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2025 Vol.3 No.1 cover

Open Access · 2025

2025 Vol.3 No.1


Transportation Development Research

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Table of Contents

7 articles
ArticleOpen AccessPublished: 17 June 2025

Enhancing Road Safety and Network Intelligence through Vehicleto-Everything (V2X) Communication: Architectures, Models, and Performance Analysis

Qutaiba Ibrahim Ali, Hussein M. Mohammed

Transportation Development Research · 1-13 · 10.55121/tdr.v3i1.426

Vehicle-to-Everything (V2X) communication is a transformative and rapidly advancing paradigm that enables real-time, bidirectional data exchange between vehicles, infrastructure, pedestrians, and broader network systems using wireless technologies. As urban mobility becomes more complex and traffic congestion, collision rates, a

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ArticleOpen AccessPublished: 30 June 2025

A Decomposition Model for Risk Equity and Network Accessibility Trade off in Hazardous Material Transportation: An Empirical Study

Abbas Mahmoudabadi

Transportation Development Research · 14-26 · 10.55121/tdr.v3i1.404

A major part of goods and substances transported across the world is categorized as hazardous materials (Hazmat) or dangerous goods. Hazmat transportation has potential risks in nature, so it is essential to avoid risk agglomeration in the most frequently selected routes while transport planning in practice. The concern leads au

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ArticleOpen AccessPublished: 30 June 2025

Integrating 5PL Frameworks with Drone-Based Last-Mile Delivery: A Model for Future-Ready Logistics

Tejinder Singh Lakhwani

Transportation Development Research · 27-45 · 10.55121/tdr.v3i1.449

The rapid evolution of logistics service providers from 1PL to 5PL has underscored the growing need for intelligent, data-driven orchestration across the supply chain. Simultaneously, drone-based delivery has emerged as a promising solution to last-mile challenges, particularly in urban congestion zones and infrastructure-defici

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ArticleOpen AccessPublished: 1 May 2025

Dynamic Evaluation of Bridges: A Case Study of the Chenab Bridge in India

Anshul Jain, Dr. Samir Patel

Transportation Development Research · 46-61 · 10.55121/tdr.v3i1.541

The Chenab Bridge, located in Jammu and Kashmir, India, is the world’s highest railway arch bridge, standing 359 meters above the Chenab River with a main arch span of 467 meters. This paper presents a comprehensive dynamic evaluation of the bridge, focusing on its response to seismic, wind, and blast loads, which are critical g

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ArticleOpen AccessPublished: 2 May 2025

Fuel Tankering Practices in Aviation and Average Origin-Airport Fuel Prices: Evidence from the Brazilian Domestic Market

Letícia Alves Tizeu, Mauro Caetano, Evandro José da Silva

Transportation Development Research · 62-71 · 10.55121/tdr.v3i1.456

Considered one of the most significant costs to aviation, the identification of strategies for aircraft fueling can contribute to optimizing air transportation resources. Therefore, this study investigates the practice of fuel tankering, addressing a theoretical gap resulting from the lack of comprehensive, network-wide route as

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ArticleOpen AccessPublished: 3 May 2025

Structural Design and Geotechnical Analysis of the Atal Tunnel: Engineering Solutions for High-Altitude Challenges

Anshul Jain, Hridayesh Varma

Transportation Development Research · 72-81 · 10.55121/tdr.v3i1.544

The Atal Tunnel, located in the Pir Panjal Range of the Himalayas in Himachal Pradesh, India, is the world’s longest highway tunnel above 10,000 feet (3,048 meters) with a length of 9.02 kilometers. This study details the tunnel’s structural components, safety features, and innovative engineering solutions, supported by data on

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ArticleOpen AccessPublished: 10 May 2025

Data–Driven Technology Foresight: Integrating ARIMA Forecasting and Network Analysis for Patent–Based Roadmapping in Korea’s Railway Industry

Yong-Jae Lee, Tae-Seong Lee

Transportation Development Research · 82-97 · 10.55121/tdr.v3i1.572

Traditional expert–driven technology foresight is often limited by subjectivity, low replicability, and high costs. To address these challenges, this study proposes a novel, data–driven framework for technology foresight that offers an objective, scalable, and multi–dimensional approach to identifying and prioritizing emerging t

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