Performance Prediction Model for Urban Dual Carriageway Using Travel Time-Based Indices

  • Muneera C. P.Email author
  • Krishnamurthy Karuppanagounder
Original Article


Performance prediction based on travel time satisfies both the road users and the traffic managers alike to provide information for smooth traffic flow. The present study aims to develop the performance prediction models for the urban dual carriageway link, using travel time-based indices. Planning time index, congestion index, and travel time index are the indices used in this study for the performance prediction. The geometric data, traffic volume count, and travel time data on the seven dual carriageways located in two urban centers of Kerala form the database for this study. Statistical analyses were carried out for the performance evaluation of urban link using travel time-based indices in each study stretch. The traffic flow in the study stretches was found to vary from 114 to 684 PCU/h/m. Nonlinear regression models were developed and validated for predicting the performance of the urban link by considering the traffic flow rate as an independent variable. Of the different model tried, the exponential model gave accurate prediction on performance with travel time-based indices. A model application was made for performance prediction of dual carriageway with considerable variation in traffic flow rate. The developed model can be used to predict the performance of dual carriageway using travel time parameter. The use of travel time-based performance prediction aids the road users to plan their trip well in advance and further can be used for regional transport planning.


Planning time index Congestion index Travel time index Dual carriageway Regression model 



The authors sincerely thank the support received from the Centre for Transportation Research, Department of Civil Engineering, National Institute of Technology Calicut, a Centre of Excellence setup under FAST Scheme of MHRD, Govt. of India.


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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Department of Civil EngineeringNational Institute of TechnologyCalicutIndia

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