A5066163440- Transportation Planning and Optimization
- Transportation and Mobility Innovations
- Urban Transport and Accessibility
- Human Mobility and Location-Based Analysis
- Urban and Freight Transport Logistics
- Sharing Economy and Platforms
- Traffic control and management
- Traffic Prediction and Management Techniques
- Statistical Methods and Inference
- Smart Parking Systems Research
- Data Management and Algorithms
- Viral gastroenteritis research and epidemiology
- Cytomegalovirus and herpesvirus research
- Advanced Manufacturing and Logistics Optimization
- Energy Efficiency and Management
- Model-Driven Software Engineering Techniques
- COVID-19 epidemiological studies
- Viral Infections and Immunology Research
- Data-Driven Disease Surveillance
- Impact of Light on Environment and Health
- Advanced Database Systems and Queries
- Smart Grid Energy Management
- Electric Power System Optimization
- Distributed systems and fault tolerance
- Sparse and Compressive Sensing Techniques
Indian Institute of Technology Delhi
2024
University of Minnesota
2018-2023
Indian Institute of Technology Madras
2023
Twin Cities Orthopedics
2018-2022
University of Minnesota System
2021
Maulana Azad National Institute of Technology
2020
Sanjay Gandhi Post Graduate Institute of Medical Sciences
2015
Savitribai Phule Pune University
1995
This paper studies the potential spread of infectious disease through passenger encounters in a public transit system using automatic count (APC) data. An algorithmic procedure is proposed to evaluate three different measures quantify these encounters. The first two increased possibility from interaction when traveling between origin–destination pairs. third measure evaluates an aggregate quantifying relative risk boarding at particular stop route. For calculating measures, compressed...
The special events such as games, concerts, state fairs, etc. attract a large amount of population, which requires proper planning transit services to meet the induced demand. Previous studies have proposed methods for estimating an average daily weekday demand, inherent disadvantage in demand event. We solve idealized version this problem i.e., we decompose event affected matrix into regular and outlier matrix. start with detecting scale data using Mahalanobis distance, detection method...
The development of an origin–destination (OD) demand matrix is crucial for transit planning. With the help automated data, it possible to estimate a stop-level OD matrix. We propose novel method estimating route using automatic passenger count (APC) data. uses [Formula: see text] norm regularizer, which leverages sparsity in actual technique popularly known as compressed sensing (CS). also discuss mathematical properties proposed optimization program and complexity solving it. used...
The k shortest paths problem finds applications in multiple fields. Of particular interest the transportation field is variant of finding simple (KSSP), which has a higher complexity. This research presents novel label-setting algorithm for multi-destination KSSP directed networks that obviates repeated to each destination (necessary existing deviation-based algorithms), resulting significant computational speedup. It shown proposed exact and flexible enough handle several variants by...
This study presents an integrated optimisation framework for locating depots in a Shared autonomous vehicle (SAV) system under demand uncertainty. A two-stage stochastic mixed integer programming (MIP) model is formulated to optimise the number and locations of SAV system, where uncertainty represented by multiple scenarios with occurrence probability. The dynamics movements are further considered forming trip chain each AV. An enhanced Benders decomposition-based algorithm Pareto-optimal...
Electric energy market is to increase their profit for electricity providers (generators) in an open competitive and reduce reduced consumer costs by taking into account available power supply, demand, clearing prices (MCP) constraints. The main contribution of this paper provided more benefit supplier new technique has used overcome the problem bidding. It may be highly important manage as per fair rules. In paper, PSO APSO are solve bidding problem. have many characteristics that similar...
Due to limited transit network coverage and infrequent service, suburban commuters often face the first mile/last mile (FMLM) problem. To deal with this, they either drive a park-and-ride location take transit, use carpooling, or directly their destination avoid inconvenience. Ridesharing, an emerging mode of transportation, can solve In this setup, driver ride-seeker station, from where rider her respective destination. The problem requires solving ridesharing matching routing riders in...
This study presents an integrated framework for locating depots in a Shared autonomous vehicle (SAV) system under demand uncertainty. A two-stage stochastic mixed integer programming (MIP) model is formulated to optimize the number and locations of SAV system, where uncertainty represented by multiple scenarios with occurrence probability. Unlike previous studies that consider station-based relocations, we take into account dynamics movements transportation network forming trip chain each...