Optimization Model of Transit Route Fleet Size Considering Multi Vehicle Type

This paper proposes a bus line capacity optimization design model considering the scale of multiple vehicles, which is achieved by minimizing system operating costs and user costs. The proposed model takes into account the difference of passenger demand in different periods, and can get the optimal headway and delivery and reserve plan. In order to prove that the method can effectively minimize the cost, we solved a numerical example and compared the cost of the method in multi-transit model planning. Furthermore, the optimization results show that the total costs (TC) were reduced by 14.48%. Among them, the user costs (UC) decreased by 30.38% and the operator costs (OC) increased by 4.18%. Sensitivity analyses are presented to verify the validity of the model. The analysis results show that multi size bus optimization can reduce the total cost, especially the user cost in a certain cost weight interval. Besides this, the cost weight which reflects the passenger volume and waiting time value, optional bus size and cross-section passenger volume all affect vehicle scheme and system cost.

THE INFLUENCE OF LAND USE ACTIVITIES TOWARDS MASS RAPID TRANSIT (MRT) FEEDER BUS SERVICE RIDERSHIP

The Mass Rapid Transit (MRT) feeder bus service is a complementary public transport service provided to encourage ridership of MRT rail services in Malaysia. In brief, this feeder bus service plays a role in connecting people to and from MRT stations. The objective of this study is to determine the passenger volume generated at each MRT feeder bus stop location in the study area, and relate it to surrounding land use activities. Using the rule of thumb in public transportation systems, 200 m and 400 m radial buffers were identified as catchment areas of the bus stops. The key finding from this study is the relationship between volume of passenger and land use activities. This study concludes that land use activities influence MRT ridership, and that the presence of shelters or waiting poles is important to encourage ingress or egress.

Prediction of passenger train using fuzzy time series and percentage change methods

In the subject of railway operation, predicting railway passenger volume has always been a hot topic. Accurately forecasting railway passenger volume is the foundation for railway transportation companies to optimize transit efficiency and revenue. The goal of this research is to use a combination of the fuzzy time series approach based on the rate of change algorithm and the Holt double exponential smoothing method to forecast the number of train passengers. In contrast to prior investigations, we focus primarily on determining the next time period in this research. The fuzzy time series is employed as the forecasting basis, the rate of change is used to build the set of universes, and the Holt's double exponential smoothing method is utilized to forecast the following period in this case study. The number of railway passengers predicted for January 2020 is 38199, with a tiny average forecasting error rate of 0.89 percent and a mean square error of 131325. It can also help rail firms identify future passenger needs, which can be used to decide whether to expand train cars or run new trains, as well as how to distribute tickets.

Train Dwell Time Efficiency Evaluation with Data Envelopment Analysis: Case Study of London Underground Victoria Line

Train dwell time is a complicated component and depends on many factors. One of the dominant factors is passenger volume. This study used actual train movement data and passenger demand data from London Underground, UK, to estimate the number of passengers and train dwell times at each station, and then evaluated train dwell times from a different perspective. Considering the various characteristics of stations, it is complicated to evaluate dwell time. Therefore, data envelopment analysis (DEA) was introduced to evaluate the dwell time at each station in relation to passenger volume at that station. The study investigated whether the dwell time spent at stations is efficient when considering the number of passengers that the stations can serve. The results showed that, in low-passenger-volume stations, the dwell time efficiency score is low and increases relative to the increase in passenger volume. For high-passenger-volume stations, interactions between passengers are more relevant and have a strong influence on dwell time. Passenger movement direction is a key factor to classify stations. This research proposes that stations should be classified according to their characteristics, and points out the challenge at any station with the same characteristics as Victoria station which has high passenger volume with bi-directional flow, and where trains arriving are crowded. This characteristic would result in high interactions between passengers, thus making a long dwell time. The station has to handle high passenger volume and also has to keep the dwell time within the threshold.

Sustainable Technology on Aircraft Design: A Review

Next-generation air transportation is a key to influence the environment, safety, and the economy. Several programs strive to create emerging innovation towards sustainability, system integrity, and alternative fuels to guarantee a reduction of its environmental effect as greenhouse gas. Nowadays, the aerospace industry is looking forward to aviation sustainable developments across the globe. Few initiatives through a novel configuration of aircraft is established like Blended Wing Body, Flying V aircraft, Box wing Aircraft, and Double bubble Aircraft to enhance the cargo and passenger volume occupancy and cut-off the fuel burn percent. With the use of disruptive technologies, researchers are progressing the revolutionary airframe for transportation. A systematic overview and comprehensive survey of passenger-based aircraft are investigated. The objective study is to examine fuel burn and its impact on the environment by types of aircraft. In-depth literature review studies on four pillar strategies used to design an efficient airplane. In addition, this paper also serves on advancement in evolutionary technologies used in jet transport aircraft. Reflecting the benefits and challenges of different aircraft designs technologies were also highlighted. This paper highlights the future implications and managerial insights for future aircraft designers.

Changes in Passengers’ Travel Behavior Due to COVID-19

The COVID-19 outbreak in 2020 has changed the way people travel due to its highly contagious nature. In this study, changes in the travel behavior of passengers due to COVID-19 in the first half of 2020 were examined. To determine whether COVID-19 has affected the use of transportation by passengers, paired t-tests were conducted between the passenger volume of private vehicles in Seoul prior to and after the pandemic. Additionally, the passenger occupancy rate of different modes of transportation during the similar time periods were compared and analyzed to identify the changes in monthly usage rate for each mode. In the case of private vehicles and public bicycles, the usage rates have recovered or increased when compared to those of before the pandemic. Conversely, bus and rail passenger service rates have decreased from the previous year before the pandemic. Furthermore, it is found that existing bus and rail users have switched to the private auto mode due to COVID-19. Based on the results, traffic patterns of travelers after the outbreak and implications responding to the pandemic are discussed.

A Two-Phase Approach for Predicting Highway Passenger Volume

With the continuous process of urbanization, regional integration has become an inevitable trend of future social development. Accurate prediction of passenger volume is an essential prerequisite for understanding the extent of regional integration, which is one of the most fundamental elements for the enhancement of intercity transportation systems. This study proposes a two-phase approach in an effort to predict highway passenger volume. The datasets subsume highway passenger volume and impact factors of urban attributes. In Phase I, correlation analysis is conducted to remove highly correlated impact factors, and a random forest algorithm is employed to extract significant impact factors based on the degree of impact on highway passenger volume. In Phase II, a deep feedforward neural network is developed to predict highway passenger volume, which proved to be more accurate than both the support vector machine and multiple regression methods. The findings can provide useful information for guiding highway planning and optimizing the allocation of transportation resources.

RESEARCH ON THE LEVEL OF URBAN ECONOMIC DEVELOPMENT IN SICHUAN PROVINCE

This paper selects 21 cities and prefectures of Sichuan Province as the research object, adopts 12 comprehensive indicators, establishes a linear model through correlation analysis, carries out regression analysis to modify the model, and uses factor analysis and cluster analysis to study the level of urban economic development. The results show that the GDP of all regions in Sichuan Province has a strong correlation with the three indicators of total retail sales of social consumer goods, passenger volume, and urbanization rate, and plays a positive role in promoting the economic development of all cities in Sichuan Province. Chengdu ranks the highest in the comprehensive ranking of urban economic development level in Sichuan Province.