A sustainable transportation system is possible only through an efficient evaluation of transportation network performance. The efficiency of the transport network structure is analyzed in terms of its connectivity, accessibility, network development, and spatial pattern. This study primarily aims to propose a methodology for modeling the accessibility based on the structural parameters of the urban road network. Accessibility depends on the arrangement of the urban road network structure. The influence of the structural parameters on the accessibility is modeled using Multiple Linear Regression (MLR) analysis. The study attempts to introduce two methods of Artificial Intelligence (AI) namely Artificial Neural Networks (ANN) and Adaptive network-based neuro-fuzzy inference system (ANFIS) in modeling the urban road network accessibility. The study also focuses on comparing the results obtained from MLR, ANN and ANFIS modeling techniques in predicting the accessibility. The results of the study present that the structural parameters of the road network have a considerable impact on accessibility. ANFIS method has shown the best performance in modeling the road network accessibility with a MAPE value of 0.287%. The present study adopted Geographical Information Systems (GIS) to quantify, extract and analyze different features of the urban transportation network structure. The combination of GIS, ANN, and ANFIS help in improved decision-making. The results of the study may be used by transportation planning authorities to implement better planning practices in order to improve accessibility.
In most of the urban cities in India, the existing road network structure is unable to meet the increasing travel demand. In this context, there is a need to utilize the existing road network in a more efficient manner. To effectively utilize the existing road network, the structural parameters like connectivity, accessibility, hierarchy and morphology should be analyzed and evaluated. This study aimed to analyze and evaluate the road network structure of Hyderabad city, Telangana state, India in terms of its connectivity. Different places in Hyderabad city were considered to quantify the connectivity measures such as alpha index, beta index, gamma index, eta index, Cyclomatic number and Aggregate transportation score. Five kilometers radius buffers were drawn from the center of each location to compute the connectivity measures. The results of the study may act as a guide to the transportation planning authorities to understand the level of connectivity at each location in the city and implement better planning practices to improve the level of connectivity in the city. Geographical Information Systems (GIS) is a platform used for better decision making in urban transportation planning. The present study also tried to prove the efficiency of GIS in analyzing the connectivity based performance of the transport network structure in the study area.
There is an increasing demand for transportation solutions that are responsive, safe, sustainable, smart and cost-efficient. This has resulted in increased emphasis on responsive intermodal transportation systems. WRITR provides an international forum for the critical evaluation and dissemination of research and development in all areas related to intermodal transportation. Research disseminated via WRITR has significant impact on both theory and practice, and is of value to academics, practitioners and policy makers in this field.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations –citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.