Analysing the root cause of the damage risk in heavy vehicles to reduce traffic congestion

This study aims to investigate important damage risks in heavy vehicles on the highway using risk analysis method as well as to examine their root causes using Fault Tree Analysis (FTA). This is im...

[1]  H. Doloi Assessing stakeholders' influence on social performance of infrastructure projects , 2012 .

[2]  Anne T. McCartt,et al.  Crash risk factors for interstate large trucks in North Carolina. , 2017, Journal of safety research.

[3]  Xiaoduan Sun,et al.  Measuring the Effectiveness of Vehicle Inspection Regulations in Different States of the U.S. , 2019, Transportation Research Record: Journal of the Transportation Research Board.

[4]  Adrian Todoruţ,et al.  Evaluation of the tire pressure influence on the lateral forces that occur between tire and road , 2017 .

[5]  Olexandr Stepanchuk,et al.  Surveying of Traffic Congestions on Arterial Roads of Kyiv City , 2017 .

[6]  RuijtersEnno,et al.  Fault tree analysis , 2015 .

[7]  Moshe E. Ben-Akiva,et al.  Overview of traffic incident duration analysis and prediction , 2018, European Transport Research Review.

[8]  R. Kiunsi A Review of Traffic Congestion in Dar es Salaam City from the Physical Planning Perspective , 2013 .

[9]  C. Blazquez,et al.  Spatial autocorrelation analysis of cargo trucks on highway crashes in Chile. , 2018, Accident; analysis and prevention.

[10]  T. Ojo,et al.  Managing traffic congestion in the Accra Central Market, Ghana , 2018, Journal of Urban Management.

[11]  Sohag Kabir,et al.  An overview of fault tree analysis and its application in model based dependability analysis , 2017, Expert Syst. Appl..

[12]  Clifton A. Ericson,et al.  Hazard Analysis Techniques for System Safety: Ericson/Hazard Analysis Techniques for System Safety , 2005 .

[13]  Sarath C. Joshua,et al.  A Causal Analysis of Large Vehicle Accidents Through Fault‐Tree Analysis , 1992 .

[14]  Mu-Chen Chen,et al.  Identifying important variables for predicting travel time of freeway with non-recurrent congestion with neural networks , 2012, Neural Computing and Applications.

[15]  I. Wiguna,et al.  Evaluation of road design performance in delivering community project social benefits in Indonesian PPP , 2019, International Journal of Construction Management.

[16]  Khaled Ksaibati,et al.  An investigation of influential factors of downgrade truck crashes: A logistic regression approach , 2019, Journal of Traffic and Transportation Engineering (English Edition).

[17]  Shashank Bharadwaj,et al.  Impact of congestion on greenhouse gas emissions for road transport in Mumbai metropolitan region , 2017 .

[18]  Mariëlle Stoelinga,et al.  Fault tree analysis: A survey of the state-of-the-art in modeling, analysis and tools , 2014, Comput. Sci. Rev..

[19]  C. Borrego,et al.  Integrating road traffic externalities through a sustainability indicator. , 2019, The Science of the total environment.

[20]  Meng Zhang,et al.  Investigation of haul truck-related fatal accidents in surface mining using fault tree analysis , 2014 .

[21]  Abdul-Mohsen Al-Hammad Common Interface Problems among Various Construction Parties , 2000 .

[22]  Younshik Chung,et al.  Assessment of non-recurrent traffic congestion caused by freeway work zones and its statistical analysis with unobserved heterogeneity , 2011 .