Gitakrishnan Ramadurai

Bio: Gitakrishnan Ramadurai is an academic researcher from Indian Institute of Technology Madras. The author has contributed to research in topic(s): Traffic flow & Bottleneck. The author has an hindex of 17, co-authored 61 publication(s) receiving 1108 citation(s). Previous affiliations of Gitakrishnan Ramadurai include Rensselaer Polytechnic Institute & Indian Institutes of Technology.

The role of built environment on pedestrian crash frequency

Abstract: This study investigates (i) the link of land use and road design on pedestrian safety and (ii) the effect of the level of spatial aggregation on the frequency of pedestrian accidents. For this purpose, pedestrian accident frequency models were developed for New York City based on an extensive dataset collected from different sources over a period of 5 years. The assembled dataset provides a rich source of variables (land-use, demographics, transit supply, road network and travel characteristics) and two different crash frequency outcomes: total and fatal-only collision counts. Among other things, it was observed that the census tract analysis (disaggregate data) provides more insightful and consistent results than the analysis at the zip code level. The results indicate that tracts with greater fraction of industrial, commercial, and open land use types have greater likelihood for crashes while tracts with a greater fraction of residential land use have significantly lower likelihood of pedestrian crashes. Moreover, census tracts that have a greater number of schools and transit stops – which are determinants of pedestrian activity – are more likely to have greater crashes. Results also show that the likelihood of pedestrian–vehicle collision increases with the number of lanes and road width. This suggests that retrofitting or narrowing the roads could possibly reduce the risk of pedestrian crashes.

Linear Complementarity Formulation for Single Bottleneck Model with Heterogeneous Commuters

Abstract: This paper formulates the dynamic equilibrium conditions for a single bottleneck model with heterogeneous commuters as a linear complementarity problem. This novel formulation offers a formal framework for the rigorous study and solution of a single bottleneck model with general heterogeneity parameter assumptions, enabling the adoption of well established complementarity theory and methods to analyze the model, and providing a significant contribution to the existing literature that either lacks a rigorous formulation or solves the problem under a limited set of heterogeneity parameter assumptions. The paper presents theoretical proofs for solution existence and uniqueness, and numerical results and insights for different heterogeneity assumptions.

A robust transportation signal control problem accounting for traffic dynamics

Abstract: Transportation system analysis must rely on predictions of the future that, by their very nature, contain substantial uncertainty. Future demand, demographics, and network capacities are only a few of the parameters that must be accounted for in both the planning and every day operations of transportation networks. While many repercussions of uncertainty exist, a primary concern in traffic operations is to develop efficient traffic signal designs that satisfy certain measures of short term future system performance while accounting for the different possible realizations of traffic state. As a result,uncertainty has to be incorporated in the design of traffic signal systems. Current dynamic traffic equilibrium models accounting for signal design, however, are not suitable for quantifying network performance over the range of possible scenarios and in analyzing the robust performance of the system. The purpose of this paper is to propose a new approach-robust system optimal signal control model; a supply-side within day operational transportation model where future transportation demand is assumed to be uncertain. A robust dynamic system optimal model with an embedded cell transmission model is formulated. Numerical analysis are performed on a test network to illustrate the benefits of accounting for uncertainty and robustness.

Dynamic user equilibrium model for combined activity-travel choices using activity-travel supernetwork representation

Abstract: Integrated urban transportation models have several benefits over sequential models including consistent solutions, quicker convergence, and more realistic representation of behavior. Static models have been integrated using the concept of Supernetworks. However integrated dynamic transport models are less common. In this paper, activity location, time of participation, duration, and route choice decisions are jointly modeled in a single unified dynamic framework referred to as Activity-Travel Networks (ATNs). ATNs is a type of Supernetwork where virtual links representing activity choices are added to augment the travel network to represent additional choice dimensions. Each route in the augmented network represents a set of travel and activity arcs. Therefore, choosing a route is analogous to choosing an activity location, duration, time of participation, and travel route. A cell-based transmission model (CTM) is embedded to capture the traffic flow dynamics. The dynamic user equilibrium (DUE) behavior requires that all used routes (activity-travel sequences) provide equal and greater utility compared to unused routes. An equivalent variational inequality problem is obtained. A solution method based on route-swapping algorithm is tested on a hypothetical network under different demand levels and parameter assumptions.

Calibration of VISSIM for Indian Heterogeneous Traffic Conditions

Abstract: Efficient modeling of vehicular traffic remains a largely debated issue especially in context of Indian heterogeneous driving conditions. VISSIM is a microscopic traffic simulation software that is gaining increasing recognition in India. However, modifications to the default behavioral parameters are essential to effectively simulate Indian heterogeneous traffic conditions. This paper presents a method and results on sensitivity analysis and automatic calibration of VISSIM model using data from an intersection in Chennai. This intersection has heavy flows during the peak time. VISSIM parameters affecting driving behavior in Indian heterogeneous conditions were found using sensitivity analysis. ANOVA and elementary effects method were used in sensitivity analysis. The model was calibrated using Visual C++ COM interface of VISSIM. Genetic Algorithm was used to find the optimal combination of sensitive parameters during calibration.

A practical guide to the American Community Survey (3-year estimates)

Abstract: Historically, most demographic data for states and substate areas were collected from the long version of the decennial census questionnaire. A “snapshot” of the characteristics of the population on the April 1 census date was available once every 10 years. The long form of the decennial census has been replaced by the American Community Survey (ACS) that has been conducted on an ongoing basis for the entire country since 2005. Instead of a snapshot in which all of the data are gathered at one time, the ACS aggregates data collected over time, making the results more difficult to interpret. However, the ACS data are updated annually.

Transportation network analysis

Abstract: Transportation Networks. Optimality. Cost Functions. Deterministic User Equilibrium Assignment. Stochastic User Equilibrium Assignment. Trip Table Estimation. Network Reliability. Network Design. Conclusions. References. Index.

Panel Analysis in Transportation Planning: An Overview

Abstract: The advantages, disadvantages, and issues involved in the panel analysis of travel behavior are discussed. Increased statistical efficiency, possibility of improved prediction, and the ability to observe changes and examine behavioral dynamics, are among the advantages panel data offer. Their disadvantages, on the other hand, stem from the added biases and costs of panel survey, and increased complexity involved in the analysis. Following a discussion of response lags, leads, and other dynamic elements of travel behavior, the paper offers a brief review of statistical methods available for the analysis of panel data. Use of panel data and dynamic models for demand forecasting is then described, followed by sample size, interview frequency, and other considerations in panel survey design and administration.