Passenger Experience Research Articles

Efficient User Pairing and Resource Optimization for NOMA-OMA Switching Enabled Dynamic Urban Vehicular Networks

Vehicular communication is revolutionizing transportation by enhancing passenger experience and improving safety through seamless message exchanges with nearby vehicles and roadside units (RSUs). To accommodate the growing number of vehicles in dense urban traffic with limited channel availability, non-orthogonal multiple access (NOMA) is a promising solution due to its ability to improve spectral efficiency by sharing channels among multiple users. However, to completely leverage NOMA on mobile vehicular networks, a chain of operations and resources must be optimized, including vehicle user (VU) and RSU association, channel assignment, and optimal power control. In contrast, traditional orthogonal multiple access (OMA) allocates separate channels to users, simplifying management but falling short in high-density environments. Additionally, enabling NOMA-OMA switching can further enhance the system performance while significantly increasing the complexity of the optimization task. In this study, we propose an optimized framework to jointly utilize the power domain NOMA in a vehicular network, where dynamic NOMA-OMA switching is enabled, by integrating the optimization of vehicle-to-RSU association, channel assignment, NOMA-OMA switching, and transmit power allocation into a single solution. To handle the complexity of these operations, we also propose simplified formulations that make the solution practical for real-time applications. The proposed framework reduces total power consumption by up to 27% compared to Util&LB/opt, improves fairness in user association by 18%, and operates efficiently with minimal computational overhead. These findings highlight the potential of the proposed framework to enhance communication performance in dynamic, densely populated urban environments.

Revisiting Passengers’ Perceptions of Airline Service Quality: A Theory-Driven Machine Learning Approach Using Big Data

ABSTRACT Understanding the discrepancy between passenger expectations and airline offerings is critical for improving service quality and customer satisfaction. This study expands the current knowledge regarding airline service quality dimensions by investigating actual passenger experiences. Analyzing 1,389,689 online reviews from TripAdvisor.com, structural topic modeling identified 29 airline service quality factors. Drawing upon AIRQUAL and SERVQUAL as theoretical frameworks, five unique dimensions emerged: flight attendance service, flight schedule, in-flight entertainment, in-flight meal, and baggage. Moreover, regression analysis highlights the significance of flight attendant services and hidden critical factors, such as attention to child passengers and special requests, in enhancing customer satisfaction. This study provides theoretical implications by uncovering airline service quality factors recognized by passengers and suggesting five potential service quality dimensions suitable for the airline context. Practically, the current study guides airline managers in understanding a passenger viewpoint and avoiding the service gap by combining machine learning, econometric approaches, and existing theories.

Sustainable Passenger Services and Child-Friendly Airport Experience: A Case Study of Istanbul Airport

This study explores the concept of child-friendly airports, using Istanbul Airport as a case study to understand how such environments can enhance the travel experience for families with children. Through qualitative research methods, including focus group discussion and in-depth interviews with 12 mothers and 12 field specialists, the research identified key attributes that constitute a child-friendly airport. Building upon the Place Diagram model, the results revealed that a child-friendly airport should prioritize sociability, comfort and image, uses and activities, and access and linkages, aligning with the model’s core themes. The results further identified numerous sub-themes linked to these four themes. Accordingly, airports should offer diverse play areas, family-friendly seating, efficient wayfinding, and high-quality, sustainable materials to create a safe, inclusive, and engaging environment for passengers with children. The study emphasizes the importance of designing airports that cater to the needs of children and their families, contributing to social equity and enhancing the overall passenger experience. These insights can serve as a benchmark for other airports aiming to improve their service offerings for families, supporting sustainable development goals related to reducing inequalities and promoting inclusive, safe, resilient, and sustainable environments. This study represents the first academic attempt focusing specifically on comprehensive services for passengers with children and the broader concept of child-friendly airports.

Short-Term Urban Rail Passenger Flow Prediction using TCN-LSTM Model

Predicting short-term passenger flow in urban rail transit systems is crucial for efficient operation and management. The TCN-LSTM model, which combines Temporal Convolutional Networks (TCNs) and Long Short-Term Memory (LSTM) networks, offers a robust solution for this task. TCNs provide an expansive receptive field, enabling the model to capture long-range dependencies and trends in passenger flow data. Meanwhile, LSTMs are adept at handling sequential data, refining the temporal features extracted by the TCN layers to account for short-term dependencies and fluctuations. This hybrid approach leverages the strengths of both architectures, resulting in a model that can accurately predict passenger volumes, accommodating regular traffic patterns and sudden changes in rider behavior. The implementation of the TCN-LSTM model in urban rail transit systems leads to optimized train schedules, improved service efficiency, and enhanced passenger experiences. By enabling more dynamic and responsive transit management, this model plays a pivotal role in addressing the challenges of modern urban transportation.

CRUISE TOURIST EXPERIENCE: AN ANALYSIS FROM TRIPADVISOR REVIEWS

Cruise tourism has grown in popularity, making it essential to understand the experiences of tourists who choose this unique mode of travel. This study examines the cruise tourist experience through the analysis of TripAdvisor reviews, focusing on key factors that shape customer satisfaction and overall travel experience. Utilizing content analysis, a comprehensive dataset of cruise reviews was analyzed to identify recurring themes such as service quality, onboard activity, and perceived value The results indicate that positive cruise experiences are heavily influenced by personalized service, high-quality food, and diverse entertainment offerings, while negative experiences often stem from overcrowding, service delays, and itinerary changes. This research provides valuable insights into the aspects of cruise tourism that enhance or diminish customer satisfaction. These findings offer practical implications for cruise operators looking to improve service quality and enhance the overall travel experience for cruise passengers. Further research recommendations are provided to explore variations in experience across different demographics and cruise types.

Advanced semantic segmentation of aircraft main components based on transfer learning and data-driven approach

Abstract The implementation of Smart Airport and Airport 4.0 visions relies on the integration of automation, artificial intelligence, data science, and aviation technology to enhance passenger experiences and operational efficiency. One essential factor in the integration is the semantic segmentation of the aircraft main components (AMC) perception, which is essential to maintenance, repair, and operations in aircraft and airport operations. However, AMC segmentation has challenges from low data availability, high-quality annotation scarcity, and categorical imbalance, which are common in practical applications, including aviation. This study proposes a novel AMC segmentation solution, employing a transfer learning framework based on a sophisticated DeepLabV3 architecture optimized with a custom-designed Focal Dice Loss function. The proposed solution remarkably suppresses the categorical imbalance challenge and increases the dataset variability with manually annotated images and dynamic augmentation strategies to train a robust AMC segmentation model. The model achieved a notable intersection over union of 84.002% and an accuracy of 91.466%, significantly advancing the AMC segmentation performance. These results demonstrate the effectiveness of the proposed AMC segmentation solution in aircraft and airport operation scenarios. This study provides a pioneering solution to the AMC semantic perception problem and contributes a valuable dataset to the community, which is fundamental to future research on aircraft and airport semantic perception. Graphical abstract

Optimizing the function of aircraft WiFi based on the Internet of Things

Abstract. This paper explores the potential of full-duplex wireless communication technology to mitigate interference in aircraft WiFi systems, thereby enhancing the internet access quality and passenger experience. The study focuses on the application of Internet of Things (IoT) technology to improve the resilience of aircraft WiFi systems against interference. Through a series of MATLAB simulations, the research demonstrates that full-duplex technology can effectively cancel out interference signals, leading to clearer and more stable communication quality. The results show that the combined signal, after cancellation, closely resembles the original communication signal, indicating a significant reduction in interference. Despite the promising results, the study acknowledges limitations such as idealized assumptions in the simulation, hardware and software constraints, and the lack of consideration for the complex electromagnetic environment encountered during actual flight operations. Future research should focus on developing more advanced interference detection and mitigation algorithms, and further investigation into the integration of full-duplex technology with existing aircraft WiFi systems, considering hardware constraints and environmental factors, is necessary to fully realize its potential in enhancing communication performance.

The Application of Near Field Communication (NFC) in Public Transportation: Current Practices, Challenges, and Future Prospects

In the field of public transportation, the introduction of NFC technology can realize contactless payment and automatic ticket checking functions, significantly improving system efficiency and passenger experience. The article first reviews the development history of the public transportation system and the basic principles of NFC technology, and then analyzes the technical architecture and working principle of the NFC payment system. Through the cases of public transportation systems in many cities around the world, the practical application and effect of NFC technology are demonstrated. This article also verifies the transaction speed, stability and user satisfaction of NFC technology in the public transportation system through a series of experimental evaluations. The results show that NFC technology has excellent performance in terms of processing speed, system stability and user satisfaction, especially during peak hours, its advantages are more obvious. At the same time, the research also pointed out the limitations of current NFC technology applications and the challenges faced in practical applications. In the future, NFC technology will become more complete and is expected to provide passengers with a more personalized and intelligent service experience.

Simulation modeling of passengers flow at airport terminals to reduce delay and enhance level of service

Passenger delays are considered as global issues that influence the overall efficiency of an airport and competitiveness as well as restricting terminal developments. This paper studied Kuwait International Airport Terminal 4 (T4); a new expansion of the old airport. This study mainly aims to analyze the influence of the design on passenger flow in T4 and how it affected the capacity in addition to obtain a path for the passenger movement from the terminal entrance until they reach the gate of the aircraft and vice versa through CAST simulation model. The effect of the T4 design on the overall efficiency was found, the current flow conditions were analyzed and compared with the required Level of Service (LOS) and several developments and expansions were suggested. Passengers flow was studied to improve passenger experience, increase operational efficiencies, maximize retail revenues and increase security effectiveness. It was indicated that customs and security facilities require expansion in areas during peak hours to maintain a high level of performance. However, the check in premium showed the minimum gap between queue capacity and the declared queuing size indicating the high level of service in this area. The results revealed that immigration queueing requires expansion. Moreover, queuing area provision indicates no capacity issues to cope with maximum queue size. The provision of immigration counters according showed no adequate queuing space to cope with MQS. It is recommended to increase the number of economy check-in counters.

Navigating the challenges of public transport and urban mobility in Thohoyandou, South Africa

Background: Transport systems are an essential feature of functional urban settlements. Yet, almost all of South Africa’s secondary cities and small towns lack a true public transportation system. Because of this, quasi-public, privately operated mini-bus taxis are the main form of transport for most urban residents. Thohoyandou, Limpopo, a town of over 70 000 people, is a typical South African town in this regard.Objectives: The purpose of this research was to understand passenger experiences of mini-bus taxis in Thohoyandou, Limpopo province, South Africa.Method: This study used semi-structured interviews to explore the mobility challenges faced by the residents of Thohoyandou.Results: This study revealed several negative aspects impacting passenger experiences. Passengers consistently reported concerns regarding driver’s behaviour that compromised safety and security. This included overloading of vehicles and disregard for traffic regulations. Passengers also highlighted the challenges posed by poor transport infrastructure and a lack of reliable service. Collectively, these factors contribute to limited mobility options, increased transportation costs and a reduced quality of life. Furthermore, the shortcomings of mini-bus taxi services disproportionately affect people with disability, who already face significant societal barriers, further marginalising them within the transportation system.Conclusion: The government should increase investment in transport infrastructure, the enforcement of traffic laws and better driver training. However, a strong government combined with much political will is required if passengers and safety are to be the main priorities of the mini-bus taxi industry.Contribution: This study highlights challenges faced by public transport users in Thohoyandou, where mini-bus taxis serve as the main mode of transport. The challenges experienced by transport users not only reduce their mobility but also contribute to marginalisation of vulnerable groups, especially people with disability.

Research on High Frequency Usage Scenarios of Touch Interactive in Dynamic Scenarios

In the era of intelligence, the smart cockpit mainly consists of more abundant large LCD instrument panel, comprehensive touch control screen, advanced in-vehicle infotainment system, etc., to create a new user experience for drivers and passengers in the cockpit. With the development of smart cockpit, touch interaction has become one of the high-frequency ways for users to interact with cars. Performing touch interaction tasks in dynamic scenarios requires distraction that prevents it from keeping its eyes on the road. At present, the scene of touch interaction safety evaluation in the industry is concentrated on air conditioning and radio, but in the dynamic scene, the driver will carry out many other operations, such as making and receiving calls, playing music, navigation Settings, vehicle Settings and other functions, which will bring safety risks such as sight deviation. Therefore, it is very important to study the high-frequency use scenarios of touch interaction in dynamic scenarios, which is helpful for enterprises to develop and design more secure and convenient interaction methods.

The Service Experience Equity on Repatronage Intention within Public Transportation Services

In a highly competitive market, service providers are often expected to enhance their profitability by delivering superior service quality. This principle is evident among many public transportation providers in Malaysia, who strive to elevate the passenger experience through refined service offerings. The objective of this study is to examine the factors influencing repatronage intentions among public transportation users in Malacca, Malaysia, using the Service Experience Equity (SEE) framework. To demonstrate the causal connections between the variables, a regression analysis has been employed. The findings reveal that service atmosphere and personnel interactions significantly impact users' willingness to continue using these services. The study emphasizes the importance for management to prioritize customer experience by investing in service environment strategies that foster user engagement and discourage customer churn. It further underscores that both the overall service experience and the quality of employee-customer interactions are critical determinants of future patronage. Consequently, it is recommended that transportation service providers leverage these elements to create a competitive edge, thereby encouraging repeat usage and building long-term customer loyalty.

Exploring the Impact of Airport Services on Passenger Satisfaction in Tanzania: A Case Study of Julius Nyerere International Airport

Satisfying passengers at the airport has been the cornerstone for airlines and airports in air transport service. This study aimed to understand the effects of airline-related quality service dimensions on overall passenger satisfaction at airports. The study intended to analyse the effect of pre-flight, in-flight, and post-flight services on passenger satisfaction at the airport. Passengers begin to interact with air transport services when booking a ticket, and airline-related service dimensions are considered part of the broader concept of airport services, which should be integrated as they overlap in satisfying passengers at the airport. Previous research focused extensively on airport-related factors but overlooked the specific impacts of airline services on overall passenger satisfaction. The study was guided by Total airport experience framework considering holistic view of passenger satisfaction. The study used a descriptive research design which targeted all international passengers travelled through Julius Nyerere International Airport at the time of conducting this study. In this regard, the study included departing and arriving passengers from Terminal III at the final lounge and baggage claim area. The Webb et al (1996) guidelines were used to determine the sample size which suggests that for population above 2,000, a sample of 1% is appropriate; The population consisted of 18,000 passengers arriving and departing at Julius Nyerere international Airport during the time of conducting survey; thus 180 passenger were selected randomly ensuring that every passenger had an equal chance of being selected. Collection of data invloved questionnaires with close-ended and open-ended questions. Descriptive analysis of collected data was conducted to summarize the main variables through utilizing the Statistical Package for Social Science (SPSS) for data analysis to obtain percentages and frequencies. The findings indicated that several dimensions of airline-related service influence passenger satisfaction: pre-flight, in-flight, and post-flight dimensions. The findings revealed that these three dimensions positively affect passenger satisfaction. For instance, in pre-flight services, respondents reported satisfaction, highlighting the crucial role of effective management of pre-flight services in determining positive initial travel experiences. High satisfaction rates were also observed for in-flight services, emphasizing the importance of onboard amenities and crew responsiveness. However, post-flight services showed areas for improvement to enhance the overall passenger experience. Additionally, the results highlighted the strategic necessity for airlines and airports to prioritize service excellence across all touchpoints of the passenger journey. Enhancing service quality and responsiveness, particularly in mishap resolution and service delivery which are crucial for maintaining a competitive advantage and fostering customer loyalty. The study concluded that passenger satisfaction is highly influenced by three primary dimensions of airline related service: pre-flight, in-flight, and post-flight dimensions. The study recommends the Airline and airport operators to focus on improving service quality delivery across all touch points of passengers journey by implementing an integrated approach such as coordinated decision making.

The role of physical and social environments on the loyalty toward urban rail services: A consideration of stations and onboard

Although urban train services have been introduced in various developing countries, ridership for this mode of public transport (PT) remains low. In response, urban planning authorities are seeking ways to boost passenger loyalty to these services. However, the existing literature has scarcely examined the role of physical and social environments in fostering passenger loyalty. Additionally, how loyalty is developed throughout the passenger experience - both at stations and onboard - remains unclear. Addressing this gap, the current study develops a model based on the 'service quality-satisfaction-behavioural intentions' paradigm and the Stimulus-Organism-Response (S-O-R) model to examine how the physical and social environments, both at rail stations and onboard trains, impact passenger loyalty in the context of urban train services. Additionally, this study validates the multi-dimensionality of physical environments and social environments in this context. Data collected from urban rail passengers in Hanoi, Vietnam is analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). The findings reveal that the physical and social environments onboard trains significantly influence loyalty towards the urban train services, while the environments at stations do not have the same impact. Furthermore, both satisfaction at stations and onboard trains significantly affect the loyalty, though the influence of satisfaction with the onboard experience is much stronger than that of satisfaction with the stations. Practically, the findings assist PT authorities in evaluating existing systems and devising future PT development strategies. Also, the study informs PT providers of ways to improve passenger satisfaction and loyalty.

Analysis of the Application and Prospects of Intelligent Technology in Sustainable Railway Operations

With the rapid development of technology, intelligent technology plays an increasingly important role in the sustainable operation of railways. This paper explores the application and prospects of intelligent technology in sustainable railway operations, emphasizing its key roles in enhancing operational efficiency, strengthening safety assurance, optimizing passenger experience, and promoting environmental protection and energy conservation. Through intelligent dispatching, real-time monitoring, big data prediction, personalized services, and mobile ticketing technologies, the railway system achieves efficient resource allocation and service innovation. The intelligent transformation of railways demonstrates significant economic and social benefits, contributing to emission reduction targets and sustainable development. Future efforts should focus on strengthening top-level design, technological innovation, standard construction, and network security to advance the intelligent railway process and co-create a new era of smart, green, and efficient railway transportation.

Exploring Smart Airports’ Information Service Technology for Sustainability: Integration of the Delphi and Kano Approaches

Airport digitalization has revolutionized service delivery at passenger touchpoints, which leads to sustainable passenger loyalty. However, it is critical to determine whether this rapid transition to digital services genuinely enhances passenger satisfaction with airport services. This study uses a mixed-method approach to identify key traditional and technology-driven information services in smart airports. The specific aim is to determine the optimal balance in which digital technologies can effectively replace human-provided services to establish sustainable passenger loyalty. Two rounds of Delphi surveys were conducted with panels of 23 and 21 experts, followed by an online Kano survey with 401 international passengers. The Delphi analysis identified 16 key information service attributes, while the Kano analysis revealed that the majority of technology-based services were attractive and positively influenced passenger satisfaction. By contrast, human-based services were mostly indifferent, although some were vital for boosting satisfaction and preventing dissatisfaction. These results advance the current airport service research and provide practical insights into optimizing passenger experiences through the strategic integration of technology for sustainable smart airports while maintaining essential human-provided services.

Analysis of relationship between railway satisfaction and delay tolerance

Railway facilities, which are part of the service environment, may affect passenger delay tolerance during delays. With the increasing frequency of railway delays, it is essential for railway companies to understand how passengers perceive these disruptions and railway facilities. While previous studies have examined the relationship between satisfaction and tolerance in interpersonal relationships, less is known about the impact of service environments, such as railway facilities, on perceptions in transportation settings. This study investigates the relationship between passenger satisfaction with railway facilities and their tolerance of delays in hypothetical scenarios, covering both short and long delays during morning and evening commute. The results of structural equation modeling show that railway satisfaction positively affects delay tolerance, while anxiety caused by unclear information during delays negatively affects tolerance. Additionally, the study identified the facility improvements that would enhance service quality. These findings offer actionable insights for railway companies to mitigate the impact of delays and improve passenger experiences.

Human-Centric Design Model to Enhance the Passenger Experience of Airport Smart Security System

Many studies have overlooked the aspect of humans when it comes to the security system integration in an airport. Hence, this study aims to develop a human-centric smart security system at the Dubai International Airport (DXB) to enhance the passenger experience. This paper proposed a human-centric design model to assess passenger experience at the smart security gate in the DXB and uses the model to analyze the proposed model based on the feedback of passengers. The model is represented by the human-centric dimension of emotional/feeling, behavior, needs and requirements, usability, trust, cognitive, and ergonomics that has a relation with passenger experience. A survey was administered to 400 respondents who had experience using the airport security system at the DXB. Regression analysis was used to test the relationship within the model and establish a human-centric model. Usability tests were used to gain deeper insight and gauge a more in-depth opinion of the respondents. It was found that cognitive had a low influence on passenger experience, while most respondents viewed the model as very useful. The findings of the study will assist the airport industry and authorities in UAE airports to better position their security system and enhance the passenger experience.

Structured acoustic materials for mitigating low-frequencybroadband aircraft noise: transfer matrix method

This study investigates, by numerical modeling, the mitigation of low-frequency broadband aircraft noise using a structured assembly of acoustic materials using the Transfer Matrix Method. The prevalence of low-frequency aircraft noise poses challenges to environmental sustainability and passenger comfort. The investigation focuses on an approach that employs strategically arranged structured acoustic materials to attenuate undesirable noise frequencies. The Transfer Matrix Method is used to model the acoustic behavior of the structured assembly, enabling a comprehensive analysis of sound transmission and absorption properties. This method supports the design and optimization of the assembly. The performance of the structured assembly to selectively attenuate low-frequency broadband noise is assessed through numerical simulations. The paper discusses implications for aircraft design, considering factors such as weight and cost. The benefits for environmental impact and passenger experience are also explored. Challenges and limitations in the implementation of structured acoustic materials are examined. The configuration studied presents an assembly of structured metamaterials arranged in series and in parallel which are integrated into a layer of glass wool. Present research contributes to the development of sustainable solutions for low-frequency aircraft noise. The structured assembly analyzed shows promise for significant noise reduction while considering practical constraints.

Evaluation of the Impacts of On-Demand Bus Services Using Traffic Simulation

This paper uses smart card data from Melbourne’s public transport network to model and evaluate the impacts of a flexible on-demand transport system. On-demand transport is an emerging mode of urban passenger transport that relies on meeting passenger demand for travel using dynamic and flexible scheduling using shared vehicles. Initially, a simulation model was developed to replicate existing fixed-schedule bus performance and was then extended to incorporate on-demand transport services within the same network. The simulation results were used to undertake a comparative analysis which included reliability, service quality, operational efficiency, network-wide effectiveness, and environmental impacts. The results showed that on-demand buses reduced average passenger trip time by 30%, increased vehicle occupancy rates from 8% to over 50%, and reduced emissions per passenger by over 70% on an average weekday compared to fixed-schedule buses. This study also offers insights for successful on-demand transport implementation, promoting urban sustainability. It also outlines future research directions, particularly the need for accurate short-term passenger demand prediction to improve service provision and passenger experience.