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Güvenlik kriteri olarak çarpışmaya kadar geçen süre ve takip zaman aralığı karşılaştırılması

Yıl 2021, Cilt: 27 Sayı: 6, 669 - 675, 30.11.2021

Öz

Araçlar arasındaki mesafeyi korumak için kriterlerin incelenmesi yolun üzerindeki davranışları ve trafik akımını daha iyi anlamaya destek olur. Bu çalışmada zaman aralığı ve çarpışma süresi kriterleri sürüş simülatörü kullanarak incelenmiştir. Zaman aralığı, frenleme zaman aralığı ve takip zaman aralığı'na ayrılır. Sonuçlar çarpışma zamanının(TTC) bir eşiğe ulaşmasıyla ve frenleme zaman aralığının(TH) 1.5 sn.’ye yükseldiğini ve bu değerden sonra sabit kaldığını gösterdi. Ayrıca, frenleme zaman aralığı ve takip zaman aralığı arasında karşılaştırma, zaman aralığı'nı takip etmekten farklı olarak, frenleme zaman aralığı'nin daha az varyansa sahip olduğunu ve değerlerinin şeritler arasında önemli ölçüde farklılık göstermediğini gösterdi. Yani sürücü her zaman 1.1 sn. sabit bir frenleme zaman aralığısı gözlemlemeye çalışıyor ve buna göre ön araca yaklaşmıyor kriterler arasında zaman aralığı frenleme'nin en önemli faktör olduğu ve bunun dikkate alınması otomobil takip eden modellerde faydalı olabileceği söylenebilir.

Kaynakça

  • [1] Saffarzadeh M, Nadimi N, Naseralavi S, Mamdoohi AR. “A general formulation for time-to-collision safety indicator”. Proceedings of the Institution of Civil Engineers-Transport, 166(5), 294-304, 2013.
  • [2] Sagberg F. “Characteristics of fatal road crashes ınvolving unlicensed drivers or riders: ımplications for countermeasures”. Accident Analysis & Prevention, 117, 270-275, 2018.
  • [3] Wali B, Khattak A, Karnowski TP. “How driving volatility in time to collision relates to crash severity in a naturalistic driving environment”. Transportation Research Board 97th Annual Meeting, Washington DC, United States, 8 January 2018.
  • [4] Moridpour S. “Evaluating the time headway distributions in congested highways” . Journal of Traffic and Logistics Engineering, 2(3), 224-229 2014.
  • [5] Ye F, Zhang Y. “Vehicle type-specific headway analysis using freeway traffic data”. Transportation Research Record, 2124(1), 222-230, 2009.
  • [6] Yin S, Li Z, Zhang Y, Yao D, Su Y, Li L. “Headway distribution modeling with regard to traffic status”. 2009 IEEE Intelligent Vehicles Symposium IEEE, Xi'an, China, 3-5 July 2009.
  • [7] Mesarec B, Lep M. “Combining the grid‐based spatial planning and network‐based transport planning”. Technological and Economic Development of Economy, 15(1), 60-77, 2009.
  • [8] Jakimavičius M, Burinskiene M. “A GIS and multi‐criteria‐ based analysisand rankingof transportation zonesof vilniuscity”. Technological and Economic Development of Economy, 15(1), 39-48, 2009.
  • [9] Treiterer J, Nemeth ZA. “Multiple rear-end collisions in freeway traffic, their causes and their avoidance”. SAE Transactions, 79, 293-309, 1970.
  • [10] Von Buseck CR, Evans L, Schmidt DE, Wasielewski P. “Seat belt usage and risk taking in driving behavior”. SAE Transactions, 89, 1529-1533, 1980.
  • [11] Winkelbauer M, Donabauer M, Pommer A, Jansen R. “Naturalistic data on time headway behind motorcycles and other vehicles”. Safety Science, 119, 162-173, 2019.
  • [12] Yue Y, Yang Z, Pei X, Chen H, Song C, Yao D. “Will crash experience affect driver’s behavior? an observation and analysis on time headway variation before and after a traffic crash”. Tsinghua Science and Technology, 25(4), 471-478, 2020.
  • [13] Siebert FW, Wallis FL. “How speed and visibility ınfluence preferred headway distances in highly automated driving”. Transportation Research Part F: Traffic Psychology and Behaviour, 64, 485-494, 2019.
  • [14] Khansari ER, Tabibi M, Nejad FM. “A study on following behavior based on the time headway”. Jurnal Kejuruteraan, 32(2), 187-195, 2020.
  • [15] Hayward J. Near Misses as a Measure of Safety at Urban Intersections. Pennsylvania State, USA, Pennsylvania State University, 1971.
  • [16] Hydén C. “The development of a Method for Traffic Safety Evaluation: The Swedish Traffic Conflicts Technique”. Lund, Sweden, Lund Institute of Technology, 1987.
  • [17] Minderhoud MM, Bovy PHL. “Extended time-to-collision measures for road traffic safety assessment” . Accident Analysis & Prevention, 33(1), 89-97, 2001.
  • [18] Ian Noy Y. Ergonomics and Safety of Intelligent Driver Interfaces. New Jersey, USA, Lawrence Erlbaum Associates, 1997.
  • [19] Wan Winsum W, Heino A. “Choice of time-headway in carfollowing and the role of time-to-collision ınformation in braking”. Ergonomics, 39(4), 579-592, 1996.
  • [20] Vogel K. “A comparison of headway and time to collision as safety indicators”. Accident Analysis & Prevention, 35(3), 427-433, 2003.
  • [21] Khansari ER, Tabibi M, Moghadas Nejad F. “Lane-Based Car-Following behaviour based on ınductive loops”. Proceedings of the Institution of Civil Engineers-Transport, 170(1), 38-45, 2017.
  • [22] Ayres TJ, Li L, Schleuning D, Young D. “Preferred timeheadway of highway drivers”. 2001 IEEE Intelligent Transportation Systems Proceedings, Oakland (CA), USA, 25-29 August 2001.
  • [23] Abtahi SM, Tamannaei M, Haghshenash H. “Analysis and modeling time headway distributions under heavy traffic flow conditions in the urban highways: Case of Isfahan”. Transport, 26(4), 375-382, 2011.
  • [24] Wang W, Cheng Q, Li C, André D, Jiang X. “A cross-cultural analysis of driving behavior under critical situations: a driving simulator study”. Transportation research part F: traffic psychology and behaviour, 62, 483-493, 2019.
  • [25] Santos J, Merat N, Mouta S, Brookhuis K, De Waard D. “The ınteraction between driving and ın-vehicle ınformation systems: comparison of results from laboratory, simulator and real-world studies”. Transportation Research Part F: Traffic Psychology and Behaviour, 8(2), 135-146, 2005.
  • [26] May AD. Fundamentals of Traffic Flow. NJ, USA, Prentice Hall Englewood Cliffs, 1990.
  • [27] Papacostas CS, Prevedouros PD. Transportation Engineering and Planning. 3rd ed. Hawaii, USA, Prentice Hall, 2009.
  • [28] Brackstone M, Waterson B, McDonald M. “Determinants of following headway in congested traffic”. Transportation Research Part F: Traffic Psychology and Behaviour, 12(2), 131-142, 2009.
  • [29] Fellendorf M, Vortisch P. “Validation of the microscopic traffic flow model vissim in different real-world situations”. 80th Annual Meeting of the Transportation Research Board, Washington, DC, 1-11 January 2001.
  • [30] Saha P, Roy R, Sarkar AK, Pal M. “Preferred time headway of drivers on two-lane highways with heterogeneous traffic”. Transportation letters, 11(4), 200-207, 2019.
  • [31] Treiber M, Kesting A, Helbing D. “Understanding widely scattered traffic flows, the capacity drop, and platoons as effects of variance-driven time gaps”. Physical review E, 2006. https://doi.org/10.1103/PhysRevE.74.016123
  • [32] Hoogendoorn SP, Botma H. “Modeling and Estimation of Headway Distributions”. Transportation Research Record, 1591(1), 14-22, 1997.

Comparing time to collision and time headway as safety criteria

Yıl 2021, Cilt: 27 Sayı: 6, 669 - 675, 30.11.2021

Öz

Examination of the criteria for maintaining distance between vehicles helps to better understand the behavior of following behavior and traffic flow. In this study, time headway(TH) and time to collision(TTC) criteria have been studied using driving simulator. TH is divided into two types, including braking TH, TH at the moment of considerable brake, and following TH, TH during following. The results showed that by reaching TTC to a threshold, braking TH has increased to 1.5 sec. and after this value, braking TH has remained constant. Also the comparison between braking and following TH showed that, unlike following TH, braking TH has less variance and its values did not differ significantly between lanes. That is, the driver is trying to observe a fixed amount of braking TH, 1.1 seconds, all the time, and not get closer to the front vehicle accordingly. It can be said that among the criteria, braking TH is the most important factor and considering it can be helpful in the carfollowing models.

Kaynakça

  • [1] Saffarzadeh M, Nadimi N, Naseralavi S, Mamdoohi AR. “A general formulation for time-to-collision safety indicator”. Proceedings of the Institution of Civil Engineers-Transport, 166(5), 294-304, 2013.
  • [2] Sagberg F. “Characteristics of fatal road crashes ınvolving unlicensed drivers or riders: ımplications for countermeasures”. Accident Analysis & Prevention, 117, 270-275, 2018.
  • [3] Wali B, Khattak A, Karnowski TP. “How driving volatility in time to collision relates to crash severity in a naturalistic driving environment”. Transportation Research Board 97th Annual Meeting, Washington DC, United States, 8 January 2018.
  • [4] Moridpour S. “Evaluating the time headway distributions in congested highways” . Journal of Traffic and Logistics Engineering, 2(3), 224-229 2014.
  • [5] Ye F, Zhang Y. “Vehicle type-specific headway analysis using freeway traffic data”. Transportation Research Record, 2124(1), 222-230, 2009.
  • [6] Yin S, Li Z, Zhang Y, Yao D, Su Y, Li L. “Headway distribution modeling with regard to traffic status”. 2009 IEEE Intelligent Vehicles Symposium IEEE, Xi'an, China, 3-5 July 2009.
  • [7] Mesarec B, Lep M. “Combining the grid‐based spatial planning and network‐based transport planning”. Technological and Economic Development of Economy, 15(1), 60-77, 2009.
  • [8] Jakimavičius M, Burinskiene M. “A GIS and multi‐criteria‐ based analysisand rankingof transportation zonesof vilniuscity”. Technological and Economic Development of Economy, 15(1), 39-48, 2009.
  • [9] Treiterer J, Nemeth ZA. “Multiple rear-end collisions in freeway traffic, their causes and their avoidance”. SAE Transactions, 79, 293-309, 1970.
  • [10] Von Buseck CR, Evans L, Schmidt DE, Wasielewski P. “Seat belt usage and risk taking in driving behavior”. SAE Transactions, 89, 1529-1533, 1980.
  • [11] Winkelbauer M, Donabauer M, Pommer A, Jansen R. “Naturalistic data on time headway behind motorcycles and other vehicles”. Safety Science, 119, 162-173, 2019.
  • [12] Yue Y, Yang Z, Pei X, Chen H, Song C, Yao D. “Will crash experience affect driver’s behavior? an observation and analysis on time headway variation before and after a traffic crash”. Tsinghua Science and Technology, 25(4), 471-478, 2020.
  • [13] Siebert FW, Wallis FL. “How speed and visibility ınfluence preferred headway distances in highly automated driving”. Transportation Research Part F: Traffic Psychology and Behaviour, 64, 485-494, 2019.
  • [14] Khansari ER, Tabibi M, Nejad FM. “A study on following behavior based on the time headway”. Jurnal Kejuruteraan, 32(2), 187-195, 2020.
  • [15] Hayward J. Near Misses as a Measure of Safety at Urban Intersections. Pennsylvania State, USA, Pennsylvania State University, 1971.
  • [16] Hydén C. “The development of a Method for Traffic Safety Evaluation: The Swedish Traffic Conflicts Technique”. Lund, Sweden, Lund Institute of Technology, 1987.
  • [17] Minderhoud MM, Bovy PHL. “Extended time-to-collision measures for road traffic safety assessment” . Accident Analysis & Prevention, 33(1), 89-97, 2001.
  • [18] Ian Noy Y. Ergonomics and Safety of Intelligent Driver Interfaces. New Jersey, USA, Lawrence Erlbaum Associates, 1997.
  • [19] Wan Winsum W, Heino A. “Choice of time-headway in carfollowing and the role of time-to-collision ınformation in braking”. Ergonomics, 39(4), 579-592, 1996.
  • [20] Vogel K. “A comparison of headway and time to collision as safety indicators”. Accident Analysis & Prevention, 35(3), 427-433, 2003.
  • [21] Khansari ER, Tabibi M, Moghadas Nejad F. “Lane-Based Car-Following behaviour based on ınductive loops”. Proceedings of the Institution of Civil Engineers-Transport, 170(1), 38-45, 2017.
  • [22] Ayres TJ, Li L, Schleuning D, Young D. “Preferred timeheadway of highway drivers”. 2001 IEEE Intelligent Transportation Systems Proceedings, Oakland (CA), USA, 25-29 August 2001.
  • [23] Abtahi SM, Tamannaei M, Haghshenash H. “Analysis and modeling time headway distributions under heavy traffic flow conditions in the urban highways: Case of Isfahan”. Transport, 26(4), 375-382, 2011.
  • [24] Wang W, Cheng Q, Li C, André D, Jiang X. “A cross-cultural analysis of driving behavior under critical situations: a driving simulator study”. Transportation research part F: traffic psychology and behaviour, 62, 483-493, 2019.
  • [25] Santos J, Merat N, Mouta S, Brookhuis K, De Waard D. “The ınteraction between driving and ın-vehicle ınformation systems: comparison of results from laboratory, simulator and real-world studies”. Transportation Research Part F: Traffic Psychology and Behaviour, 8(2), 135-146, 2005.
  • [26] May AD. Fundamentals of Traffic Flow. NJ, USA, Prentice Hall Englewood Cliffs, 1990.
  • [27] Papacostas CS, Prevedouros PD. Transportation Engineering and Planning. 3rd ed. Hawaii, USA, Prentice Hall, 2009.
  • [28] Brackstone M, Waterson B, McDonald M. “Determinants of following headway in congested traffic”. Transportation Research Part F: Traffic Psychology and Behaviour, 12(2), 131-142, 2009.
  • [29] Fellendorf M, Vortisch P. “Validation of the microscopic traffic flow model vissim in different real-world situations”. 80th Annual Meeting of the Transportation Research Board, Washington, DC, 1-11 January 2001.
  • [30] Saha P, Roy R, Sarkar AK, Pal M. “Preferred time headway of drivers on two-lane highways with heterogeneous traffic”. Transportation letters, 11(4), 200-207, 2019.
  • [31] Treiber M, Kesting A, Helbing D. “Understanding widely scattered traffic flows, the capacity drop, and platoons as effects of variance-driven time gaps”. Physical review E, 2006. https://doi.org/10.1103/PhysRevE.74.016123
  • [32] Hoogendoorn SP, Botma H. “Modeling and Estimation of Headway Distributions”. Transportation Research Record, 1591(1), 14-22, 1997.
Toplam 32 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Mühendislik
Bölüm İnşaat Müh. / Çevre Müh. / Jeoloji Müh.
Yazarlar

Ehsan Ramezanı-khansarı Bu kişi benim

Fereidoon Moghadas Nejad Bu kişi benim

Sina Moogeh Bu kişi benim

Yayımlanma Tarihi 30 Kasım 2021
Yayımlandığı Sayı Yıl 2021 Cilt: 27 Sayı: 6

Kaynak Göster

APA Ramezanı-khansarı, E., Moghadas Nejad, F., & Moogeh, S. (2021). Comparing time to collision and time headway as safety criteria. Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi, 27(6), 669-675.
AMA Ramezanı-khansarı E, Moghadas Nejad F, Moogeh S. Comparing time to collision and time headway as safety criteria. Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi. Kasım 2021;27(6):669-675.
Chicago Ramezanı-khansarı, Ehsan, Fereidoon Moghadas Nejad, ve Sina Moogeh. “Comparing Time to Collision and Time Headway As Safety Criteria”. Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi 27, sy. 6 (Kasım 2021): 669-75.
EndNote Ramezanı-khansarı E, Moghadas Nejad F, Moogeh S (01 Kasım 2021) Comparing time to collision and time headway as safety criteria. Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi 27 6 669–675.
IEEE E. Ramezanı-khansarı, F. Moghadas Nejad, ve S. Moogeh, “Comparing time to collision and time headway as safety criteria”, Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi, c. 27, sy. 6, ss. 669–675, 2021.
ISNAD Ramezanı-khansarı, Ehsan vd. “Comparing Time to Collision and Time Headway As Safety Criteria”. Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi 27/6 (Kasım 2021), 669-675.
JAMA Ramezanı-khansarı E, Moghadas Nejad F, Moogeh S. Comparing time to collision and time headway as safety criteria. Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi. 2021;27:669–675.
MLA Ramezanı-khansarı, Ehsan vd. “Comparing Time to Collision and Time Headway As Safety Criteria”. Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi, c. 27, sy. 6, 2021, ss. 669-75.
Vancouver Ramezanı-khansarı E, Moghadas Nejad F, Moogeh S. Comparing time to collision and time headway as safety criteria. Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi. 2021;27(6):669-75.





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