asia Soc. Transp. Stud., 2019, 13, 2390–2411.
- Raj, J., Ramesh, V., Varma, S. R. and Vanajakshi, L. D., Evalua-tion and application of automated traffic sensor data under Indian conditions. In Transportation Research Board 92nd Annual Meet-ing, Washington DC, USA, 2014; https://trid.trb.org/view/1288362
- Patra, S. S., Muthurajan, B., Chilukuri, B. R. and Devi, L., Devel-opment and evaluation of a low-cost Wi-Fi media access control scanner as traffic sensor. In IEEE 11th International Conference on Communication Systems and Networks (COMSNETS), Bengaluru, 7–11 January 2019.
- Singh, V., Gore, N., Arkatkar, S., Joshi, G. and Bhaskar, A., Vali-dating travel time reliability as a function of congestion using Wi-Fisensor derived travel time data. Transportation Research Board 99th Annual Meeting, Washington DC, United States, 12–16 Janu-ary 2020.
- van Lint, J. W. C. and van Zuylen, H. J., Monitoring and predicting freeway travel time reliability. Transport. Res. Record: J. Trans-port. Res. Board, 2005, 1917(1), 54–62.
- van Lint, J., van Zuylen, H. J. and Tu, H., Travel time unreliability on freeways: why measures based on variance tell only half the story. Transport. Res. Part A, 2008, 42(1), 258–277.
- Lomax, T., Schrank, D. and Turner, S., Selecting travel time relia-bility measures. techreport, Texas Transportation Institute, USA, 2003; https://d2dtl5nnlpfr0r.cloudfront.net/tti.tamu.edu/documents/TTI-2003-3.pdf
- Chase Jr, R. T., Williams, B. M. and Rouphail, N. M., Detailed analysis of travel time reliability performance measures from em-pirical data. In Transportation Research Board 92nd Annual Meet-ing, Washington DC, United States, 2013.
- Anderson, J. C., Sirupa, R., Kothuri, S. and Unnikrishnan, A., Un-derstanding factors affecting arterial reliability performance metrics.NITC-RR-1117. Portland, OR: Transportation Research and Educa-tion Center (TREC), 2019; https://doi.org/10.15760/trec.240
- Chepuri, A., Borakanavar, M., Amrutsamanvar, R., Arkatkar, S. and Joshi, G., Examining travel time reliability under mixed traffic conditions: a case study of urban arterial roads in Indian cities. Asian Transp. Stud., 2018, 5(1), 30–46.
- Chepuri, A., Joshi, S., Arkatkar, S., Joshi, G. and Bhaskar, A., Deve-lopment of new reliability measure for bus routes using trajectory data. Transp. Lett., 2019, 12(6), 363–374. 16. Bharti, A., Chandra, S. and Chalumuri, R. S., Performance evalua-tion of urban arterial in Delhi using travel time reliability. Proceed-ings of the Eastern Asia Society for Transportation Studies, 2013, 9;http://easts.info/online/proceedings/vol9/PDF/P331.pdf
- Asakura, Y. and Kashiwadani, M., Road network reliability caused by daily fluctuation of traffic flow. In 19th PTRC Summer Annual Meeting, University of Sussex, United Kingdom, 1991, pp. 73–84.
- FHWA, Travel time reliability: Making it there on time, all the time. Federal Highway Administration, US Department of Transpor-tation, 2006.
- Day, C. M., Remias, S. M., Li, H., Mekker, M. M., McNamara, M. L., Cox, E. D. and Bullock, M., Performance ranking of arterial corridors using travel time and travel time reliability metrics. Trans. Res. Rec.: J. Trans. Res. Board, 2015, 2487(1), 44–54.
- Elefteriadou, L., Travel time reliability implementation for the freeway SIS. Report No. FDOT Sponsored Research, BDK77-931-04, University of Florida Transportation Institute, USA, 2014.
- Pu, W., Analytic relationships between travel time reliability measures.Transp. Res. Rec.: J. Transp. Res. Board, 2011, 2254(1), 122–130.
- Gong, L. and Fan, W. D., Applying travel-time reliability measures in identifying and ranking recurrent freeway bottlenecks at the network level. J. Transp. Eng., Part A, 2017, 143(8), 04017042.
- Asakura, Y., Reliability measures of an origin and destination pair in a deteriorated road network with variable flows. In Proceedings of the 4th EURO Transportation Meeting, Newcastle, England, UK, 1996.
- Gopi, P., Sachdeva, S., and Bharati, A., Evaluation of travel time reliability on urban arterial. Int. J. Eng. Res. Technol., 2014, 3(6), 797–803.
- Remias, S., Hainen, A., Mathew, J., Vanajakshi, L., Sharma, A. and Bullock, D., Travel time observations using bluetooth MAC address matching: a case study on the Rajiv Gandhi roadway, Chennai, India,2017; doi:10.5703/1288284316505.
- Kumar, S. V., Vanajakshi, L. and Subramanian, S. C., A model based approach to predict stream travel time using public transit as probes. In IEEE Intelligent Vehicles Symposium (IV), Baden-Baden, Germany, 5–9 June 2011
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