Abstract

Critical gap (CG) estimation, while taking into consideration inconsistent driver behavior resulting from heterogeneous traffic conditions, is a tedious task. Several methods dealing with CG estimation have been developed in the past but limited research has been done in this regard for developing countries and there is a lot of scope to explore this field considering varying traffic conditions on the roads. In this study, the maximum likelihood method (MLM), one of the most prominent methods of determining CG, has been compared with two other methods developed for traffic conditions prevailing in India. These methods use different techniques for calculating the CG, such as minimization of absolute differences of gaps given by Ahmad et al., and minimization of square root of standard deviation of actual gap value from the predicted CG as per the Indian Highway Capacity Manual (Indo-HCM). This paper discusses the estimation of CG for five different categories of vehicles using these methods to counter the heterogeneity of traffic. Data has been collected on two urban multi-lane roundabouts in India. SOLVER in MS Excel is used to optimize the functions defined in all three methods. The results reveal that the method suggested by Ahmad et al. gives the most consistent results which are close to actual value when driver behavior is inconsistent. The other two methods are also reasonably consistent, with the method given in Indo-HCM being slightly better than MLM. Further, two-way ANOVA was applied to check the consistency of results.

Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.