Lelitha Vanajakshi

Chennai Traffic Dataset

Muni Srinivasulu, Bijo Sebastian, Lelitha Vanajakshi

A synchronized dataset comprising camera data collected on urban roads in Chennai, India, covering straight-road, curved- road, and intersection scenarios. Annotations are provide for images.

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Chennai Traffic Dataset

Muni Srinivasulu, Bijo Sebastian, Lelitha Vanajakshi

A synchronized dataset comprising camera data collected on urban roads in Chennai, India, covering straight-road, curved- road, and intersection scenarios. Annotations are provide for images.

in (code pays fourni par la source)

A Stochastic Traffic Delay Model for a Multi-Channel Queuing System with Random Arrivals and Departures

Vinaya S. Mattungal, Chithra A. Saikrishna, Lelitha Vanajakshi

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Delay Model for Signalised Intersections Based On M/D/N Queueing System

Vinaya S. Mattungal, Lelitha Vanajakshi

Delay is a fundamental measure for evaluating the performance of the traffic systems.However, the stochastic nature of vehicle arrivals and discharges at the intersection introduces significant complexity in its estimation.Its estimation becomes even more challenging in developing countries like India, where traffic …

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Travel Time Reliability Prediction Using Quantile Random Forest Regression

B. Anil Kumar, Gunda Chandana, Lelitha Vanajakshi

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Bus Arrival Time Prediction: A Comprehensive Review

B. Anil Kumar, Ramanand Singh, Hima Elsa Shaji, Lelitha Vanajakshi

Bus arrival prediction systems play a crucial role in enhancing the efficiency and reliability of public transportation networks. Existing reviews in this area mainly focus on travel time prediction, without paying enough attention to the data, the patterns in the data, which …

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An analytical delay model for multi-class and lane-free traffic condition

Vinaya S. Mattungal, Lelitha Vanajakshi

This study emphasises the criticality of delay as a performance metric for signalized intersections and the challenges associated with its estimation, particularly in the context of Multi-class and Lane-free (MCLF) traffic conditions. Traditional delay models are often inadequate for such conditions, necessitating …

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Fusion of Thermal and RGB Images for Traffic Object Detection

Anirud Nandakumar, Lelitha Vanajakshi, Chandrashekar Lakshminarayanan

Conventional approaches to traffic data collection often involve the use of RGB cameras. In an outdoor scenario, the data collected is affected by many factors, such as poor/excessive lighting, weather, occlusion, etc. Introducing a thermal sensor helps tackle the loss of information …

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Automated Detection of Roadway and Traffic Control Conditions Using On-Board Image Processing

Ashmitha Jaysi Sivakumar, L Pragati, Lelitha Vanajakshi

Accurate detection of roadway and traffic control conditions is crucial for enhancing Advanced Driver Assistance Systems (ADAS) in dynamic environments. This study aims to leverage deep learning techniques, specifically YOLO series, for their identification in real-world scenarios. Detection of traffic signs, markings …

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Bus Signal Priority Solution for Non-Uniform Vehicle Arrival Conditions

Nazia Tazin Imran, Lelitha Vanajakshi

Bus signal priority (BSP) is an affordable and less infrastructure-demanding operational strategy that is used to improve the efficiency and reliability of transit vehicles. Majority of the studies on BSP are designed with the assumption of uniform vehicle arrivals and departures, ignoring …

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Spatio-Temporal Machine Learning Approaches for Bus Travel Time Prediction

G. Ganesan Subramanian, Aditya Verma, Lelitha Vanajakshi

Predicting bus travel times is critical for enhancing passenger satisfaction, optimizing route planning, and improving overall system efficiency. This study explores spatio-temporal modeling techniques to predict travel times for a bus route in Chennai, India, leveraging spatial dependencies across route sections and …

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Queue Dissipation-Based Max Pressure Signal Control Using Vehicle Re-Identification Data

Himabindu Maripini, Tamojit Ghosh, Lelitha Vanajakshi

Traffic congestion is a persistent urban challenge, and signal control strategies play a crucial role in enhancing network efficiency. Traditional max pressure-based control systems prioritize optimizing throughput based on known queue lengths but often overlook the impact of intersection delays and real-world …

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