Transportation Planning and Sustainable Mobility

The present study aims to model the mode choice behaviour between city bus and motorized three-wheeler services in Hyderabad City. A questionnaire survey was carried out to obtain the socio-economic and travel characteristics of individuals. Correlation matrix for socio-economic and travel characteristics were developed to check the multicollinearity between the variables. Binary logistic regression was conducted using the choice of transport mode as the outcome variable, with socio-economic and travel characteristics serving as the predictors. The results of the model show that high-income groups are preferring shared motorized three-wheeler when compared to city bus, while low-income groups are preferring city bus. As the age increases preference to bus increases when compared to shared motorized three-wheelers. For short distance trips, shared motorized three-wheeler services are used when compared with the city bus services. Therefore, to optimize transportation services in the city, an integrated plan for both bus and motorized three-wheelers networks should be developed. This plan would focus on enhancing bus services for longer trips and journeys with extended wait times, while paratransit would be designed to offer frequent services tailored for shorter trips. Such an approach aims to improve overall efficiency and convenience in urban mobility, meeting diverse travel needs across different trip lengths and waiting times.

Mode choice for cities with population less than a million exhibit choice behaviors which is governed by universally common factors like cost, convenience, and comfort. In the current paper, the mode choice in the study region of Imphal is investigated. A Multinomial Logit Model (MNL) is developed, the prediction accuracy, direct and cross elasticity as well as the acceptable travel time cost and acceptable distance of the trip have been evaluated. The acceptable travel time cost of the various modes is as anticipated with the car users having a highest value. The absolute values of direct elasticity for a 1% change in out-of-pocket costs indicate a relatively inelastic change in choice probabilities of the modes. The results indicate that public policies such as increase in the out-of-pocket costs or reduction in in-vehicle times have small effect on the usage and ridership. It also means that the revenue can be increased by raising out-of-pocket costs. A hierarchy within the choice of alternatives is modeled using Nested Logit (NL). It is seen that car, two-wheelers, non-motorized transport, auto form a subset of alternatives whose choice is conditional on choosing the non-shared mode. The marginal choice is between non-shared mode, pooled services, bus, share auto, and Tata Magic. Based on the willingness-to-pay survey a choice between the existing shared services (share auto, Tata Magic) and e-auto is explored.

Population growth in Silchar has necessitated the development of efficient transportation systems to alleviate traffic congestion and enhance mobility. This research project focuses on the capacity and level of service (LOS) estimation of a critical roundabout in the city, which is crucial for regulating traffic flow and ensuring smooth vehicular movement. The study aims to evaluate the roundabout’s capacity and LOS to identify areas for improvement and optimization. A comprehensive analysis was conducted using field observations and traffic engineering methodologies, including Indo-HCM 2017, IRC: 65–1976, and Highway Capacity Manual (HCM) 2010 guidelines. Capacity and LOS estimation involved calculating critical gaps and clearance times between minor and major road vehicles using the INAFOGA and clearance time methods for the Indo-HCM method. The IRC method estimated roundabout capacity based on weaving traffic proportions, while HCM 2010 used average control delay. Findings indicate that the roundabout’s capacity, as estimated by Indo-HCM, is 2414 PCU/h with a corresponding LOS B, reflecting efficient functionality with moderate delays. IRC: 65–1976 methodology suggests a capacity of 2884 PCU/h, essential for effective traffic flow. HCM 2010 analysis shows varying capacities for different approaches varying between 792 PCU/hr and 977 PCU/hr, with LOS of C, A, B, and A for four approaches. The outcomes are expected to guide urban planners, traffic engineers, and policymakers in making informed decisions to enhance the transportation network of Silchar, contributing to the city’s sustainable development. Integrating three methodologies enhances accuracy and reliability in transportation planning and traffic management.

Due to the rapid growth of urbanization, the travel needs of people are evolving day by day. Motorized transport leads to many issues including social and environment. As Non-Motorized Transport (NMT) is a sustainable mode of transport, it will be addressing not only environmental issues but also keeping the healthier lifestyle of the people. In a way, this study aims to explore the economic sustainability of NMT infrastructure in the Indian context. The objective of the study is to investigate the barriers to NMT promotion and evaluate the effectiveness of policies and stakeholder involvement in achieving sustainable urban mobility. Chennai Metropolitan Area (CMA) has been considered as a study area. CMA is the first city in India to adopt the NMT policy and execute the NMT infrastructure on the streets. From the literature, it is understood that the economic benefits of the NMT projects were always been overlooked. To understand and analyze the economic benefits, various stakeholders such as municipal bodies, funding agencies, research institutes, non-governmental organizations (NGOs), and private developers have been considered. A sample size of 22 stakeholder interviews data has been collected. Best–worst method (BWM) has been used to analyze the data. BWM reveals that the economic indicators “reduction in travel cost” is the most critical factor with the highest weight of 28.7%, followed by “travel time benefits” at 11.3%. In conclusion, the study emphasizes that the importance of multi-stakeholder participation is vital in addressing the challenges of economic and financial sustainability.

Parking is the act of stopping and leaving a vehicle in a particular place, typically for a period. It’s an essential aspect of urban transportation management, crucial for maintaining traffic flow and ensuring accessibility. This study aims to assess existing parking characteristics and develop a suitable discrete choice model to predict commuters’ mode choice behavior. Alappuzha municipality, the selected study area, situated in the most western portion of Alappuzha District in Indian state of Kerala. A user opinion survey was carried out among customers and visitors along a chosen road stretch to gain a full understanding of travel behavior and factors impacting mode and parking choices. The purpose of the survey was to find out the most important factors influencing parking in Alappuzha City. The analysis is based on data collected from 1393 samples in a user opinion survey. These include a variety of personal information, travel-related data, parking patterns, and fictitious events. IBM SPSS was the software used to analyze the data samples. Vehicle category is chosen as the dependent variable and the socio-economic and travel data are independent variables. Multinomial logit model was developed separately for different modes using SPSS software. The overall prediction percentage of developed model is 73.1% and that of validation model is 77%. Since the difference of overall prediction percentage between original model and validation model is 3.9% which is less than 5%, the developed mode choice model is proved to be good. From the analysis, the parking policies are also framed for the study area for enhancing sustainable transport solutions.

Inland Water Transport (IWT) has many environmental benefits compared to other modes, i.e., road or rail and there is a great potential of developing IWT in countries like India with several alluvial rivers. To develop IWT, the most critical factor is maintaining depth during non-monsoon period and eco-friendly submerged vanes is a potent and innovative solution. Submerged vanes are small hydraulic structures, and they can also be used as effective intervention for fairway development by harnessing natural flow energy for improving depth of navigational channel for vessel movement. This paper is based on a field study, conducted on a particular location on one of the major alluvial rivers in northern India. Results are shared and discussed in the paper after analyzing the pre- and post-monsoon changes after implementing the intervention at the site.

Commuting distances in developing countries have received little attention, creating a significant gap in research. This study aims to address this crucial gap by utilizing the 76th NSSO round on “Drinking water, sanitation, and housing conditions”—a nationally representative dataset for our analysis. Research conducted in developed countries has shown that residential self-selection (RSS) has a negligible role in determining commute distance. In the context of a fast-developing country like India, this article investigates whether this phenomenon holds true. Our primary focus is on understanding the explanatory power of location and physical characteristics of households. Our analysis reveals that over two-thirds of job-related trips in India cover a maximum distance of less than 5 km, which holds true for both males and females. Additionally, when examining reasons for relocation, it becomes evident that relocation for employment-related reasons is rare, with residence being the core focal point. The association of these variables with commute distances indicates a negligible to weak relationship. Based on our results, we conclude that the inclusion of location and physical characteristics of households need not significantly contribute to the explanatory power of the model, and the FSM, or the four-step model, cannot be the sole basis for transport planning.

Worsening congestion conditions, high energy consumption, and environmental crises have paved the path for water transportation to re-emerge in the transportation industry after being neglected for many decades. Kochi, as one of the major port cities in India, which is enriched with navigable waterways has taken the initiative to launch the first water metro system of India, an integrated electric ferry transportation system, becoming the first of Asia in the same category. The newly emerged public transport facility is designed to cater both recreational riders and commuters. However, ridership data indicates that while recreational users have accepted the system, commuter riders remain hesitant. Therefore, this study will specifically focus on assessing the service quality of the system, with a particular emphasis on its suitability for commuter riders. The study considered 25 factors that may influence the user’s satisfaction with water metro. Using machine learning techniques, a predictive model was developed for identifying the influencing factors on the passengers’ overall satisfaction of the Kochi water metro system. The study revealed that the water metro fare aligns with passenger expectations and identified water metro awareness as a key factor among other factors. Additionally, the random forest machine learning model was found to be the most effective for predicting overall passenger satisfaction with the Kochi water metro. The study findings help the policymakers and operators to prioritize the improvement areas for increasing the water metro ridership.

Environmental noise constitutes a significant environmental challenge in metropolitan areas, wherein road traffic noise, a primary urban pollutant, remains substantially underestimated despite presenting considerable health risks. This study aims to evaluate noise levels within and around noise-sensitive urban areas and to assess public awareness of the associated health risks. Field measurements were collected to validate the applicability of standard noise models, which were subsequently employed to characterize the acoustic environment and to evaluate exposure levels within the residential areas. A questionnaire survey involving 1623 residents was administered to assess the impact of noise exposure and public awareness. Statistical analyses, including the chi-square test, Shapiro–Wilk test, and Kolmogorov–Smirnov test, were employed to validate noise levels and identify key determinants of public perception of increased noise pollution health risks. The results reveal excessive noise levels, with 61.9% of residents exposed to noise exceeding the safe limits. A strong correlation (r² = 0.83) was found between measured and modeled noise. Despite a relatively high literacy rate of 73.8% and a predominantly young population, the majority of respondents exhibited limited or no awareness of the significant adverse health effects of traffic noise, indicating a considerable knowledge gap. To effectively address this issue and to ensure regulatory compliance, it is imperative to prioritize public education, develop targeted communication strategies, and enhance local interventions. A strong emphasis on public awareness is crucial to mitigate the health impacts of noise pollution.

Public transport accessibility assessment evaluates the ease of accessing public transportation services within a specific area. It considers factors such as proximity of stops/stations to key destinations, availability of transportation modes, service frequency and reliability, affordability of fares, and universal accessible infrastructure. Past assessments have focused on similar physical and service parameters. The assessment of public transport accessibility focused primarily on stop-level or corridor-level parameters, neglecting urban-level factors such as land use and building footprints. Additionally, user behavior and perception of public transport accessibility were not considered in most assessment methods. The literature review revealed a lack of a comprehensive framework that integrates public transport accessibility at the urban, corridor, and stop levels. This research aims to develop a framework that addresses this gap by integrating accessibility assessments across these different levels, hence a comprehensive framework for Advanced Public Transport Accessibility Index (APTAI) has been developed in this research. The Urban Network Analysis (UNA) was performed at urban level considering land use and building footprints along with network parameters. At corridor level, the service parameters like frequency, headway, stops, and routes were considered along with dynamic factor of availability of the PT service at the given time and Transit Network Analysis (TNA) was performed. At stop level, Transit Stop Analysis (TSA) was performed to capture the perception and behavior of people about the factors like bus frequency, waiting time, safety, comfort and distance and time to reach from POI (point of interest) to SAP (service access point) was considered, and the transit stop accessibility level was calculated. The APTAI was computed by integrating accessibility indices from each level using an accessibility adjacency matrix. The proposed framework was applied to the case area of Hubli–Dharwad with the results compared against the conventional Public Transport Accessibility Level (PTAL) method.

The transit operational efficiency is evaluated based on frequency, passenger load, and total operational hours. Current measurement definitions for these variables typically use one transit parameter at a time, lacking comprehensive macro-level assessment tools. Frequency and hours of operation represent the supply side, while passenger load reflects demand side of the system. This study aims to bridge the measurement gap for policymakers and practitioners by using the Level of Service (LOS) framework. By comparing seat supply per hour with actual demand, the study identifies the absolute gap between supply and demand. Additionally, using passenger load variation instead of simple passenger load values provides more realistic view of resource overuse or underuse. The study methodology combines the Transit Capacity and Quality of Service Manual (TCQSM)’s LOS measurement guidelines with the proposed absolute difference and passenger load variation-based LOS measurements. The study examines 13 routes in Surat, India, passing through Rander TAZ. The frequency and passenger load-based measurement shows a minimum LOS-B for all routes. However, including the absolute difference and passenger load variation reveals a minimum of LOS-D, with some routes at LOS-E/F. The comprehensive LOS assessment shows that 6 out of 13 routes fall below LOS-B, prioritizing them for future policy interventions through macro-level assessment. With a stagnant ridership of 0.25 million per day over past 4 years, resulting in 2.5% transit mode share and lower LOS on half of the selected routes, the primary cause of low usage is evident. Proposed framework offers more accurate representation of system operations.

Urban productivity is increasingly hampered by rising traffic congestion and the rapid growth of the automobile population, which significantly contributes to environmental pollution. As a result, this pollution negatively affects the health of city dwellers. This research focuses on work trip travel patterns in Trivandrum, which is a city facing congestion issues, especially during peak hours. In order to gain a deeper understanding of the changing dynamics of work-related travel before and after the COVID-19 pandemic, an extensive study was carried out in the urban area of Trivandrum. In order to find noteworthy changes in work trip patterns and new trends, this study entails analyzing a variety of work trip characteristics and comparing data from before and after the pandemic. We will also investigate the viability of switching to a light metro rail system along the NH66 route through Kazhakkoottam-Akkulam-Enchakkal-Killipalam for work trip commutes. This evaluation will be conducted based on a scientific methodology of surveys and data collection, and further analysis using binomial logistic regression. Travel preference surveys based on user opinion collected by distributing questionnaires are adopted for the collection of realistic data on travel preferences. The objective is to assess the acceptability and viability of light metro rail as a sustainable transportation option. The study intends to offer useful insights and suggestions by carefully examining the data and the results of the analysis. These results will help policymakers, politicians, and urban planners to make well-informed decisions to improve urban mobility, lessen traffic congestion, and mitigate the harmful effects of pollution on public health in the urban area. This research not only tackles current transportation concerns, but it also provides a forward-looking view of sustainable urban development.

This study investigates the impact of various service attributes on customer satisfaction within the water metro system, utilizing the Impact Asymmetry (IA) Index to categorize these attributes into frustrators, dissatisfiers, hybrids, satisfiers, and delighters. The goal is to identify key areas for improvement and strategic focus to enhance overall service quality. The analysis identifies several critical frustrators, including jetty platform protection and punctuality of boat arrival and departure, which exhibit significant negative impacts on customer satisfaction. These areas are essential for immediate improvement efforts to address major sources of customer frustration. Attributes such as comprehensibility of passenger information system (display) and awareness regarding the usage of life jackets fall into the satisfiers category, positively influencing customer perceptions and indicating areas where maintaining or enhancing service quality is beneficial. The findings highlight the need for a strategic approach to service management. Prioritizing improvements in frustrators and dissatisfiers while leveraging the strengths of satisfiers and delighters can optimize service quality and elevate customer satisfaction.

Non-motorized transportation (NMT), such as walking, cycling, skateboarding, rollerblading, and non-motorized scooters, provides various advantages for urban development, including environmental sustainability, improved health, and cost reduction. In light of the increasing global CO₂ emissions, especially from the transportation sector, the role of NMT in addressing climate change is becoming increasingly crucial. Focusing on Kochi, Kerala, an influential commercial center known for its cultural and economic significance, this study evaluates the current pedestrian infrastructure, identifies shortcomings, and provides recommendations for improvements. The selection of the study site in Kochi was based on diverse criteria, such as pedestrian accident rates, land use diversity, and the presence of key landmarks. Data collection methods included road inventories, pedestrian satisfaction surveys, volume counts, and user surveys. The findings revealed notable encroachments and connectivity issues that impact pedestrian satisfaction. The Walkability Score and Quality of Service assessments indicated average satisfaction levels. Space syntax analysis uncovered strong connectivity in specific areas but poor integration and accessibility. Additionally, pedestrian directedness analysis identified variations in pedestrian service coverage area based on the existing network and the actual service coverage area based on actual travel times, including delays. Overall, this study highlights critical areas requiring intervention and presents strategic recommendations to enhance pedestrian infrastructure. By addressing these issues, the study aims to create safer, more efficient urban environments that prioritize non-motorized transportation and improve the overall liveability of the city.

As fossil fuel supplies are being depleted and their negative effects on the environment become more apparent, research into renewable energy sources and alternative fuels has increased. Developing countries face the dual challenge of rising energy demand from population growth and urbanization, alongside the necessity to reduce greenhouse gas (GHG) emissions. In this regard, the present study reviews the viability, environmental effects, and infrastructure requirements of alternative fuels such as hydrogen, biofuels, electricity, methanol, natural gas, and ammonia. Although hydrogen and ammonia exhibit potential as carbon-free alternatives, issues with transport, storage, and manufacturing costs are impeding their uptake. Electric vehicles, while beneficial for short-distance travel, face limitations in range and resource availability. Biofuels offer a viable short-term solution but struggle with feedstock procurement and the food-versus-fuel debate. The study also looks at how governmental assistance and technical developments could promote the widespread use of alternative fuel vehicles (AFVs). It also examines the role of ammonia as a promising carbon-free fuel with a mature infrastructure capable of mitigating hydrogen’s key drawbacks. The insights aim to aid policymakers and researchers in making informed decisions to achieve sustainable mobility, thereby reducing reliance on fossil fuels and supporting global climate goals. The study underscores the urgency of a diversified approach to decarbonizing the transport sector, leveraging the strengths of each fuel type to overcome individual limitations and achieve significant reductions in fossil fuel dependency and carbon emissions.

India has been actively promoting electric vehicles (EVs) as a strategy to decarbonise the road transport sector. Key initiatives, such as purchase subsidies under the FAME scheme and state-level incentives including road tax exemptions, registration fee waivers, and additional purchase subsidies, have been pivotal in driving EV adoption in the country. This study aimed to examine the influence of policy awareness, technical knowledge, and environmental consciousness on EV adoption. The impact of these factors was assessed based on the stated preference of potential vehicle owners in Surat, Kolkata, Pune, and Coimbatore. A random sampling method was used to collect data via interview surveys of 1,555 individuals across these cities. A binary logit model was built to understand the effect of various factors on a buyer’s likelihood of opting for an EV in the next 5 years. Age, gender, education, household monthly income, occupation, vehicle ownership, environmental consciousness, and knowledge of EVs, FAME subsidy, and road tax waiver were independent variables. The results from the model indicate that age, income, employment, and current vehicle ownership significantly influence an individual’s decision to purchase EVs. However, gender and education are insignificant in the decision-making process. Awareness about road tax waiver significantly influences an individual’s choice, whereas awareness about FAME subsidy is insignificant. Further, knowledge about EVs and environmental consciousness positively influences an individual’s likelihood of purchasing EVs.

Understanding pedestrian behavior and its interaction with transportation infrastructure is crucial for ensuring safe and efficient urban environments. This study presents a comprehensive analysis of delay measurement techniques and their correlation with pedestrian behavior within the context of urban mobility systems. The study begins by reviewing existing literature on delay measurement methodologies, encompassing traditional approaches and emerging technologies such as GPS tracking and computer vision. It identifies key metrics for delay measurement, including travel time, waiting time at intersections, and overall journey delay. Furthermore, the study examines various factors influencing pedestrian behavior, ranging from individual characteristics such as age and gender to environmental factors such as weather conditions and built environment features. It explores how these factors impact pedestrian movement patterns, decision-making processes, and overall travel experience. The analysis integrates delay measurement techniques with observations of pedestrian behavior to identify correlations and causal relationships. It investigates how variations in delay affect pedestrian choices, such as route selection, crossing behavior, and mode of transportation. Additionally, it explores the role of infrastructure design and traffic management strategies in mitigating delays and enhancing pedestrian safety and satisfaction. The findings of this study contribute to the development of effective urban planning and transportation policies aimed at improving pedestrian mobility and enhancing the overall quality of urban life. By integrating delay measurement with insights into pedestrian behavior, policymakers and urban planners can design more pedestrian-friendly environments and optimize transportation systems to better serve the needs of all road users.

This study evaluates the effectiveness of trip length models in capturing the trade-off between speed and cost for daily commuters in Guwahati, India. Trip length models are crucial in transportation planning, predicting travel distances based on various factors. Traditional models often used fixed cost coefficients, assuming a direct relationship between trip length and cost. Recent models incorporate utility-based approaches, integrating both travel time and monetary cost. This study uses a mixed-method approach, combining quantitative and qualitative research techniques. A detailed questionnaire survey gathered data from 420 respondents, focusing on factors influencing trip length, speed, and cost. The findings indicate a predominant preference for two-wheelers, with work trips being the most common purpose. Females are found to be more centric toward electric vehicles (EVs) than males. The study examines mode-specific trip costs and preferences among commuters, revealing a higher preference for two-wheelers and cars for longer distances. The study highlights the economic efficiency of bicycles and e-rickshaws for shorter trips, while buses and e-buses are more economical for public transport. The results show that trip lengths in Guwahati are generally between 1 and 7 km, with an average trip length of 5.69 km. Understanding the limitations and strengths of current trip length models can help stakeholders develop more accurate tools for forecasting travel patterns, optimizing transportation networks, and making informed decisions on infrastructure investments and policy interventions.

Ensuring good accessibility at metro interchanges is crucial for creating an efficient, user-friendly public transportation network. Metro systems are extensively used as they help reduce journey times, making them essential for urban commuters. Assessing the performance of transport infrastructure and understanding user behavior provides valuable insights for policymaking and investment decisions. Traditional evaluation methods often rely on individual indicators, which can fail to capture the multidimensional nature of transportation systems. Metro interchanges are carefully planned to enhance connectivity and streamline networks, acting as essential hubs where passengers can switch between routes or directions to reduce travel time and increase flexibility. This study aims to develop a comprehensive assessment that identifies the key parameters influencing the choice of interchange stations over standard nodal stations, taking a holistic approach to transportation systems. A critical aspect of this analysis is last-mile connectivity—how effectively passengers can complete their journeys after leaving the metro network. This factor is essential for a robust public transportation system as it ensures passengers can reach their final destinations smoothly. Using SPSS software, the study evaluates important parameters through various statistical models, including logit models and factor analysis, using data collected from four metro interchange stations in Delhi. User feedback was gathered to rate the quality of service for each parameter, allowing for a detailed analysis of service levels. The findings offer valuable insights for planners, transportation authorities, and metro operators by pinpointing areas for improvement in interchange accessibility and user experience. By identifying parameters such as access distance, dispersal time, and interchange time, the study highlights factors that can enhance the overall effectiveness and functionality of metro interchanges. Ultimately, this research provides a comprehensive framework for evaluating metro interchange connectivity, covering dimensions of effectiveness, functionality, and user experience, to guide future improvements in urban transit systems.

Congestion pricing has demonstrated significant effectiveness in managing traffic congestion in cities around the world. While numerous cities globally have implemented or explored various congestion pricing schemes, their potential remains largely untapped in Indian cities. This paper investigates the feasibility of congestion pricing as a tool to address traffic issues in India, focusing specifically on the city of Ahmedabad. By analyzing both successful and unsuccessful international cases, the study extracts critical lessons that can inform potential implementations in the Indian context. Through a theoretical assessment, this study identifies three distinct spatial characteristics in Indian urban environments that could facilitate effective congestion pricing: (1) well-defined charging zones, (2) advantageous geographical features, and (3) compact, densely built central business districts. These features, prevalent in Indian cities, could play a vital role in achieving successful outcomes similar to those observed internationally. In addition to spatial considerations, the paper addresses the unique challenges Indian policymakers may encounter, such as garnering public support, ensuring political feasibility, and developing the necessary technical infrastructure. To assist policymakers in overcoming these challenges, the study provides practical recommendations rooted in international best practices. Overall, the research extends the discussions on congestion pricing in the Indian context, resulting in the identification of valuable insights to guide decision-making for the implementation of congestion pricing schemes, ultimately promoting sustainable urban mobility and addressing traffic congestion issues in Indian cities.

Road freight transit is growing at an exponential rate, and its environmental impact is becoming more pronounced. Conventional diesel-powered trucks contribute significantly to greenhouse gas emissions and air pollution, jeopardizing climatic stability and human health. Green freight corridors, also known as E-Corridors, have emerged as a promising alternative for integrating sustainable technologies and practices into critical freight routes. However, there is relatively little literature on how to scientifically and rationally identify potential corridors for green freight movement. To overcome this gap, the current work presents a systematic methodology for identifying possible freight corridors based on regional freight demand assessment. Visakhapatnam, a significant port city in the east, is used as a case study in the research. The primary, secondary and tertiary hinterlands of the study region are determined through primary and secondary surveying, including Origin and Designation surveys. Furthermore, these hinterlands are delineated into 31 freight zones, which are used to estimate freight demand. Furthermore, spatial and network analysis techniques in Arc GIS were utilized to detect important freight flow between zones in order to discover prospective green freight corridors. The vehicular turnover on these specific roadways was anticipated and modelled for the year 2047, and the results reveal a reasonably high count of ‘Multi Axle’ and ‘Two Axle’ vehicles, followed by ‘Three Axle’ and ‘Light Commercial’ vehicles. These studies identify four such corridors that have the ability to accommodate alternative fuel cars and can be converted into a ‘E-Corridor’ using existing infrastructure. In addition, the study also investigates alternative solutions such as electric vehicles and smart technologies that can be implemented along these identified green freight corridors, as well as a phased electrification roadmap for these corridors that adheres to current EV standards and capacities, culminating in full electrification by 2047. Thus, the overall study emphasizes the need for ongoing research in green technology and infrastructure in realizing the full potential of green freight corridors and paving the path for a cleaner and more efficient transportation system.