Transportation Commons^™

Assessing The Perceived Safety Of Cyclists With Virtual Reality, Vahid Balali

Mineta Transportation Institute

In 2022, 7,522 pedestrians and 1,084 bicyclists were killed and approximately 67,000 pedestrians and 46,195 bicyclists injured in motor vehicle crashes on public roadways in the United States, according to the Insurance Institute for Highway Safety (IIHS). The transportation industry is faced with a pressing need to bolster the safety of these vulnerable road users. This research develops models of design and environmental factors that influence bicyclists’ and pedestrians’ perception of safety using Virtual Reality (VR) technology and ultimately informs transportation infrastructure design to better accommodate nonmotorized travelers. The goal of the bicycle element of this research is to develop …

Why Are Fairness Concerns So Important? Lessons From A Last-Mile Transportation System, Yiwei Chen, Hai Wang

Research Collection School Of Computing and Information Systems

The Last-Mile Problem refers to the provision of travel service for passengers from the nearest public transportation node to the final destination. The Last-Mile Transportation System (LMTS), which has recently emerged, provides on-demand last-mile transportation service for passengers. We consider an LMTS that consists of two types of passengers, regular-type passengers and special-type passengers (e.g., seniors, disabled people). The valuation of the last-mile service for special-type passengers is statistically higher than the one for regular-type passengers. Passengers incur disutility from waiting for the last-mile service. In this paper, we explore two fairness constraints on special-type passengers: (1) the fare for …

Political Turbulence And Aviation Safety: A Cross-National Analysis Of Political Stability's Effects On Aviation Accidents, Léa Faure, Lilliam Maria Cáceres Malachowski

Journal of Aviation/Aerospace Education & Research

To what extent does political stability affect aviation safety? This research aims to link domestic political conditions and public safety through the consideration of aviation accident frequency. Political instability can indeed have profound effects on reducing overall public safety in a variety of domains through its influence on public policies. Reduced regulations and governance efforts can appear in contentious contexts for less-prioritized fields. This could influence the reemergence of technical aviation risk factors like crew training and performance, maintenance issues, infrastructure problems, human errors, etc. This would highlight a correlation between such political instability and weaker aviation safety regulations, investments …

Long-Term Traffic Prediction Using Deep Learning Long Short-Term Memory, Ange-Lionel Toba, Sameer Kulkarni, Wael Khallouli, Timothy Pennington

School of Cybersecurity Faculty Publications

Traffic conditions are a key factor in our society, contributing to quality of life and the economy, as well as access to professional, educational, and health resources. This emphasizes the need for a reliable road network to facilitate traffic fluidity across the nation and improve mobility. Reaching these characteristics demands good traffic volume prediction methods, not only in the short term but also in the long term, which helps design transportation strategies and road planning. However, most of the research has focused on short-term prediction, applied mostly to short-trip distances, while effective long-term forecasting, which has become a challenging issue …

From Equitable Access To Equitable Usage: Moving Towards Data-Driven, Evidence-Based Cycling Assets Management, Kewei Ren, Yunping Liang, Chun-Hsing Ho

Durham School of Architectural Engineering and Construction: Faculty Publications

Cycling is increasingly recognized for its wide range economic, environmental, and health benefits as a mobility option. However, disparities in the provision and the quality of bicycle infrastructure persists. Ensuring fair access and usage of these benefits for all presents a significant challenge. As a result, establishing effective methodologies to evaluate cycling equity is critically important. This paper synthesizes research on infrastructure asset management with a focus on equity considerations in bicycle infrastructure. A systematic review of 19 North American studies critically examines how existing research categorizes vulnerable populations and assesses fairness. The results reveal that most existing analyses focus …

Whipped Into Shape: Infrastructure As Punishment For The Unruly Citizen, Eliza Mortimer

Anthós

This article interrogates how inflexible designs and policies of airline seating, as well as critical socio-political rhetoric, discipline and marginalize bodies that do not conform to normative standards. Situating airline seating within fat and disability studies models, Mortimer argues that these punitive measures are not neutral, but rather reflective of cultural narratives of productivity, morality, and bodily discipline. Mortimer draws from ethnographic analyses of first-person accounts and policy reviews to demonstrate how shrinking seats, rigid policies, and moralized discourse construct a “space of calculability” that pressures fat individuals to monitor and minimize their bodies to justify their presence in public …

Simulated Efficiency Of A Modified Bmw I3 Traction Motor Operating As An Isolated Dc-Dc Converter, Shayne Taylor

Graduate Research Theses & Dissertations

Battery electric vehicles are currently fighting to have any advantage over internal combustion engine powered vehicles to reduce global transportation greenhouse gas emissions. Electric motors are typically deemed as the largest source of loss in many vehicles but have recently become more efficient on average than the AC-DC converter used to charge the vehicle. This paper investigates the potential for a dual three phase electric traction motor based on a BMW i3 electric vehicle traction motor to take the place of an isolated DC-DC converter, an important part of the AC-DC converter. This electric machine in simulations produced a similar …

Psychosocial Determinants Of Public Transportation Use Among Brazilian And American Users: An Integrated Modeling Approach, Ingrid Luiza Neto, Hartmut Günther, Bryan E. Porter, Taciano L. Milfont, Pastor Willy Gonzales Taco, Caroline Cardoso Machado

Psychology Faculty Publications

Overreliance on cars can promote individual, environmental, economic and social problems, requiring the development of measures to reduce car use and encourage the use of more sustainable transport options. Contributing to this call, here we report a cross-cultural study conducted in Brazil (n = 312) and the United States (n = 518) investigating the applicability of the model of Bamberg and Möser in predicting the use of public transport. Results indicated the model is equivalent across samples, regarding both the measures and the relations between the variables of the model. Intention strongly predicted self-reported public transport behaviour, explaining 70% of …

Bi-Objective Dynamic Tugboat Scheduling With Speed Optimization Under Stochastic And Time-Varying Service Demands, Xiaoyang Wei, Hoong Chuin Lau, Zhe Xiao, Xiuju Fu, Xiaocai Zhang, Zheng Qin

Research Collection School Of Computing and Information Systems

With the growing emphasis on green shipping to reduce the environmental impact of maritime transportation, optimizing fuel consumption with maintaining high service quality has become critical in port operations. Ports are essential nodes in global supply chains, where tugboats play a pivotal role in the safe and efficient maneuvering of ships within constrained environments. However, existing literature lacks approaches that address tugboat scheduling under realistic operational conditions. To fill the research gap, this is the first work to propose the bi-objective dynamic tugboat scheduling problem that optimizes speed under stochastic and time-varying demands, aiming to minimize fuel consumption and manage …

Safety And Sustainability In The Domestic Ferry Sector : A Pci Framework For Esg-Aligned Maritime Governance, Mirza Zeeshan Baig

World Maritime University Ph.D. Dissertations

The domestic ferry sector is a significant component of maritime transportation. It strengthens social ties, supports economic growth and connects communities. Despites its importance, this industry faces ongoing challenges. These include fragmented governance, operational adequacies, safety risks and environmental concerns. The study deals with these issues by combining a systems-based approach with governance and change management theories. It examines the interplay between human, technical and organizational aspects. The study integrates the rule-based and rights-based maritime governance along with the Lewin’s three stage change management model (Unfreeze, Change, and Refreeze).

At the core of the study is the development of a …

Improving Onboard Training For Deck Cadets : An Analysis Through The Lens Of Learning Theories, Yusuke Mori

World Maritime University Ph.D. Dissertations

As a critical component of skill development and identity construction for prospective seafarers, onboard training has played a central role in Maritime Education and Training (MET). Each Maritime Education and Training Institution (METI) implements distinct onboard training arrangements based on its environmental, socio-cultural, and historical context, as well as the learning theories that inform its approach. However, the absence of a rigorous examination of the factors influencing national variations in onboard training creates challenges in establishing legal norms at the international level. Furthermore, the literature has identified a wide range of issues and challenges in the implementation of onboard training, …

Developing A Roadmap For Green Port In Timor-Leste, Emanuel Da Silva Maia

World Maritime University Dissertations

No abstract provided.

Breaking The Yoke: A Systematic Unmasking Of Challenges To Sustainable Rural Development In South Sudan, Gai Chol Paul

Journal of Sustainable Social Impact

South Sudan, a young nation grappling with the legacy of protracted conflict, faces significant challenges in fostering sustainable rural development. While the immense potential of its vast agricultural lands remains largely untapped, the persistent triple threat of insecurity, deficient infrastructure, and the absence of robust government policy actively hinders progress. The ongoing armed conflict, characterized by inter-communal violence and sporadic attacks, casts a long shadow over rural areas in South Sudan. Thus, I developed this mixed-method multiple-case study, grounded in the sustainable livelihoods framework, to explore challenges that hinder sustainable rural development in South Sudan. I collected data through document …

Organisational Resilience : A Study Of The Resilience Of Maritime Stakeholders In Ghana, Priscilla Ami Dogbeda Dzokoto

World Maritime University Dissertations

No abstract provided.

A Novel Approach To Evaluate Seatbelt Non-Compliance Of Drivers In New Jersey, Md Arifuzzaman Nayeem

Theses and Dissertations

This study intends to investigate the non-compliant behavior of drivers with seatbelt use in New Jersey. By examining various factors such as temporal and roadway characteristics, this study seeks to identify the underlying causes of this seatbelt non-compliance behavior. To overcome the limitations of traditional methods like cross-sectional data collection, a novel approach known as moving vehicle method was employed. To gain further insights, hypothesis tests were performed across the entire dataset to pinpoint significant temporal, roadway, and geometric factors contributing to non-compliant behaviors. In the subsequent step, the association of other risky behaviors like speeding and distracted driving with …

Moving Towards The Electrification Of Medium- And Heavy-Duty Vehicles In The Inland Empire, Kimberly Collins, Raffi Der Wartanian, Francisca Beer, Yunfei Hou

Mineta Transportation Institute

This report investigates the transition to zero-emission medium- and heavy-duty vehicles (MDHD) within California’s Inland Empire (IE), emphasizing the significance of electric vehicle charging infrastructure and opportunity charging strategies in facilitating sustainable transportation. Utilizing a mixed-methods approach that combines a systematic literature review, geospatial and big data analytics, and thematic analysis of expert interviews, the study explores the multifaceted challenges and opportunities of electrification. The literature review assesses policies at various governance levels, while geospatial analysis identifies regional traffic patterns and infrastructure needs. Big data analytics examine vehicle movements, complemented by insights from interviews with 16 regional experts, offering a …

Optimization Of Customer Service And Driver Dispatch Areas For On-Demand Food Delivery, Jingfeng Yang, Hoong Chuin Lau, Hai Wang

Research Collection School Of Computing and Information Systems

With the rapid development and popularization of mobile and wireless communication technologies, on-demand food delivery (OFD) platforms have been able to connect restaurants, customers, and drivers in real time, drastically changing dining and food delivery services. Motivated by the critical need for supply and demand management in the on-demand food delivery market, we focus on the optimization of customer service area and driver dispatch area for on-demand food delivery services. Specifically, for each restaurant, the platform needs to decide the (1) customer service area (CSA), i.e., the surrounding area within which customers can see the restaurant’s information and order food …

Path-Choice-Constrained Bus Bridging Design Under Urban Rail Transit Disruptions, Yiyang Zhu, Jian Gang Jin, Hai Wang

Research Collection School Of Computing and Information Systems

Although urban rail transit systems play a crucial role in urban mobility, they frequently suffer from unexpected disruptions due to power loss, severe weather, equipment failure, and other factors that cause significant disruptions in passenger travel and, in turn, socioeconomic losses. To alleviate the inconvenience of affected passengers, bus bridging services are often provided when rail service has been suspended. Prior research has yielded various methodologies for effective bus bridging services; however, they are mainly based on the strong assumption that passengers must follow predetermined bus bridging routes. Less attention is paid to passengers’ path choice behaviors, which could affect …

Segac: Sample Efficient Generalized Actor Critic For The Stochastic On-Time Arrival Problem, Honglian Guo, Zhi He, Wenda Sheng, Zhiguang Cao, Yingjie Zhou, Weinan Gao

Research Collection School Of Computing and Information Systems

This paper studies the problem in transportation networks and introduces a novel reinforcement learning-based algorithm, namely. Different from almost all canonical sota solutions, which are usually computationally expensive and lack generalizability to unforeseen destination nodes, segac offers the following appealing characteristics. segac updates the ego vehicle’s navigation policy in a sample efficient manner, reduces the variance of both value network and policy network during training, and is automatically adaptive to new destinations. Furthermore, the pre-trained segac policy network enables its real-time decision-making ability within seconds, outperforming state-of-the-art sota algorithms in simulations across various transportation networks. We also successfully deploy segac …

Enabling Sustainable Freight Forwarding Network Via Collaborative Games, Pang Jin Tan, Shih-Fen Cheng, Richard Chen

Research Collection School Of Computing and Information Systems

Freight forwarding plays a crucial role in facilitating global trade and logistics. However, as the freight forwarding market is extremely fragmented, freight forwarders often face the issue of not being able to fill the available shipping capacity. This recurrent issue motivates the creation of various freight forwarding networks that aim at exchanging capacities and demands so that the resource utilization of individual freight forwarders can be maximized. In this paper, we focus on how to design such a collaborative network based on collaborative game theory, with the Shapley value representing a fair scheme for profit sharing. Noting that the exact …

Time-To-Failure Prediction Of Fine-Grained Soil Slopes Subject To Weather-Driven Deterioration, Arm M. Morsy

Mineta Transportation Institute

Embankments have been widely used in the construction of transportation and flood defense infrastructure. Embankments constructed from clays experience a suite of weather-driven deterioration processes that lead to a progressive loss of hydromechanical performance, causing potentially severe and costly consequences. This study aimed to predict the time to failure of aging, deteriorating clay embankments supporting transportation infrastructure. A multi-phase numerical modeling approach was developed to replicate the long-term, weather-driven, hydromechanical behavior of clay embankments. This model simulated the behavior of a number of well-documented embankment failure case studies that had sufficient data to derive the necessary soil properties and climate …

Fine-Grained Passenger Load Prediction Inside Metro Network Via Smart Card Data, Xiancai Tian, Chen Zhang, Baihua Zheng

Research Collection School Of Computing and Information Systems

Metro system serves as the backbone for urban public transportation. Accurate passenger load prediction for the metro system plays a crucial role in metro service quality improvement, such as helping operators schedule train timetables and passengers plan their trips. However, existing works can only predict low-grained passenger flows of origin-destination (O-D) paths or inflows/outflows of each station but cannot predict passenger load distribution over the whole metro network. To this end, this paper proposes an end-to-end inference framework, PIPE, for passenger load prediction of every metro segment between two adjacent stations, by only utilizing smart card data. In particular, PIPE …

Reinforcement Learning For Strategic Airport Slot Scheduling: Analysis Of State Observations And Reward Designs, Anh Nguyen-Duy, Duc-Thinh Pham, Jian-Yi Lye, Nguyen Binh Duong Ta

Research Collection School Of Computing and Information Systems

Due to the NP-hard nature, the strategic airport slot scheduling problem is calling for exploring sub-optimal approaches, such as heuristics and learning-based approaches. Moreover, the continuous increase in air traffic demand requires approaches that can work well in new scenarios. While heuristics rely on a fixed set of rules, which limits the ability to explore new solutions, Reinforcement Learning offers a versatile framework to automate the search and generalize to unseen scenarios. Finding a suitable state observation and reward structure design is essential in using Reinforcement Learning. In this paper, we investigate the impact of providing the Reinforcement Learning agent …

Exploring Performance-Based Contracts: A Good Option To Address Long-Term Road Maintenance In California?, Maria Calahorra-Jimenez, Richard Poythress

Mineta Transportation Institute

Performance-based contracts (PBCs) used in road maintenance provide flexibility for considering new materials, design, and technology to achieve predetermined performance targets. Several states in the U.S. have already used these types of contracts in road maintenance, and their experience can inform the use of PBCs in California. The objectives of this research are twofold. First, identify the benefits and challenges of PBCs compared to traditional contracts. Second, explore the main aspects of PBCs implementation for road maintenance and relate them to California's context. To this end, deductive-inductive content analysis was conducted on 84 peer-reviewed articles published between 1998 and 2023. …

Adopt: An Environmentally-Friendly System For Alerting Drivers To Occluded Pedestrians Traffic, Abrar Abdulrahman Alali

Computer Science Theses & Dissertations

The emergence of sensing technologies and vehicular communications has brought significant opportunities for enhancing pedestrian safety on city streets. However, existing solutions rely on costly technologies such as computer vision and trajectory prediction to detect crossing pedestrians, while they have limits in detecting pedestrians who are occluded by parked cars. Despite the presence of collaborative perception by surrounding vehicles and infrastructure, there is a notable absence of incorporating existing parked cars themselves due to their insufficiency in detecting pedestrians and communicating with other cars while they are turned off. Furthermore, accommodating pedestrians on streets has been linked to an additional …

Experimental Investigation Of The Self-Healing Potential Of Bacteria For Sustainable Concrete Structures Phase 2, Andrea Calabrese, Pitiporn Asvapathanagul, Nisarg N. Patel, Nanubala Dhruvan, Austin Adams, Michael Hernandez, Douglas S. Lopez-Cruz

Mineta Transportation Institute

Concrete is a critical component of so much of the modern construction industry. This material, well known for its versatility, robustness, longevity, and strength, is well-suited for a wide range of structural applications. Nonetheless, the widespread occurrence of cracks in concrete structures, primarily attributed to its limited tensile strength, shrinkage, and overstain, imposes a considerable economic and environmental challenge when it comes to retrofitting these fissures. This study tackles this problem by harnessing bacteria tolerant to high alkaline conditions to enable Microbially Induced Calcium Carbonate Precipitation (MICP) for the self-repair of concrete. This is achieved through an external application method, …

Battery Management System Development For Electric Vehicles And Fast Charging Infrastructure Improvement, Yu Yang, Hen-Geul Yeh, Cesar Ortiz

Mineta Transportation Institute

The electric vehicle (EV) has become increasingly popular due to its being zero-emission. However, a significant challenge faced by EV drivers is the range anxiety associated with battery usage. Addressing this concern, this project develops a more efficient battery management system (BMS) for electric vehicles based on a real-time, state-of-charge (SOC) estimation. The proposed study delivers three modules: (1) a new equivalent circuit model (ECM) for lithium-ion batteries, (2) a new SOC estimator based on the moving horizon method, and (3) an on-board FPGA implementation of the classical Coulomb counting method for SOC estimation. The research team extends the traditional …

Network-Based Representations And Dynamic Discrete Choice Models For Multiple Discrete Choice Analysis, Huy Hung Tran, Tien Mai

Research Collection School Of Computing and Information Systems

In many choice modeling applications, consumer demand is frequently characterized as multiple discrete, which means that consumer choose multiple items simultaneously. The analysis and prediction of consumer behavior in multiple discrete choice situations pose several challenges. In this paper, to address this, we propose a random utility maximization (RUM) based model that considers each subset of choice alternatives as a composite alternative, where individuals choose a subset according to the RUM framework. While this approach offers a natural and intuitive modeling approach for multiple-choice analysis, the large number of subsets of choices in the formulation makes its estimation and application …

Smart Robot Design And Implementation To Assist Pedestrian Road Crossing, Hovannes Kulhandjian

Mineta Transportation Institute

This research focuses on designing and developing a smart robot to assist pedestrians with road crossings. Pedestrian safety is a major concern, as highlighted by the high annual rates of fatalities and injuries. In 2020, the United States recorded 6,516 pedestrian fatalities and approximately 55,000 injuries, with children under 16 being especially vulnerable. This project aims to address this need by offering an innovative solution that prioritizes real-time detection and intelligent decision-making at intersections. Unlike existing studies that rely on traffic light infrastructure, our approach accurately identifies both vehicles and pedestrians at intersections, creating a comprehensive safety system. Our strategy …

Addressing Data Limitations Of Commercial Waterways Via Machine Learning And Stochastic Optimization, Sanjeev Bhurtyal

Graduate Theses and Dissertations

Freight transportation is a crucial component of the US economy, with truck, rail, and water contributing significantly to the Gross Domestic Product (GDP). However, challenges arise in maintaining infrastructure capacity to accommodate the growing tonnage and value of freight transportation. Waterways offer high efficiency and environmental friendliness, with the capacity to transport substantial cargo volumes. Utilizing waterways can alleviate bottlenecks in landside transportation, accommodating the rising tonnage of commodity flow in the US. Despite the advantages of waterway transportation, the data limitations hinder informed decision-making regarding port operation and infrastructure investment. The lack of granularity and timeliness in available data …