Krishna Nikhil Sumanth Behara

• Doctor of Philosophy
• Postdoctoral Research Fellow (Smart Cities) at Queensland University of Technology

Origin-Destination (OD) matrix is a tableau of travel demand distributed between different zonal pairs. Essentially, OD matrix provides two types of information: (a) the individual cell value represents travel demand between a specific OD pair; and (b) group of OD pairs provides insights into structural information in terms of distribution pattern...

Traditional bi-level origin-destination (OD) matrix estimation process adjusts the matrix (at the upper level) based on the deviation between the observed and simulated traffic counts. The problem is mathematically under-determined, and the quality of the solution can be enhanced by restricting the upper level search space with information from oth...

Most traditional metrics compare origin-destination (OD) matrices based on the deviations of individual OD flows and often neglect OD matrix structural information within their formulations. Limited metrics exist in literature for the structural comparison of OD matrices. One such metric is mean structural similarity index (MSSIM) that computes sta...

This research proposes a novel single-level approach to traffic counts-based OD estimation using observed turning proportions and partial OD flows. The key idea is to relax the need for explicit assignment-based bi-level models and exploit the observations from big traffic data. The observed turning proportions are used to estimate traffic counts;...

Comparative analysis of multimodal travel demand can help transport planners to improve the sustainability of a transport system. This research proposes a framework to qualitatively compare and analyze multimodal travel demand (of constrained and free transport modes) to identify opportunities and prioritize areas for improvement of constrained mod...

The study delves into the complexities of travel disruption and recovery during and after the COVID-19 pandemic. Using a data-driven methodology, we explore spatial-temporal patterns across regions by times of the day, weekdays/weekends, and trip purposes. Using passively collected location-based data from January 2019 to October 2021 in the Northe...

Driver fatigue is a major cause of road crashes. However, there is limited knowledge regarding the potential consequences of driver fatigue in taxi (conventional and app-based), ride-hailing, and ridesharing services. Driver fatigue is likely to be significantly exacerbated in this population due to the multi-task characteristics of their jobs; thu...

The quality of Origin–Destination matrix (OD) estimation depends on number of factors including the selection of appropriate upper-level function of bi-level formulation, constraints to the OD flows, and suitable solution algorithm. Addressing these aspects, the study first explored different upper-level formulations using two types of traffic info...

Limited studies exist in the literature on demand related travel patterns, the analysis of which requires a rich database of Origin Destination (OD) matrices with appropriate clustering algorithms. This paper develops a methodological framework to explore typical travel patterns from multi-density high dimensional matrices and estimate typical OD c...

This study performed statistical analyses to identify likely crash contributing factors for Head-on Fatal and Serious Injury (FSI) collisions involving heavy vehicles (HVs) on the Queensland state road network. Head-on HV collisions are associated with the largest number of fatalities compared to other crash types in Queensland. However, there is l...

This research proposes a novel single-level approach to traffic counts-based OD estimation using observed turning proportions and partial OD flows. The key idea is to relax the need for explicit assignment-based bi-level models and exploit the observations from big traffic data. The observed turning proportions are used to estimate traffic counts;...

The structure of a daily Origin-Destination (OD) matrix represents the distribution of travel patterns in terms of number of trips ending into different destinations within a region. However, the daily travel patterns could be significantly different due to different characteristics such as regular working days, weekends, long weekends, public holi...

Understanding the differences in multi-modal travel demand can help transport planners to improve the sustainability of a transport system. Thus, this study aims to develop a multi-step methodological framework to identify gaps in demand between different modes and apply on a realistic large-scale network. The framework includes three methods. Meth...

Expressways in India are vastly different from those in the developed countries due to its varied vehicle composition and quasi-lane disciplined traffic movement. Relatively, limited research has been done on the lane utilization and lane choice behavior of different vehicle types on Indian expressways. This study thus focuses on building a structu...

The Delhi-Gurgaon expressway is vastly different from expressway or freeways in other countries due to its varied roadway and traffic conditions. It is a multi-lane urban road connecting nearby urban areas (Delhi and Gurgaon) with divided carriageway for high speed travel having partial control of access at frequent locations via basic, weaving, me...