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It is an enduring challenge to know the underlying determinants (factors and actors) for developing safe roads from the driving behavior perspective. Human (driver) errors and violations are generally referred as the most frequent cause of road accidents. This research analyzed a driver questionnaire survey of 584 drivers covering their behavior (error and deliberate violations) and safety-related attitudes while completing their driving task, at four-legged signalized intersections in India. We analyzed the driver behavior in terms of lane choice, signage and marking apprehension, tailgating, and vehicle speed consciousness at intersections, and their tendency to commit errors or violations. Driving frequency was found to have a significant effect on both Inattentive Error/Confused Error (IE/CE) and Risky Self-willed Violation (RSV). Gender was found to significantly affect only RSV and age influences only IE/CE. Highway agencies can consider the findings in developing user-friendly and self-explanatory road infrastructure with improved road users’ safety features.
Prasanta K. Sahu; Avijit Maji; Bhargav Nath; Hyuk-Jae Roh. Questionnaire based study of drivers’ error and violation at four-legged signalized intersection. Transportation Letters 2021, 1 -12.
AMA StylePrasanta K. Sahu, Avijit Maji, Bhargav Nath, Hyuk-Jae Roh. Questionnaire based study of drivers’ error and violation at four-legged signalized intersection. Transportation Letters. 2021; ():1-12.
Chicago/Turabian StylePrasanta K. Sahu; Avijit Maji; Bhargav Nath; Hyuk-Jae Roh. 2021. "Questionnaire based study of drivers’ error and violation at four-legged signalized intersection." Transportation Letters , no. : 1-12.
Investigating the spatial transferability of freight generation (FG) models is an imperative research need to enable the usage of formerly estimated model parameters in new application contexts with or without the usage of local data. By understanding how to transfer models (and to what extent), planning agencies in large countries like India can save freight survey costs in regions where they lack the institutional capacity and resources. Due to geographically sprawling nature of most of the Indian cities, an important research question regarding transferability is whether the models developed for urban areas can provide accurate estimates of freight activity in the suburban areas or vice versa. This paper aims to provide two solutions to this problem: (i) compare the relative effectiveness of transferability depending up on the direction of transfer and (ii) assess which models can be transferred and which cannot. Data collected from seven cities are used for this study. A set of freight production (FP) models are developed using this data to understand the differential influence of geographical location and industry segment on the model coefficients. The estimated FP models show that suburban establishments exhibit significantly higher FP rates as compared to other establishments. Subsequently, transferability direction and accuracy are determined using standard metrics such as transfer R2, relative aggregate transfer error and transfer index. The transferability findings will provide actionable insights into development of FP models in regions with data constraints, which is of great value in an era of declining budgets for travel surveys.
Bhavani Shankar Balla; Prasanta K. Sahu; Agnivesh Pani. Are Freight Production Models Transferable between Urban and Suburban Areas? Guiding Model Transfer in Geographically Sprawling Indian Cities. Journal of The Institution of Engineers (India): Series A 2021, 102, 643 -656.
AMA StyleBhavani Shankar Balla, Prasanta K. Sahu, Agnivesh Pani. Are Freight Production Models Transferable between Urban and Suburban Areas? Guiding Model Transfer in Geographically Sprawling Indian Cities. Journal of The Institution of Engineers (India): Series A. 2021; 102 (3):643-656.
Chicago/Turabian StyleBhavani Shankar Balla; Prasanta K. Sahu; Agnivesh Pani. 2021. "Are Freight Production Models Transferable between Urban and Suburban Areas? Guiding Model Transfer in Geographically Sprawling Indian Cities." Journal of The Institution of Engineers (India): Series A 102, no. 3: 643-656.
Large urban freight traffic generators (LTGs) are large specialized buildings or landmarks housing multiple establishments and generate a significant truck trips at both disaggregate and aggregate levels. Identification of LTGs and quantifying their relationship with freight travel characteristics helps policymakers formulate necessary logistical interventions and reduce externalities from freight activity. Hence, this study proposes a methodology for identifying LTGs and exploring their interactions on freight travel, expenditure pattern, shipment pattern, and other establishment characteristics. A decision-tree approach called chi-squared automatic interaction detector (CHAID) algorithm is used to map these interactions. Results suggest that LTGs are distinctly associated with multiple variables such as shipment size, shipper expenditure, commodity classification, and business age characteristics. Business age is the best predictor across all models. These associations vary based on LTG definitions. Implications of this study would augment the efforts on interlinking LTGs with urban freight demand modeling systems and enable sustainable city logistics initiatives and last mile delivery management.
Aitichya Chandra; Agnivesh Pani; Prasanta K. Sahu; Bandhan Bandhu Majumdar; Sushant Sharma. Identifying large freight traffic generators and investigating the impacts on travel pattern: A decision tree approach for last-mile delivery management. Research in Transportation Business & Management 2021, 100695 .
AMA StyleAitichya Chandra, Agnivesh Pani, Prasanta K. Sahu, Bandhan Bandhu Majumdar, Sushant Sharma. Identifying large freight traffic generators and investigating the impacts on travel pattern: A decision tree approach for last-mile delivery management. Research in Transportation Business & Management. 2021; ():100695.
Chicago/Turabian StyleAitichya Chandra; Agnivesh Pani; Prasanta K. Sahu; Bandhan Bandhu Majumdar; Sushant Sharma. 2021. "Identifying large freight traffic generators and investigating the impacts on travel pattern: A decision tree approach for last-mile delivery management." Research in Transportation Business & Management , no. : 100695.
Commuting between an origin and destination pair is one of the most critical components of an individual's daily activity, and the associated trip satisfaction significantly influences a commuter's well-being. Owing to negative externalities associated with urban travel such as increased congestion, poor roadway infrastructure, inadequate and unreliable public transport system, safety and security concerns, a reduction in perceived trip satisfaction could be observed among Indian commuters. Thus, it is prudent to analyze commuters' perception towards associated trip satisfaction and related components for formulating policy instruments to improve commuters' experience. This paper identified the key determinants of perceived satisfaction related to different types of trips in the Indian capital New Delhi. A Travel survey questionnaire was designed to elicit commuters' perceived satisfaction associated with daily, work, and non-work trips. Based on 898 responses, a set of ordered logit models were estimated. It was found that socio-demographic factors such as gender and age, accessibility and built-environment characteristics such as streets' level of congestion, availability and existing condition of sidewalks, bus stop safety, and security were significant determinants of commuters' trip satisfaction. Results also indicated that the choice of mode and associated safety perception played a vital role in commuters' trip satisfaction levels. Public transport users were less satisfied compared to the car commuters for both work and non-work trips. Based on the findings, a set of policy measures such as illumination of roadways, reduction in street-congestion levels, up keeping existing sidewalks, improving public transportation accessibility, etc. could be implemented for enhancing the trip-satisfaction level of urban commuters belonging to a typical metropolitan city of a developing country like India.
Bandhan Bandhu Majumdar; Malavika Jayakumar; Prasanta K. Sahu; Dimitris Potoglou. Identification of key determinants of travel satisfaction for developing policy instrument to improve quality of life: An analysis of commuting in Delhi. Transport Policy 2021, 110, 281 -292.
AMA StyleBandhan Bandhu Majumdar, Malavika Jayakumar, Prasanta K. Sahu, Dimitris Potoglou. Identification of key determinants of travel satisfaction for developing policy instrument to improve quality of life: An analysis of commuting in Delhi. Transport Policy. 2021; 110 ():281-292.
Chicago/Turabian StyleBandhan Bandhu Majumdar; Malavika Jayakumar; Prasanta K. Sahu; Dimitris Potoglou. 2021. "Identification of key determinants of travel satisfaction for developing policy instrument to improve quality of life: An analysis of commuting in Delhi." Transport Policy 110, no. : 281-292.
This paper analyses and compares transferability of freight production (FP) and freight trip production (FTP) models to provide guidance on when, when not, and how to transfer models from one spatial context to another. Separate sets of model parameters are estimated for various industry sectors in two regions within Kerala, a Southern State of India and are transferred to Jaipur, a Northern State of India. Model performance in five different transfer combinations are assessed to understand the degree of transferability of FP and FTP models which included intrastate transfers within Kerala and interstate transfers to Jaipur. Two approaches of updating model parameters using locally collected data are evaluated – Bayesian updating and combined transfer estimation – with metrics that measure transferability improvement. The relative performance of transferred models revealed that the degree of transferability of freight models vary widely across industry sectors and depends on: (i) measure of business size and the (ii) metric of measuring freight activity. That is, employment-based models show better transferability than area-based models and FP models are more transferable than FTP models. The transferability results also suggested that the interstate transferability is higher than interstate transferability. Overall, the study findings will assist planning agencies to: (i) identify the locational characteristics that restrict the transferability of freight models, (ii) develop modelling strategies that focus on the appropriate metric of measuring freight and business size indicators, and (iii) reduce costs and resources in regions where there is lack of institutional capacity to develop freight demand model systems.
Agnivesh Pani; Prasanta K. Sahu; Furqan A. Bhat. Assessing the Spatial Transferability of Freight (Trip) Generation Models across and within States of India: Empirical Evidence and Implications for Benefit Transfer. Networks and Spatial Economics 2021, 21, 465 -493.
AMA StyleAgnivesh Pani, Prasanta K. Sahu, Furqan A. Bhat. Assessing the Spatial Transferability of Freight (Trip) Generation Models across and within States of India: Empirical Evidence and Implications for Benefit Transfer. Networks and Spatial Economics. 2021; 21 (2):465-493.
Chicago/Turabian StyleAgnivesh Pani; Prasanta K. Sahu; Furqan A. Bhat. 2021. "Assessing the Spatial Transferability of Freight (Trip) Generation Models across and within States of India: Empirical Evidence and Implications for Benefit Transfer." Networks and Spatial Economics 21, no. 2: 465-493.
This paper contributes to the existing research on freight transportation, spatial and land use planning by investigating an improved spatial aggregation technique to delineate desirable freight traffic analysis zones. Zoning is a process of spatially aggregating several predefined basic spatial units (BSUs) into multiple zones. It plays a vital role in the transportation planning and decision-making process and is well-documented as the modifiable areal unit problem (MAUP). MAUP involves aggregating BSUs to obtain optimal zones satisfying specific criteria and constraints. This paper proposes an improved spatial aggregation methodology to develop a freight traffic analysis zone system by applying the multiobjective optimization concept using a genetic algorithm. The decision variables, namely, (i) Freight trip density; (ii) Number of establishments; (iii) Employment density; and (iv) Compactness, are chosen to represent the elements of freight, passenger traffic, and land use. The problem is formulated as a multiobjective network partitioning problem. The four objectives aim to create zones with better homogeneity and compactness. It is solved using a genetic algorithm with a weighted distance metric approach to prioritize the four objectives. Results show that zones resulting from the improved methodology are superior to the existing zones in terms of homogeneity of decision variables and compactness. The findings are expected to help the decision-making process of urban, transportation, and land-use planners in selecting appropriate freight traffic zone delineation strategies for a given region.
Aitichya Chandra; M.N. Sharath; Agnivesh Pani; Prasanta K. Sahu. A multi-objective genetic algorithm approach to design optimal zoning systems for freight transportation planning. Journal of Transport Geography 2021, 92, 103037 .
AMA StyleAitichya Chandra, M.N. Sharath, Agnivesh Pani, Prasanta K. Sahu. A multi-objective genetic algorithm approach to design optimal zoning systems for freight transportation planning. Journal of Transport Geography. 2021; 92 ():103037.
Chicago/Turabian StyleAitichya Chandra; M.N. Sharath; Agnivesh Pani; Prasanta K. Sahu. 2021. "A multi-objective genetic algorithm approach to design optimal zoning systems for freight transportation planning." Journal of Transport Geography 92, no. : 103037.
Activity center (AC) location allocation is a central concept for better quality of life, poverty reduction, accessibility maximization, and minimization of trip length and cost. An AC is characterized by p number of basic facilities present within it. The proposed framework identifies heuristically the potential locations of ACs that consist of multiple basic facilities. This article proposes a spatial planning framework to help policymakers while making infrastructure development decisions within budgetary limitations. For the application of this planning framework, a rural district in India is considered to allocate the location of ACs with four facilities: a health-care center, high school, bank, and market. The effect of AC developments on trip length is analyzed by preparing different activity chains to complete multiple trip purposes. Two cases are considered for location allocation of ACs. In the first case, we assumed that there is no facility existing in the study area; the latter case dealt with a situation where there are facilities already existing. In the case analysis, four categories of ACs are configured: AC4 with all four facility types, AC3 with any three facility types, AC2 with any two facility types, and AC1 with a single facility. Findings revealed that considerable trip cost savings in terms of trip length reduction could be realized from AC4 type activity centers over all other categories of AC. The policy context discussed in this article will not only help in maintaining uniformity in socioeconomic services over the region, but also, balance population density in physically isolated areas and densely populated areas. With the illustrated application, all the identified ACs with partial services within a region can be augmented to become full-fledged ACs in a phased manner, where infrastructure financing is constrained, particularly in lower and middle-income economies. In summary, the research framework will improve the quality of life in rural regions with a focus on better health, improved education, and an enhanced economy.
Sushreeta Mishra; Prasanta K. Sahu; Agnivesh Pani; Babak Mehran. Spatial Planning Framework for Development of Rural Activity Centers: Method of Location Allocation, Effect on Trip Length, and Policy Implications. Papers in Applied Geography 2021, 1 -20.
AMA StyleSushreeta Mishra, Prasanta K. Sahu, Agnivesh Pani, Babak Mehran. Spatial Planning Framework for Development of Rural Activity Centers: Method of Location Allocation, Effect on Trip Length, and Policy Implications. Papers in Applied Geography. 2021; ():1-20.
Chicago/Turabian StyleSushreeta Mishra; Prasanta K. Sahu; Agnivesh Pani; Babak Mehran. 2021. "Spatial Planning Framework for Development of Rural Activity Centers: Method of Location Allocation, Effect on Trip Length, and Policy Implications." Papers in Applied Geography , no. : 1-20.
Existing studies indicate that ideal spacing between bus stops improves the quality of service, travel time, and other transit service parameters. In this study, a network-wide heuristic methodology is proposed to optimize the number of stops in an existing bus network by eliminating redundant stops along each bus route in the network through an iterative process. It is postulated that ideal stop spacing can substantially lower the operating costs as it can reduce fleet size requirements without affecting the performance of the transit system. The proposed methodology attempts to eliminate undesired stops based on two vital inputs: (1) stop spacing, and (2) passenger boarding, which represent accessibility and travel time/delay. Potentially undesirable stops are eliminated recursively while their corresponding passenger boarding is redistributed across the adjacent stops. The process is repeated until ideal stop locations are identified. Stop location consolidation is evaluated using two performance indicators, i.e., in-vehicle travel time and access distance, which are considered for evaluating the performance of the modified bus network and comparing the total ridership with the existing network to justify the improvements. In other words, the ideal stop spacing is determined based on projected demand (ridership) loss and assessment of the performance indicators. The application of the proposed methodology is demonstrated using the bus network of the City of Regina in Saskatchewan, Canada. The findings of this research are expected to serve as a decision support tool for transit planners by offering additional flexibility to adopt appropriate bus stop spacing for an existing network.
Prasanta K. Sahu; Babak Mehran; Surya P. Mahapatra; Satish Sharma. Spatial data analysis approach for network-wide consolidation of bus stop locations. Public Transport 2021, 13, 375 -394.
AMA StylePrasanta K. Sahu, Babak Mehran, Surya P. Mahapatra, Satish Sharma. Spatial data analysis approach for network-wide consolidation of bus stop locations. Public Transport. 2021; 13 (2):375-394.
Chicago/Turabian StylePrasanta K. Sahu; Babak Mehran; Surya P. Mahapatra; Satish Sharma. 2021. "Spatial data analysis approach for network-wide consolidation of bus stop locations." Public Transport 13, no. 2: 375-394.
Electric two-wheelers (E2W) can help de-carbonize transport in Indian cities. To promote E2W as an attractive alternative compared to the conventional two-wheelers, an investigation on prospective users’ choice decisions is necessary. This paper proposed a comprehensive methodology to evaluate the prospective users’ choice decision toward electric two-wheelers and related attributes in the Indian context. In this paper, attributes such as Operating Cost (OC) savings, top speed, range, charging duration, acceleration, and purchase cost were considered to design a Stated Preference (SP) survey to collect data from prospective E2W users in Hyderabad, India. Concurrently, multinomial logit (MNL) and random parameter logit (RPL) models are developed, and the willingness-to-pay (WTP) associated with each of the identified attributes was estimated. Additionally, the effect of socio-economic characteristics on prospective users’ choice decision was also assessed. Subsequently, a sensitivity analysis was carried out to estimate the relative influence of the attributes on an individual’s choice decision in terms of the shift in probability to choose alternatives with better attribute levels than the base alternative. The results revealed that top speed was perceived as the most important attribute influencing an individual’s choice decision, followed by acceleration and charging duration. Age, income, and journey time significantly influenced an individual’s perception toward E2W and related attributes in the Indian context.
Mallikarjun Patil; Bandhan Majumdar; Prasanta Sahu; Long Truong. Evaluation of Prospective Users’ Choice Decision toward Electric Two-Wheelers Using a Stated Preference Survey: An Indian Perspective. Sustainability 2021, 13, 3035 .
AMA StyleMallikarjun Patil, Bandhan Majumdar, Prasanta Sahu, Long Truong. Evaluation of Prospective Users’ Choice Decision toward Electric Two-Wheelers Using a Stated Preference Survey: An Indian Perspective. Sustainability. 2021; 13 (6):3035.
Chicago/Turabian StyleMallikarjun Patil; Bandhan Majumdar; Prasanta Sahu; Long Truong. 2021. "Evaluation of Prospective Users’ Choice Decision toward Electric Two-Wheelers Using a Stated Preference Survey: An Indian Perspective." Sustainability 13, no. 6: 3035.
Freight transportation has received limited attention in the past compared to passenger transportation, especially in developing economies. However, the importance of freight transportation for the efficient functioning of any urban transportation system is gradually being realized. Estimating freight trips generated by the various manufacturing and service sectors in an urban setup is the primary step in freight transportation and management. For this purpose, segregating the various sectors and estimating freight trip generation is imperative. The primary aim of this study is to develop freight trip generation equations for one of the booming sectors in India, the restaurant service sector. The regions of Mumbai and Delhi-NCR are the focus of this study. About 150 restaurants (101 in Delhi-NCR, and 49 in Mumbai) were surveyed for this study. The face-to-face interview method at the establishments was adopted as the primary mode of data collection, primarily due to its high response rate. The daily average freight trips produced and attracted are observed to be approximately three vehicles and six vehicles, respectively. Separate models are estimated for freight trip attraction and production. It is observed that Poisson regression models for both attraction and production outperform the respective linear regression models. Poisson regression models are particularly useful when the dependent variable values are non-negative integers with sparse dispersion and a low mean. As far as the influencing variables are concerned, employment, vehicle ownership, and seating capacity are found to be significant for the freight trip models. The interaction variable formed by employment and vehicle ownership is used in the trip attraction model; similarly, a variable is created form the interaction of seating capacity and vehicle ownership in the trip production models.
Gopal R. Patil; Srinivas Thadoju; Prasanta K. Sahu; Aupal Mondal; Vaibhav Bajpai. Data Collection and Modeling of Restaurants’ Freight Trip Generation for Indian Cities. Transportation in Developing Economies 2021, 7, 1 -11.
AMA StyleGopal R. Patil, Srinivas Thadoju, Prasanta K. Sahu, Aupal Mondal, Vaibhav Bajpai. Data Collection and Modeling of Restaurants’ Freight Trip Generation for Indian Cities. Transportation in Developing Economies. 2021; 7 (1):1-11.
Chicago/Turabian StyleGopal R. Patil; Srinivas Thadoju; Prasanta K. Sahu; Aupal Mondal; Vaibhav Bajpai. 2021. "Data Collection and Modeling of Restaurants’ Freight Trip Generation for Indian Cities." Transportation in Developing Economies 7, no. 1: 1-11.
Concerns over transport energy consumption and greenhouse gas emissions have lately prompted significant attention towards vehicle ownership patterns and the distributional implications of climate mitigation policies. This paper contributes to freight transport literature by examining how establishments can be meaningfully grouped using their fleet ownership pattern (size and composition) and how these segments vary in their freight travel pattern and CO2 emission levels. The analysis performed using an establishment-based freight survey dataset from Kerala, a coastal state in India, revealed five latent classes of fleet ownership. The determinants of freight transport emissions and the gross emitters in fleet segments are presented subsequently by analyzing how the establishment-level characteristics (employment, business age, industry sector, value density, and relative location) explain the variation in CO2 emissions. The study findings offer insights for designing effective carbon policy instruments and incentive schemes to regulate the establishment-level freight travel pattern and control transport emissions.
Agnivesh Pani; Prasanta K. Sahu; José Holguín-Veras. Examining the determinants of freight transport emissions using a fleet segmentation approach. Transportation Research Part D: Transport and Environment 2021, 92, 102726 .
AMA StyleAgnivesh Pani, Prasanta K. Sahu, José Holguín-Veras. Examining the determinants of freight transport emissions using a fleet segmentation approach. Transportation Research Part D: Transport and Environment. 2021; 92 ():102726.
Chicago/Turabian StyleAgnivesh Pani; Prasanta K. Sahu; José Holguín-Veras. 2021. "Examining the determinants of freight transport emissions using a fleet segmentation approach." Transportation Research Part D: Transport and Environment 92, no. : 102726.
Weather events are arbitrary, and this makes it difficult to incorporate weather parameters into transportation models. Recent research on traffic weather interaction analysis conducted at the University of Regina, Canada reported traffic variations with cold temperatures and snowfall. The research team at the University of Regina proposed a linear association between snowfall and temperature to analyze the traffic variation on provincial highways during winter months. The variations were studies with the inclusion of the expected daily volume factor as an independent variable in the model structure. However, the study did not analyze the nature of the association between daily truck traffic volume and snowfall. Based on these drawbacks of the past studies, in this research, the objective is to focus on the effects of snow and temperature on traffic volume changes with a methodological help of Maximal Information Coefficient (MIC), which stems from the maximal information-based nonparametric exploration (MINE) statistics. The results obtained from the analysis indicate that the relationship between snow and truck traffic is non-linear. However, the study could not establish any functional relationship between snowfall and daily truck volume. It is desired to further conduct an hourly analysis to explore a new relationship between snowfall and truck volume.
Prasanta K. Sahu; Leela Manas Bayireddy; Hyuk-Jae Roh. A New Approach to Exploring the Relationship between Weather Phenomenon and Truck Traffic Volume in the Cold Region Highway Network. Modelling 2020, 1, 122 -133.
AMA StylePrasanta K. Sahu, Leela Manas Bayireddy, Hyuk-Jae Roh. A New Approach to Exploring the Relationship between Weather Phenomenon and Truck Traffic Volume in the Cold Region Highway Network. Modelling. 2020; 1 (2):122-133.
Chicago/Turabian StylePrasanta K. Sahu; Leela Manas Bayireddy; Hyuk-Jae Roh. 2020. "A New Approach to Exploring the Relationship between Weather Phenomenon and Truck Traffic Volume in the Cold Region Highway Network." Modelling 1, no. 2: 122-133.
This paper discusses the concept of facility center development by identifying locations for co-locating multiple facility types so as to access several facilities at a single location. This concept maximizes accessibility and reduces travel cost for individuals with multiple trip purposes. The appropriateness of facility center locations are evaluated with two parameters: 1) habitation accessibility to facility centers using Two-Step-Floating-Catchment-Area method (2SFCA), and 2) facility center crowdedness using inverted Two-Step-Floating-Catchment-Area method (i2SFCA). This study uses both 2SFCA and i2SFCA method concurrently to get perception of quality of service provided and received. Considering two facilities such as health care center and high school for spatial planning of facility centers, the proposed methodology is analyzed for two cases. In the first case, it is assumed that no facility exists in the study area and in the second case, the existing location of health care centers and high schools are considered for analysis. The proposed methodology is applied in Jhunjhunu – a district in Rajasthan, India as a case study. Discussed policy strategy would help for resource allocation in phased manner for new facility development or capacity augmentation of existing facilities; thus would improve the quality of rural citizen’s life
Sushreeta Mishra; Prasanta K. Sahu. Facility Centers in Rural Areas: Concept, Development, Effect on Habitational Accessibility and Facility Crowdedness, and Policy Strategies for Resource Allocation. Papers in Applied Geography 2020, 7, 82 -103.
AMA StyleSushreeta Mishra, Prasanta K. Sahu. Facility Centers in Rural Areas: Concept, Development, Effect on Habitational Accessibility and Facility Crowdedness, and Policy Strategies for Resource Allocation. Papers in Applied Geography. 2020; 7 (1):82-103.
Chicago/Turabian StyleSushreeta Mishra; Prasanta K. Sahu. 2020. "Facility Centers in Rural Areas: Concept, Development, Effect on Habitational Accessibility and Facility Crowdedness, and Policy Strategies for Resource Allocation." Papers in Applied Geography 7, no. 1: 82-103.
Air freight transportation is paramount for the expansion of trade and economic growth of any country. Recent statistics indicates that developing countries like India, are showing continuous growth trend in air freight sector; however, the modelling efforts for the air freight are scarce as compared to other freight mode. This paper analysed the relationship between air freight demand and airport characteristics using the aggregate data collected from the 42 airports around India. A set of statistical models were developed using regression analyses to estimate the air freight tonnage in an airport. The models are designed by considering their practical applications in facility planning and investment decision for airport infrastructure. Three different types of determinants were identified related city, physical, and operational characteristics of the airports. The results showed that number of industrial units in the city is a key determinant in predicting the air freight demand followed by population. On the other hand, physical and operational characteristics such as runway length, building area, passenger volume, and aircraft movement showed better correlation with freight activities. Another important finding is that the air freight demand will significantly change based on the city type in which the airport is located. Comparison of modelling results using different approaches revealed that that panel data regression models using airport’s operational characteristics gives better presentation of air-freight movement. Overall, the air freight demand models discussed in this paper may be utilized in facility planning, policy effect analysis and access road improvements of airports in India.
Manoharan Veerappan; Prasanta K Sahu; Agnivesh Pani; Gopal R Patil; Ashoke K Sarkar. Analysing and modelling the relationship between air freight movement and airport characteristics in India. Transportation Research Procedia 2020, 48, 74 -92.
AMA StyleManoharan Veerappan, Prasanta K Sahu, Agnivesh Pani, Gopal R Patil, Ashoke K Sarkar. Analysing and modelling the relationship between air freight movement and airport characteristics in India. Transportation Research Procedia. 2020; 48 ():74-92.
Chicago/Turabian StyleManoharan Veerappan; Prasanta K Sahu; Agnivesh Pani; Gopal R Patil; Ashoke K Sarkar. 2020. "Analysing and modelling the relationship between air freight movement and airport characteristics in India." Transportation Research Procedia 48, no. : 74-92.
The first step in transportation planning studies is the discretization of study area into numerous zones. Zoning systems are expected to reflect the characteristics of the area they divide and is of crucial importance to the planning process. In order to obtain zones appropriate for freight demand modelling, the zoning process needs to be incorporated with zonal characteristics that account for inter-zone variability of freight movements. These zones can be termed as Freight Traffic Analysis Zones (FTAZs). Although these zones will ease the task of freight data collection, compatibility should exist between zoning systems for passenger and freight movements. The existing zoning systems, such as census boundaries, lacks the generalizability to use in passenger and freight transportation planning framework, hence needs to be updated. Rather than using the existing zones or completely changing them on an administrative scale, the alternative option could be to update the zones by regrouping them using an automated zone design methodology. The objective of automated zone design is to maximize the homogeneity in FTAZs using a cluster analysis while effectively incorporating the essential contiguity criteria. This could be efficiently done on a Geographic Information System (GIS) platform. This research aims to demonstrate the design of FTAZs by performing clustering analysis of basic spatial units in a GIS platform. Jaipur Metropolitan region is taken as a case study in this paper to execute the methodology with the use of publicly available data sources. The analyses and findings presented in this paper should be helpful for identifying appropriate zone delineation strategies for developing freight demand models.
Aithichya Chandra; Agnivesh Pani; Prasanta K Sahu. Designing Zoning Systems for Freight Transportation Planning: A GIS-based approach for Automated Zone Design using Public Data Sources. Transportation Research Procedia 2020, 48, 605 -619.
AMA StyleAithichya Chandra, Agnivesh Pani, Prasanta K Sahu. Designing Zoning Systems for Freight Transportation Planning: A GIS-based approach for Automated Zone Design using Public Data Sources. Transportation Research Procedia. 2020; 48 ():605-619.
Chicago/Turabian StyleAithichya Chandra; Agnivesh Pani; Prasanta K Sahu. 2020. "Designing Zoning Systems for Freight Transportation Planning: A GIS-based approach for Automated Zone Design using Public Data Sources." Transportation Research Procedia 48, no. : 605-619.
Semi-flexible transit (SFT) service pattern coupled with real-time dynamic scheduling of passenger requests and dynamic route assignment of vehicles is considered as a cost-effective alternative to serving public transportation users in low demand conditions. Transit agencies tend to provide SFT by delivering it in-house by public transit agencies or contracting-out to private operators like transportation network-, taxi- or microtransit companies. Past studies focussing on economic issues in implementing SFT delivery models mostly used rudimentary information provided by transit agencies to quantify the operating cost, including budgetary inputs such as average annual maintenance, fuel, and administrative costs. These aggregate costs imply a uniform cost for SFT operation per unit time; however, the cost is subjected to change through spatial and temporal variations in demand and service. This study developed analytical disaggregate operating cost models that could account for marginal variations in cost due to the change in demand and service characteristics. Such model can assist policymakers while evaluating the economic feasibility of SFT delivery models. Rigorous and approximate operating cost models are developed for two competing service patterns: commonly adopted fixed-route bus transit (FRBT) and proposed SFT. Assuming in-house delivery of FRBT, SFT operating cost Eq.s are derived for two service delivery models, namely Contract-Out Taxi, and In-House Transit. Subsequently, these cost models are used to identify the critical passenger demand, where service patterns or delivery models could replace one another to minimize the total cost of operation. Study models can be used as part of a decision support tool to establish contracting, planning, and operating policies to optimize SFT operation subjected to required service quality.
Sushreeta Mishra; Babak Mehran; Prasanta K. Sahu. Assessment of delivery models for semi-flexible transit operation in low-demand conditions. Transport Policy 2020, 99, 275 -287.
AMA StyleSushreeta Mishra, Babak Mehran, Prasanta K. Sahu. Assessment of delivery models for semi-flexible transit operation in low-demand conditions. Transport Policy. 2020; 99 ():275-287.
Chicago/Turabian StyleSushreeta Mishra; Babak Mehran; Prasanta K. Sahu. 2020. "Assessment of delivery models for semi-flexible transit operation in low-demand conditions." Transport Policy 99, no. : 275-287.
This paper contributes to the emerging literature on freight studies by identifying the optimal freight traffic analysis zone (FTAZ) system at which to conduct macro-level freight travel analysis. To arrive at the optimal scale, we develop alternate zone systems by grouping census wards with similar freight-related characteristics (industrial characteristics, commercial land use characteristics, locational characteristics and socio-demographic characteristics). The resultant zone systems are analysed at multiple geographic scales and the optimal scale of each zone system is determined by performing the Brown–Forsythe test. Results suggest that a 1:3 aggregation ratio (24–28 zones) is the optimal scale for Metropolitan FTAZs, whereas the publicly available ad-hoc zone system and prior literature on National FTAZs follow 1:10 aggregation. The study findings suggest that Metropolitan planning organizations need to reconsider their existing data collection strategy, consider a larger aggregation ratio and, by extension, adopt smaller zones to ensure that both local and global freight travel characteristics are captured in freight travel analyses.
Prasanta K. Sahu; Aitichya Chandra; Agnivesh Pani; Bandhan Bandhu Majumdar. Designing freight traffic analysis zones for metropolitan areas: identification of optimal scale for macro-level freight travel analysis. Transportation Planning and Technology 2020, 43, 620 -637.
AMA StylePrasanta K. Sahu, Aitichya Chandra, Agnivesh Pani, Bandhan Bandhu Majumdar. Designing freight traffic analysis zones for metropolitan areas: identification of optimal scale for macro-level freight travel analysis. Transportation Planning and Technology. 2020; 43 (6):620-637.
Chicago/Turabian StylePrasanta K. Sahu; Aitichya Chandra; Agnivesh Pani; Bandhan Bandhu Majumdar. 2020. "Designing freight traffic analysis zones for metropolitan areas: identification of optimal scale for macro-level freight travel analysis." Transportation Planning and Technology 43, no. 6: 620-637.
A metro infrastructure, facility, and service quality investigation based on commuter perception was conducted in this study to explore and prioritize the key attributes influencing overall metro service quality in a typical Indian context. Based on the critical state-of-the-art review, 12 key attributes were identified and they were accommodated in a paper-based questionnaire to elicit commuter perception of importance and satisfaction by using a five-point Likert scale. Subsequently, TOPSIS, an extensively adopted multi-attribute decision-making technique, was carried out to rank the attributes with respect to perceived importance and satisfaction. Then an importance satisfaction analysis (ISA) was conducted to further classify the attributes in four quadrants based on their perceived degree of importance and satisfaction using an ISA matrix. Finally, the derived results from the TOPSIS and ISA analysis were combined and compared to obtain a prioritized set of attributes requiring intervention for better metro service quality in an Indian context. Results of this study clearly indicated the relative strengths and weaknesses of each metro service/infrastructure-specific attribute and presented the probable role of metro authorities for each of them. Attributes such as metro fare, connection to metro, and metro frequency were observed to be the most important, but were not performing satisfactorily, indicating that more emphasis is required on these attributes to improve the overall quality of travel by metro rail in an Indian context. Thus, this methodology would be instrumental in detecting a set of priority areas for improvement in metro rail services, which could contribute to retaining existing commuters and attracting new metro users.
Bandhan Bandhu Majumdar; Dilum Dissanayake; Avanindra Singh Rajput; Yong Qi Saw; Prasanta Sahu. Prioritizing Metro Service Quality Attributes to Enhance Commuter Experience: TOPSIS Ranking and Importance Satisfaction Analysis Methods. Transportation Research Record: Journal of the Transportation Research Board 2020, 2674, 124 -139.
AMA StyleBandhan Bandhu Majumdar, Dilum Dissanayake, Avanindra Singh Rajput, Yong Qi Saw, Prasanta Sahu. Prioritizing Metro Service Quality Attributes to Enhance Commuter Experience: TOPSIS Ranking and Importance Satisfaction Analysis Methods. Transportation Research Record: Journal of the Transportation Research Board. 2020; 2674 (6):124-139.
Chicago/Turabian StyleBandhan Bandhu Majumdar; Dilum Dissanayake; Avanindra Singh Rajput; Yong Qi Saw; Prasanta Sahu. 2020. "Prioritizing Metro Service Quality Attributes to Enhance Commuter Experience: TOPSIS Ranking and Importance Satisfaction Analysis Methods." Transportation Research Record: Journal of the Transportation Research Board 2674, no. 6: 124-139.
Freight studies have traditionally used business size measures such as employment and gross floor area as predictors of freight generation, giving very limited attention to the effects of an establishment’s age on freight demand. This study uses establishment-based freight survey data collected in seven cities of Kerala, India, to analyze the impacts of the age of an establishment on its freight demand. This is achieved by grouping the establishments into pre-specified classes with relatively homogeneous freight demand pattern. This classification is based on a data-driven a posteriori segmentation of industrial classes. These groups are further divided into sub-groups based on founding year of an establishment. As the business age increases, establishments grow in business size indicators and hence the changes in productivity can be either because of age or because of size or both. It is very important to separate the effects of these two indicators. The Blinder–Oaxaca decomposition method is used in this study to disentangle the effects of size and age on freight production and freight trip production. Age is found to be a fundamental driver of freight demand in younger establishments while the explanatory power of business size variables in explaining freight demand diminishes with age. The study findings illustrate the potential omitted variable bias that can occur when freight demand is estimated using business size indicators, without controlling for the business age differences.
Agnivesh Pani; Furqan A. Bhat; Prasanta Sahu. Effects of Business Age and Size on Freight Demand: Decomposition Analysis of Indian Establishments. Transportation Research Record: Journal of the Transportation Research Board 2020, 2674, 112 -126.
AMA StyleAgnivesh Pani, Furqan A. Bhat, Prasanta Sahu. Effects of Business Age and Size on Freight Demand: Decomposition Analysis of Indian Establishments. Transportation Research Record: Journal of the Transportation Research Board. 2020; 2674 (2):112-126.
Chicago/Turabian StyleAgnivesh Pani; Furqan A. Bhat; Prasanta Sahu. 2020. "Effects of Business Age and Size on Freight Demand: Decomposition Analysis of Indian Establishments." Transportation Research Record: Journal of the Transportation Research Board 2674, no. 2: 112-126.
Sugarcane bagasse ash (SCBA), a by-product from sugar industry, has been evidently reported as a potential alternative cementitious material that can partially replace cement. In spite of its high valorization potential in cement production, the large quantity of bagasse ash generated from Indian sugar plants (44,220 tonnes/day) is entirely unutilized and disposed as waste. Lack of comprehensive SCBA availability and accessibility studies are the major deterrents for the effective utilization of SCBA in industrial scale applications. This study investigated the availability of bagasse ash, fly ash, and slag in India, and their accessibility to existing cement plants. A comparative network analysis using ArcGIS was adopted, to assess the benefits of using bagasse ash in cement plants. Bagasse ash was found to be a potentially viable supplementary cementitious material in three out of the five major sugar-producing states of India. It is shown that switching over to bagasse ash results in significant reduction of carbon emissions associated with logistics (5.41 million tonnes/year). Strategic locations for new cement plants were identified based on availability of bagasse ash, using location-allocation analysis. A practical framework has also been presented for the effective utilization and recycling of sugar industry wastes in the construction sector.
G. Athira; A. Bahurudeen; Prasanta Sahu; Manu Santhanam; Prakash Nanthagopalan; S. Lalu. Effective utilization of sugar industry waste in Indian construction sector: A geospatial approach. Journal of Material Cycles and Waste Management 2020, 22, 724 -736.
AMA StyleG. Athira, A. Bahurudeen, Prasanta Sahu, Manu Santhanam, Prakash Nanthagopalan, S. Lalu. Effective utilization of sugar industry waste in Indian construction sector: A geospatial approach. Journal of Material Cycles and Waste Management. 2020; 22 (3):724-736.
Chicago/Turabian StyleG. Athira; A. Bahurudeen; Prasanta Sahu; Manu Santhanam; Prakash Nanthagopalan; S. Lalu. 2020. "Effective utilization of sugar industry waste in Indian construction sector: A geospatial approach." Journal of Material Cycles and Waste Management 22, no. 3: 724-736.