Passenger Load Factor Research Articles

Modeling and Predicting Passenger Load Factor in Air Transportation: A Deep Assessment Methodology with Fractional Calculus Approach Utilizing Reservation Data

This study addresses the challenge of predicting the passenger load factor (PLF) in air transportation to optimize capacity management and revenue maximization. Leveraging historical reservation data from 19 Turkish Airlines market routes and sample flights, we propose a novel approach combining deep assessment methodology (DAM) with fractional calculus theory. By modeling the relationship between PLF and the number of days remaining until a flight, our method yields minimal errors compared to traditional techniques. Through a continuous curve constructed using the least-squares approach, we enable the anticipation of future flight values. Our analysis demonstrates that the DAM model with a first-order derivative outperforms linear techniques and the Fractional Model-3 in both modeling capabilities and prediction accuracy. The proposed approach offers a data-driven solution for efficiently managing air transport capacity, with implications for revenue optimization. Specifically, our modeling findings indicate that the DAM wd model improves prediction accuracy by approximately 0.67 times compared to the DAM model, surpassing the fractional model and regression analysis. For the DAM wd modeling method, the lowest average mean absolute percentage error (AMAPE) value achieved is 0.571, showcasing its effectiveness in forecasting flight outcomes.

Adaptive Equivalent Factor-Based Energy Management Strategy for Plug-In Hybrid Electric Buses Considering Passenger Load Variations

Energy management strategies (EMSs) are one of the key technologies for the development of plug-in hybrid electric buses (PHEBs). This paper addresses the issue of optimal energy distribution for PHEBs under significant variations in passenger load at different bus stations, which cannot be solved by a single equivalent factor equivalent fuel consumption minimization energy management strategy (ECMS). An adaptive equivalent factor equivalent fuel consumption minimization energy management strategy (A-ECMS) considering passenger load is proposed. First, the powertrain system of the PHEB is modeled, and the accuracy of the model is verified in a simulation environment. Then, the reference SOC descent trajectory of the battery is obtained using a dynamic programming (DP) algorithm, the recursive least squares (RLS) method is employed to identify the passenger load, and the influence of different loads on the state of charge (SOC) trajectory under a single equivalent factor is analyzed. Finally, a genetic algorithm (GA) is used to establish the correspondence between passenger load, bus station, and equivalent factor, enabling the actual SOC to follow the reference SOC descent trajectory, thereby achieving optimal energy distribution. Simulation results demonstrate that the A-ECMS reduces fuel consumption of the PHEB per 100 km by 2.59% and 10.10% compared to the ECMS and rule-based EMS, respectively, validating the effectiveness of the proposed strategy.

Construction and Application of Intelligent Optimization Model of Urban Resource Management for Sustainable Development

Abstract In this paper, we first digitally design the urban management resource base and then construct a dynamic bargaining resource allocation model based on super-marginal analysis with corner point equilibrium and dynamic bargaining. In the context of sustainable development, an intelligent optimization model is used to analyze the problem of water resource allocation and optimize urban traffic infrastructure paths in order to achieve carbon reduction targets. Finally, six recommendations are made for optimizing and managing urban resources in the context of sustainable development. The results of the prioritization coefficients of each subarea are 0.186, 0.164, 0.153, 0.158, 0.153, 0.0769, and 0.111, respectively, and the results of the allocation of the optimal solution for the social objective, the optimal solution for the economic benefit, the optimal solution for the ecological benefit, and the optimal solution for the comprehensive benefit are very close to each other. In addition, the rates of water shortage for agricultural, industrial, and other uses. are 3.29%, 4.85%, 3.94%, 2.92%, and 3.87%, respectively. The variation range of the average passenger load factor and departure frequency under the carbon reduction target is between ±40%, the average vehicle area varies in the range of ±20%, and the variation range of the energy consumption factor and CO2 emission factor is -40%-0%. The intelligent optimization model for urban resource management proposed in this paper has practical significance for urban water resource planning and transportation structure optimization.

Carbon Emission Intensity and Its Abatement Choices: A Case of China Eastern

Air transportation, which is a derived demand, is booming following the rapid development of the world economy, and carbon emissions from the air transportation industry, which takes fossil fuels as its main energy source, have been increasing. Therefore, with global warming attracting considerable attention, the issue of how to reduce carbon emissions from air transportation has become a hot issue. We take China Eastern Airlines Corporation Limited (China Eastern) as an example to analyze the main factors influencing airlines’ carbon emissions, specifically around the impact of airline internal operating indicators, such as available seat kilometers (ASK), passenger load factor (PLF), fuel consumption per unit passenger kilometer, the average age of operated aircraft, on-time performance (OTP), etc. This paper uses a correlation analysis, panel regression analysis, and other ways to explore the influence mechanism of the above factors on carbon emission intensity. The conclusions for China Eastern are the following: first, PLF has a significant negative relationship with carbon emission intensity; second, fuel consumption per passenger kilometer has a significant negative relationship with carbon emission intensity. Third, OTP has a significant positive relationship with carbon emission intensity. Fourth, fleet size has a significant positive relationship with carbon emission intensity. Finally, we propose several targeted carbon abatement measures for China Eastern, such as improving PLF and OTP, reducing fuel consumption per unit passenger kilometer, speeding up fleet renewal, etc.

Optimization of cabin seating arrangement strategies based on the Wells-Riley risk theory.

Civil aviation transport is an important source of global respiratory disease spread due to the closely-spaced environment. In order to reduce the probability of infection of passengers, an improved Wells-Riley model for cabin passenger risk assessment have been given in this work, the cabin ventilation and passenger nose and mouth orientation were considered. The model's effectiveness has been verified with published data. Finally, how the load factor and use of an empty seat scheme are associated with the number of infected people was assessed. The results demonstrated that the number of infected people positively correlates with the passenger load factor, and the most suitable load factor can be determined by controlling the final number of infected people with the condition of the epidemic situation in the departure city. Additionally, infection risk was found to be lower among passengers in window seats than in those in aisle seats and middle seats, and keeping empty seats in the middle or aisle could reduce the cabin average probability of infection by up to 37.47%. Using the model developed here, airlines can determine the optimal load factor threshold and seating arrangement strategy to improve economic benefits and reduce the probability of passenger infection.

An Empirical Research on The Factors Affecting Profitability in Air Transportation

This study aims to analyse the impact of traditional airline companies' internal and external environmental factors on profitability. In total, 17 airlines operating in different regions were included in the study. Passenger load factor, cargo ton-km and the number of destinations were chosen as internal factors affecting the profitability of airlines. GDP, oil prices and exchange rate figures were external environmental factors affecting profitability. Panel ARDL analysis method was used in the study. In the model of the study, all variables were analysed together without division. All selected variables have been observed to affect airline profitability, and the effect of external environmental factors on profitability is more significant.

Vehicle Dispatch and Route Optimization Algorithm for Demand-Responsive Transit

Giving priority to the development of public transit is an important way to achieve efficient, convenient, safe, comfortable, economic, reliable, green and low-carbon sustainable development. In view of the highly dispersed and regular passenger flow, demand responsive transit is an important complementary means for traditional public transport to improve passenger satisfaction. However, high operating costs and low load factor will have a bad impact on the operation of public transport and reduce passenger satisfaction. In this work, firstly, by analyzing the demand frequency of historical travel stations, the stations with high demand are extracted by time periods as high probability travel points; On this basis, a dynamic vehicle dispatching optimization model is established, and the static vehicle dispatching is carried out with the goal of minimizing the running mileage of the bus system; Finally, based on the initial static route and the later real-time travel demand, the accurate dynamic planning algorithm is used to optimize the dynamic route with the goal of minimizing the change of the system mileage, so as to achieve timely response to the demand. The results show that the two-phase scheduling optimization model based on the station extraction strategy can provide a reasonable real-time vehicle scheduling and route optimization scheme, improve the utilization rate of vehicles and the passenger load factor, and provide a theoretical basis and application guidance for actual vehicle scheduling.

Forecasting the recovery period of air passenger transportation by using vector error correction model

AbstractThe COVID‐19 pandemic has had a significantly negative impact on all transportation modules, especially air passengers. The authors aimed to forecast the air passenger load factor using time series modelling for the affecting variables. After providing general information about this pandemic, the forecasting results regarding getting back into the recovery period were presented by time series modelling. The last five years (2016–2020) and the first eight months of 2021 were examined with the following variables: available seat kilometre, revenue passenger kilometre, passenger load factor, gross domestic product, and domestic and international passenger numbers. The forecast results reveal that the recovery period started in June of 2021 and continues with a robust growth trend until September 2021 due to the vaccination process and the starting of the summer season. This trend changed between September to November 2021 slightly negative, from November 2021 to January 2022 slightly positive, and from January 2022 to March 2022 mildly negative. Correspondingly, passenger load factor (PLF) is affected by itself and domestic transportation in the short‐term period. This effect seems short‐term in domestic and international transport. This research reveals that minimising the economic damage by benefiting from the increasing trend of air passenger numbers increases the recovery period.

INFLIGHT SERVICE WASTE MANAGEMENT DURING THE COVID-19 IN INDONESIA

Various business sectors, including the aviation industry, faced significant challenges during the COVID-19 pandemic. Globally, there was a decline of 60-80% in passenger load factor. Adaptation is required to reduce the cost of inflight service and the waste produced. The study was conducted through field observation and interview. At the time of the study, no other research on the specific topic of the impact of COVID-19 on managing inflight service wastes could be found. The study highlights the measures taken by airlines and airport operators to comply with the regulations, and more importantly to reassure the public that it was safe to travel by air and that the waste produced by the air transport industry does not aggravate the pandemic. The results of this study indicated that airlines and airport operators had made preventive efforts in reducing inflight service waste, improving aircraft cleanliness to protect passenger health. The initiatives were aimed at preventing the transmission of COVID-19. The measures taken included changing the packaging of food and beverages, using the prepacked meal method and adopting more hygienic method in processing raw materials. Initiatives included providing workers with Personal Protective Equipment (PPE) when handling inflight service wastes.

Evaluating the Quality of Service of Bus Performance in Johor Bahru

The increase in living standard would also be a major factor for rapid urban development, which is caused by the increase in the daily traffic volume. Therefore, traffic congestion can occur daily, especially during peak hours in the morning and late afternoon to cover the huge number of people movement. Moreover, the quality of bus services should be assessed on operational aspects provided by urban operators. Therefore, this paper is to determine the quality of service (QOS) of bus performance in Johor Bahru, Johor. The study was conducted in April 2019. Service quality data were taken at Terminal JB Sentral, Johor Bahru. The Transit Capacity and Quality of Service Manual (TCRPM) was adopted as the specific guidelines and key indicators to determine and analyse the QOS of bus performance in the selected area. The study focused on four specific areas, such as service hour, passenger load factor, on-time performance and service frequency. The study concluded that the passenger load factor was classified as QOS of Class B since passengers could still choose their seats during the journey. On the other hand, on-time performance was classified as QOS of Class E, as most passengers made one round trip per weekday with a transfer experience of not-on-time vehicles every day. The overall QOS for bus services in Johor Bharu was classified as QOS of Class D, which was considered as moderate because several issues on QOS should be addressed and rectified by stakeholders. Some improvement on these three attributes should be made to increase the QOS. The study outcome should be used as an indicator for operators to measure their bus services. Since Johor Bahru is a major city in Malaysia, authorities and the government can use the outcome as inputs to measure the effectiveness of public transportation in urban areas.

Performance of Bus Services in Urban Area: A Case Study in Penang, Malaysia

Since the escalated industrialisation and urbanisation process began traffic congestion has been a serious problem in many Malaysian cities. One of the solutions for the traffic congestion is by promoting public transport. Public transport is needed to manage the transport in cities. In 2007, a corporate body owned by the Malaysian Government named Prasarana Malaysia, introduced the Rapid bus service in Penang. Currently, Rapid bus is the main public transport operator in Penang. However, the bus service had some setbacks and passengers had publicly voiced their dissatisfaction. Therefore, to encourage more people in using the public transport, a better public transport system should be provided and improved occasionally. Previous comprehensive studies were inadequate, and thus a detailed analysis of the bus service performance in Penang is needed. The Transit Capacity and Quality of Service Manual (TCQSM) was chosen for guidelines. Based on reviews from journals and papers three (3) objectives which focused on service frequency, on time performance and passenger load factor were chosen for the study. The study was conducted to evaluate the bus service performance in Penang. The study results obtained the quality of service (QOS) of D for the Rapid bus service performance in Penang, which was regarded as satisfactory. This showed that buses in Penang needed to be greatly improved to change the passenger’s perceptions.

Network structure revelation and airport role evaluation under three different COVID-19 pandemic periods: Evidence from a Chinese airline

The continuous spread of coronavirus disease 2019 (COVID-19) has had a substantial impact on China's domestic airline networks. It is important for airlines to identify key airports and airport roles in future network design. In this paper, a k-core algorithm is used to decompose the network layers during different periods of COVID-19 to investigate the network structure and the airport role change. By considering both airport degree and route traffic, network characteristics are analyzed, and the key airports are determined based on network evaluation. The results show that the airline network is robust due to its mixed hub-and-spoke network structure, which is basically dominated by direct flights between airports. However, different operation patterns should be implemented based on airport roles. It is not advisable for airlines to pursue network connectivity at the cost of a low passenger load factor.

The Airline Passenger Load Factor Prediction with Machine Learning - Linear Regression Method and Modeling with Fractional Calculus and Deep Assessment Methodology

The Airline Passenger Load Factor Prediction with Machine Learning - Linear Regression Method and Modeling with Fractional Calculus and Deep Assessment Methodology

Forecasting Air Travel Demand for Selected Destinations Using Machine Learning Methods

Over the past decades, air transportation has expanded and big data for transportation era has emerged. Accurate travel demand information is an important issue for the transportation systems, especially for airline industry. So, “optimal seat capacity problem between origin and destination pairs” which is related to the load factor must be solved. In this study, a method for determining optimal seat capacity that can supply the highest load factor for the flight operation between any two countries has been introduced. The machine learning methods of Artificial Neural Network (ANN), Linear Regression (LR), Gradient Boosting (GB), and Random Forest (RF) have been applied and a software has been developed to solve the problem. The data set generated from The World Bank Database, which consists of thousands of features for all countries, has been used and a case study has been done for the period of 2014-2019 with Turkish Airlines. To the best of our knowledge, this is the first time that 1983 features have been used to forecast air travel demand in the literature within a model that covers all countries while previous studies cover only a few countries using far fewer features. Another valuable point of this study is the usage of the last regular data about the air transportation before COVID-19 pandemic. In other words, since many airline companies have experienced a decline in the air travel operation in 2020 due to COVID-19 pandemic, this study covers the most recent period (2014-2019) when flight operation performed on a regular basis. As a result, it has been observed that the developed model has forecasted the passenger load factor by an average error rate of 6.741% with GB, 6.763% with RF, 8.161% with ANN, and 9.619 % with LR.

Prediction and Analysis of Train Passenger Load Factor of High-Speed Railway Based on LightGBM Algorithm

In order to improve the prediction accuracy of train passenger load factor of high-speed railway and meet the demand of different levels of passenger load factor prediction and analysis, the influence factor of the train passenger load factor is analyzed in depth. Taking into account the weather factor, train attribute, and passenger flow time sequence, this paper proposed a forecasting method of train passenger load factor of high-speed railway based on LightGBM algorithm of machine learning. Considering the difference of the influence factor of the passenger load factor of a single train and group trains, a single train passenger load factor prediction model based on the weather factor and passenger flow time sequence and a group of trains’ passenger load factor prediction model based on the weather factor, the train attribute, and passenger flow time sequence factor were constructed, respectively. Taking the train passenger load factor data of high-speed railway in a certain area as an example, the feasibility and effectiveness of the proposed method were verified and compared. It is verified that LightGBM algorithm of machine learning proposed in this paper has higher prediction accuracy than the traditional models, and its scientific and accurate prediction can provide an important reference for the calculation of passenger ticket revenue, operation benefit analysis, etc.

Evaluating the quality of services for bus performance in Alor Setars

Traffic congestion is one of the issues raised as the development and urbanization moving forward. Bus services still considered as an public transport option to move from one location to another. Since 1957, bus services have been a primary selection not just a big cities like Kuala Lumpur and Georgetown as well as small town in like Alor Setar, Kota Bahru and others. As the demand increase year by year, the quality of service is expected to be improved as well. Recently, public transport in small cities in Malaysia also faced a huge competition with E-hailing services such as Grab and MyCar. Therefore, these paper is to determine the service quality of bus performance in Alor Setar, Kedah. These studies were conducted in April 2019. Service quality data have been taken at Terminal Shahab Perdana, Alor Setar. Transit Capacity and Quality of Service Manual (TCRPM) has been stated as a specific guidelines and key indicators to determine the quality service of bus performance in designated area. There were four specific areas would be focused in these studies such as service frequency, hours of service, factors of passenger load, on time performance. Based on the results, it shows that only passenger load factor has classified as A quality of service in these studies. The hours of services and on time performance were classified as Class D while the service frequency was classified as Class F. The overall quality of service in Alor Setar, Kedah is classified as Class D which consider as moderate as there is a lot of issues should be addressed. Some improvement on these three attributes should be made to increase the quality of service. Authorities also could use the outcome of these studies to determine and identifies the significant improvements for bus service on these areas.

Analisis Kinerja Pelayanan Angkutan Perintis di Wilayah Kecamatan Liukang Tangaya Kabupaten Pangkajene dan Kepulauan

Analyze Service Performance of Pioneer Transportation in Liukang Tangaya Sub-district Area, Pangkajene and Islands District. The aim of this study was to find out efficiency of the pioneer transportation performance in Liukang Tangaya Sub-district Area and the variables that affect to it, and to formulate the development strategies in the future also.The approach of this study was quantitative. Data collection performed by direct observation. Total load data processed to obtain load factor as benchmark to determine efficiency and continued by analyzing the influence variables to formulate the development strategies by using SWOT analysis. The result showed that the pioneer transportation route R-44 was efficient, where passenger load factor for line Liukang Tangaya – Maccini Baji more than 100% and cargo below 6%, with realized frequency also as much 89%. The affecting variables are the amount of cargo quantity and the amenities of load space. The development strategies that suggested are: (i) Increase the quality of passenger’s service on board as well as when in harbor, (ii) Intensify socialization related to schedule information departure of the ship either by print media or by government web sites to stimulate more cargo quantity, (iii) fleet regenerate with more greater passenger’s capacity and load space equipped with cooler, (iv) increase shipping frequency numbers so that passenger buildup would never happen.

How public transport subsidy policies in China affect the average passenger load factor of a bus line

This study applies inventory theory to illustrate the internal relationship between the average passenger load factor and choice of public transport subsidy policy by the government. Subsidy policies are broadly classified into four types: fixed amount subsidy, passenger volume subsidy, vehicle trip subsidy, and incentive mechanism subsidy. A bus supply model with the objective of minimizing expected loss is formulated with demand considered to be a continuous random variable. We then analyse, using numerical examples, how the four subsidy policies affect the model-related parameters and the average passenger load factor. Results show that, in terms of reducing the average passenger load factor, the fixed-amount subsidy has no effect while the passenger volume subsidy and vehicle trip subsidy have limited effects, although the latter is more effective than the former. Further, the incentive mechanism subsidy requires an appropriate unit penalty value to reach the appropriate average passenger load factor. A combination of the vehicle trip subsidy and an appropriate incentive mechanism subsidy is the most effective method to improve the average passenger load factor. However, the effectiveness is constrained by the bus supply capacity.

Evaluation of paratransit performance as public transport in Medan City

Although bus comfort is a crucial indicator of service quality, existing studies tend to focus on passenger load factor and headway. This study examines the performance of paratransit in Medan city by using those criteria. The analysis is conducted using survey passengers onboard expressed as a percent of available seats and number of fleets required to operate a transport route for a given interval. The result showed there is significant gap in paratransit load factor from government regulation, and average headways of paratransit still fulfilling the level of services except for 2 operators which is National and Mars. Government intervention is needed to increase the service’s reliability of public transport.

Analisis Tarif Angkutan Umum Berdasarkan Biaya Operasi Kendaraan

The aim of this study is to analyze the Vehicle Operational Cost (VOC) and tariff based on the calculation of VOC and compare with the prevailing tariff in Blang Pidie-Banda Aceh route. Primary data was carried out by surveys, among others, physically survey of the vehicles, number of vehicles and passengers, and investigation survey. Secondary data was obtained from the relevant government institutions. The results of the analysis showed that the average passenger load factor of the inter-city transportation route of Blang Pidie-Banda is 56.25%. The average tariff set by the government is Rp. 106,500/passenger, the average tariff calculated by VOC for Blang Pidie-Banda Aceh route is Rp. 114,014/passenger, while the average rate applied in the field is Rp. 125,000/ passenger. The calculation of Cost of Production (COP) is Rp. 103,649/passenger-km. While the ability to pay (ATP) of the public transport services users is Rp. 208,333. Tariffs based on Vehicle Operating Cost (VOC) are smaller than the prevailing rates in the field and the rates applicable in the field are also higher than the rates set by the local municipality.