Bus Passengers Research Articles

Understanding bus passengers vibrational discomfort based on graphical modelling: a field experiment

Understanding bus passengers vibrational discomfort based on graphical modelling: a field experiment

Estimating Bus Passenger Mobility with Wi-Fi Data and Clustering

Thanks to Wi-Fi technology, it is possible to gather passive mobility data over a long time and to analyze travel behaviors variability. However, the main challenge is to identify relevant data, in a way that is efficient whatever the chosen period of network. Our research evaluates the replicability of a method, based on a partitioning algorithm, that allows to identify signals emitted by passengers from those emitted by non-passengers automatically. The findings show that this algorithm is easily replicable and useful to study individual mobility from passive data. It is hence a good opportunity for understanding travel demand.

Strategies and Practices of Intelligent Imputation in Data Mining Based on Contact Number Evaluation

Abstract This paper proposes the general architecture of a multi-scale classification system based on the intelligent imputation method of multi-scale classification. SVM is used to transform the storage structure model of the object, obtain the trained support vector set with corresponding weights, measure the similarity between two data points based on the Hausdorff distance, realize the construction of a similarity matrix, adopt the idea of mean value, blur the data information, and improve the mechanism of on-scale imputation. The bicubic difference method is used as the theoretical basis of scale-down extrapolation, and the scale-down extrapolation algorithm DAMSC is established. Based on the quaternionic linkage number, the dataset data are preprocessed, and the data eigenvalue weights are calculated at the same time. The multi-scale classification validity index evaluates the model’s accuracy in classification and its performance in both upward and downward scale extrapolation. When the categorized data is 7, the MSCVI metric of the model attains a peak of 0.92254 in the segmentation dataset run results, which is more advantageous than other metrics. In the regression test of the model’s imputation results, the correlation coefficient of bus passengers is 0.99, the adjusted R-square is 0.97043, and the coefficient of the regression equation is 1.042, and the model in this paper is valid and reliable for the imputation of passenger drop-off points.

Оцінка економічної ефективності оптимізації трансмісії пасажирських автобусів типу Setra S 417

The creation and implementation of technologies aimed at increasing fuel efficiency is becoming the focus of attention of car manufacturers. This may involve improving engines, using less dense materials to build cars, developing efficient transmissions, and implementing alternative energy sources. Changing the gear ratio of the main gear affects the force and speed of rotation of the car's wheels. When reducing the gear ratio (using a higher gear), the torque increases, but the speed of rotation of the wheels, which is used to overcome large obstacles or climb, decreases. Conversely, increasing the gear ratio (using a lower gear) decreases torque but increases wheel speed, resulting in higher speeds on flat surfaces. The effect of changing the gear ratio on fuel performance can be a bit complex. Basically, using a lower gear ratio (higher gear) can help save fuel at high speeds or when driving on level roads, because the engine can run more efficiently at lower rpm. However, in mountain conditions or when driving at low speeds, when more torque is needed, using a higher gear can result in more fuel consumption. The article proposes the reconstruction of the transmission, by replacing the gears of the main transmission, in order to change the gear ratio of the transmission of the Setra S 417 type passenger bus. The vehicle under study is operated at the "TRAVELBUS TERNOPIL" transport enterprise The traction-speed calculation of a bus with a unified transmission was carried out, the fuel-economical characteristic was calculated, and a reduction in the average consumption of fuel and lubricants was established. The effectiveness of the conducted unification was tested in different directions, and it was established that the greatest efficiency was achieved on the expressway. Such unification is not advisable on routes with mountainous terrain.

Integration planning between components of Type B bus station Sukorejo

Kendal Regency has problems with passenger bus station services in the transportation sector. Integrating components in Sukorejo Type B Bus Station includes crossing circulation patterns between people and vehicles. The crossing can cause conflicts that endanger the safety of service users. This study aimed to handle circulation conflicts through the integration of the components applied in the Sukorejo Type B Bus Station can be optimal. This study used a methodological approach such as quantitative, explanation, and planning, referring to the field results and observational surveys. This research used 135 respondents of inter-city transportation within the province (AKDP) and 147 respondents of rural transportation (ANGDES). The results showed the integration performance between the components of the Sukorejo Type B Bus Station through the Normalized Score, which got a value of - 100 with good information and indicated by the total circulation distance needed to reach each bus station component in 452 meters for 342 seconds. In Bus Station Type B Sukorejo, circulation crossings caused conflict at as many as 10 points due to the pedestrian crossing activities in private vehicle parking, arrival areas, waiting areas, and public transport departures. The research value of PV2 < 108 meant the need for pedestrian facilities indicated that it was not necessary to handle circulation crossings with pedestrian facilities. It was just sufficient to provide pedestrian warning signs to cross, so that vehicle drivers could be careful in crossing each conflict point.

МЕТОДЫ ПОВЫШЕНИЯ НАДЕЖНОСТИ ГОРОДСКИХ АВТОБУСОВ

The article is devoted to the renewal of the fleet of city passenger buses in the Russian regions within the framework of the adopted state strategies and programs. It considers the problems of national and economic importance associated with improving the reliability of buses and safety of their operation. The purpose of writing the paper is to publish proposals to improve the reliability of urban route buses. The scientific novelty consists in the formation of the list of requirements to the newly created machines on the basis of the analysis of the experimental operation of the city buses in St. Peters-burg, supplied within the framework of the implementation of the transport reform. The methods of buses reliability improvement at the stage of their design by means of application of traditional mathematical apparatus are proposed.

Analisis Fluktuasi Jumlah dan Karakteristik Penumpang Bus Trans Jogja Kondisi Sebelum, Selama, dan Setelah Covid-19

Trans Jogja Urban Public Transportation is a form of reform of the subsidized road transport system in the Special Region of Yogyakarta, which has served the Yogyakarta Urban Area since 2008. Trans Jogja Buses have served 25 sub-districts, with a fleet of 128 buses subsidized by the DIY Regional Government and 44 buses subsidized by the Ministry of Transportation of the Republic of Indonesia. When the COVID-19 pandemic hit in 2020-2021, there was a decrease in people's movements, resulting in a decrease in Trans Jogja Bus passengers. This study aims to analyze the fluctuations of passengers and compare the characteristics of the Trans Jogja Bus passengers in conditions before COVID-19 (in 2019), during COVID-19 (in 2020 and 2021), and after COVID-19 (in 2022). The analysis results show that based on the monthly average, the number of Trans Jogja Bus passengers in conditions during COVID-19 decreased by 54%. After COVID-19, it increased by 12% compared to during COVID-19. The monthly average number of passengers After COVID-19 is not as regular as in conditions before COVID-19, with a disparity of 50%t. Based on the characteristics of passengers during COVID-19, the proportion of missing passengers is by the professional aspect, namely students/students and civil servants/national soldiers/police. Regarding travel intentions, a relatively large proportion of the missing were college, school, and tourism travel, each decreasing by 7%.

FEASIBILITY OF DEVELOPMENT OF AUTOMOBILE PASSENGER TRANSPORT IN THE NORTHERN REGIONS OF OUR COUNTRY

Automobile passenger transport is an integral part of the country’s unified transport system and ensures its territorial integrity and accessibility of its regions. Today, in our country, much attention is paid to the development of public transport, which can improve passenger traffic and partially reduce the movement of personal cars in the winter in the northern regions of our country. However, the solution to this problem requires a reliable, comfortable off-road bus fleet. And in the northern regions, this problem remains constantly acute due to the insufficient number of vehicles for transporting passengers, especially in winter.
 Purpose – To study the need for the development of road passenger transport in the northern regions of the Russian Federation.
 Method or methodology of the work: the article used a statistical method of analysis.
 Results: the feasibility of using automobile passenger transport in the northern regions of Russia was investigated, a possible design of a passenger bus was proposed depending on the climatic features of the northern regions.
 The scope of the results: conducting research aimed at creating new technologies in the development of road passenger transport, depending on the geographical location and climatic features of the country’s regions.

Stochastic-priority-integrated signal coordination considering connected bus operation uncertainties

Multimodal arterial signal coordination for buses and passenger vehicles can improve arterial travel smoothness and efficiency. However, uncertainty in bus operations requires signal priority at intersections, which impacts coordination and increases stop times for other traffic types. Therefore, this study proposes a stochastic priority-integrated signal coordination (SPIC) method. It includes an offline stochastic programme to determine the arterial signal coordination, i.e. cycle length and offsets, considering the stochastic signal priority, and an online mixed-integer nonlinear programme to determine the signal priority together with the bus arrival and departure times at and from stops and intersections in a connected vehicle environment. A scenario-based heuristic algorithm is proposed to solve the SPIC efficiently. Numerical studies have validated that SPIC can improve the efficiency of buses and passenger vehicles. Sensitivity analyses show that the SPIC effectively reduces delays with fluctuations in the bus travel time, dwell time, and passenger vehicle demands.

Optimizing Transit Operations and Passenger Experience: A Simulation-based Study of Bus Interarrival and Passenger Load Scenarios at a Major Transfer Point

This study employs simulation-based analysis of passenger flow and bus operations at the Adam Malik transfer point within the TransJakarta BRT system. The findings from the analysis of the current system indicate that the average number of total passenger exits in corridors 13, 13B, 13C, and L13E were 618, 509, 1143, and 790, respectively. Additionally, the average time spent by passengers within the system for each corridor was 4.48 minutes, 6.12 minutes, 5.94 minutes, and 5.46 minutes, respectively. Through the development of 15 scenarios, the study demonstrates the impact of adjusting passenger boarding procedures and reducing interarrival time on waiting times and passenger processing efficiency, particularly during peak hours. The results emphasize the substantial influence of these variables on waiting times, total exits, and system duration for passengers and buses.

A two-stage approach to siting electric bus charging stations considering future-current demand

With the global acceleration of the carbon-neutral process and the widespread adoption of electric buses in various countries, the placement of charging stations plays a crucial role in promoting low-carbon development in public transportation systems. This paper proposes a two-stage approach for siting electric bus charging stations considering future-present needs. Initially, perspectives on future and current needs, a community discovery model is constructed using bus space-time swipe card data to identify the municipal bus travel link network. This model considers the OD distribution of bus passenger flow, which is essential for determining the line network and capacity layout. Additionally, a bus first and last station hotspot identification-Voronoi diagram model is established based on the service area partition of bus charging stations, incorporating the weight of charging demand. The model assesses the aggregation of charging demand in each service area using demand aggregation and spatial aggregation indicators. It utilizes the current bus charging requirements aggregation pattern to determine the siting of bus charging stations in the sub-regions, resulting in a data-driven two-stage method for siting electric bus charging stations considering future and current demand. The city is divided into 11 bus charging station subzones using the community discovery model, and sites are selected within each subzone. The results indicate that the demand aggregation degree has increased to some extent in 10 service areas compared to the initial sub-district and an overall increase of 22.79% for the entire city, from 0.487 to 0.598. Among them, 8 service areas have a demand aggregation degree greater than 0.5, indicating that charging demand in most sub-districts is concentrated in high-value aggregation areas. The spatial aggregation degree of all service areas is less than 1, with a decrease in the spatial aggregation degree of 7 service areas and an overall decrease of 11.47% for the entire city, from 0.680 to 0.602. Most service areas experience a decrease in spatial aggregation degree while the demand aggregation degree increases, optimizing the structure of the service areas and reducing the time cost of charging the buses. The model demonstrates good applicability to charging stations and offers an effective approach to siting them.

Modelling bus bunching along a common line corridor considering passenger arrival time and transfer choice under stochastic travel time

This study examines bus bunching along a common-line corridor, considering crucial factors underexplored in existing literature, such as stochastic travel times, passenger arrival patterns, and passenger transfer behaviours. We first develop a bus motion model that captures the interaction between bus trajectories and passenger movement. Then we formulate a reliability-based passenger arrival time choice and a transfer choice model to characterise passengers’ behaviours. Afterwards, the bus motion model and the passenger choice models are integrated, and a Method of Successive Averages type iterative algorithm is developed to obtain stable passenger arrival patterns and transfer choices. Numerical experiments are carried out on a hypothetical network followed by a case with real-world data. Our findings demonstrate that a high transfer demand could amplify the propagation of bus bunching across lines along the common-line corridor. Meanwhile, a 50% increase in transfer demand leads to a 24%–30% rise in headway fluctuation. Furthermore, our results suggest that non-uniform passenger accumulation patterns can restore headway regularity as a result of coordinated passenger movement and bus motions, thus alleviating the persistent deterioration in bus bunching.

A Dual-View Approach for Multistation Short-Term Passenger Flow Prediction in Bus Transit Systems

Timely and accurate prediction of bus passenger flow plays a crucial role in uncovering real-time traffic demand, presenting an essential and formidable challenge in the realm of bus scheduling and management. The extensive application of deep learning methods in transit passenger flow prediction can be attributed to their exceptional ability to effectively capture spatiotemporal features, resulting in superior performance. However, prevailing deep learning models in transit passenger flow prediction tend to ignore the data enhancement. Additionally, the predominant focus on a single station in the prediction task presents challenges in effectively capturing the spatiotemporal features of the entire network. A model named TSD-ST is proposed to better accomplish the task of predicting short-term transit passenger flow at multistation. The TSD-ST model leverages time series decomposition for data enhancement. Simultaneously, in addition to considering the adjacency graph, the similarity of all the stations of the entire transit network is also considered and uses multigraph convolution and graph fusion modules. This approach enables the TSD-ST model to effectively capture spatiotemporal dependencies. Experiments based on real-world bus transit datasets confirm that the TSD-ST model shows better performance in prediction tasks at 30-min, 60-min, and 90-min time scales, with an average improvement of 21.87%. The effectiveness of each component has been verified through ablation experiments.

Sustainable development of passenger transport in Poland in the context of young passengers’ preference survey

The issue of reducing the adverse impact of transport on the environment has been reflected in key European transport documents. Their content clearly indicates that rail transport is more “environmentally friendly” than road transport. An increase in the number of rail passengers and, at the same time, a drop in the number of road transport passengers is consistent with the concept of sustainable development. The purpose of the article is to analyse the preferences of rail and bus passengers and use research results to enhance sustainable development. In order to achieve this aim, the method of critical analysis of available secondary research results and the survey method were adopted, with the use of a questionnaire in primary research. The author’s own research was conducted on a representative sample of 331 young passengers. On the basis of available secondary research results, the price, travel time and modern technology categories as well as elements thereof were selected for analysis. The study results may be used to formulate a strategy for sustainable development of transport, contributing to the reduction of road passenger transport in favour of rail transport.

How to improve public transport usage in a medium-sized city: key factors for a successful bus system

In recent years, the promotion and use of public transport (PT) has become key to overcoming the negative impacts of mobility, such as traffic congestion, high pollution (GHG), and traffic accidents. Improving users’ satisfaction and increasing the attractiveness of buses play an essential role in increasing PT patronage. Whilst most of the literature concentrates on large and complex bus systems, less attention has been paid to European medium-sized cities, the region’s most common urban configuration, where public transport mainly depends on bus services. To this end, a survey campaign was conducted on passengers of urban buses in Oviedo, Spain, a representative medium-sized city. An Exploratory Factor Analysis (EFA) was used to identify key user satisfaction factors. In this case, three factors were the most important: comfort and information, service performance, and integration. That was complemented by the overall satisfaction (OS) with services, which was used for ranking the importance of the factors using an ordinal logistic regression model; comfort and information appear as the most important. These findings can serve bus operators to identify service-related attributes that need more attention or investment to increase users’ satisfaction and to make the service attractive to potential users.

Effect of large bus body reflection on sound barrier efficiency for road traffic noise control: a simulation study

Assessment of road traffic noise (RTN) generally approximates vehicles as point sources, including in the setting of roadside sound barriers (SBs). However, when a large passenger bus passes on a road section with an SB, strong reflected sound waves emerge between the bus body and the SB, reducing the effectiveness of the SB. In this study CadnaA software was used for simulating the sound field distribution formed by such reflections. Because a large bus cannot be approximated as a point source, multi-point noise measurement results of the near-field position of the body of a moving bus were adopted for simulating the actual three-dimensional bus by distributing small-area sources approximately at the near-field different positions near the bus body surface. For a bus moving on a road past an SB, noise distributions were simulated for three scenarios: 1) without an SB, 2) with a smooth reflection-type SB, and 3) with an absorption-type SB. This study presents important insights for establishing RTN SBs.

Factors impacting bus selection: Differences between the middle and later stages of COVID-19

As one of the most important modes of transportation, buses play an essential part in people's journeys. However, less has been known about whether and under what circumstances people will choose to travel by bus during the COVID-19 epidemic. Based on the theory of planned behaviour (TPB), the study examined how the impact of the different stages of COVID-19 (middle stage and later stage), the quality of public transport services and the fear of COVID-19 (FCV-19) are associated with individual choices.An online survey of 404 participants from Anhui Province, China was conducted. We collected data on demography information, together with related TPB constructs (behavioural intentions, self-reported bus use, attitudes, subjective norm, perceived behavioural control, fear of COVID-19 and bus passenger satisfaction). After verifying the scales and the basic TPB model, we established a structural equation model (SEM).Our analysis of the survey data yielded the following results: 1) In the middle stage of the COVID-19 epidemic, fear of COVID-19 was significantly related to the intention to take the bus, and passenger satisfaction was insignificantly related to travel by bus. 2) In the later stage of the COVID-19 epidemic, passenger satisfaction was significantly related to the decision to take the bus, and fear of COVID-19 was significantly related to the intention to travel by bus.These research results not only reveal the internal mechanism of passengers choosing to take the bus but also provide important information for future disaster emergency management. On this basis, some feasible suggestions are made to avoid the decrease of bus ridership and help the public transportation system recover from the crisis.

STRUCTURAL OPTIMIZATION OF TRUCK LADDER CHASSIS USING FINITE ELEMENT METHOD

The research aim is to find out the most suitable cross section truck ladder chassis with the factors of maximum stress and equivalent stress. The vehicle's chassis is an important component, and static loading circumstances can lead to a variety of breakdowns. Unbalanced loading circumstances exist in the design of passenger and truck trucks; the local passenger bus's real carrying capacity for unloading is lower than that of the truck. The passenger truck chassis is designed with maximum stress and maximum deflection as the primary design parameters. But the present study focus is on the stresses developed in the chassis for each type of cross section. For our analysis the material we selected is ASTM 710 Steel. Different models of chassis have been selected with different types of cross sections that are I , C and rectangular (hollow). The solid modelling and Finite Element Analysis has been done in Ansys. In the end the analytical results are compared with the results of software.

Bus-Passenger-Flow Prediction Model Based on WPD, Attention Mechanism, and Bi-LSTM

The prediction of the bus passenger flow is crucial for efficient resource allocation, frequency setting, and route optimization in bus transit systems. However, it remains challenging for a single model to simultaneously capture the time-series data of the bus passenger flow with periodicity, correlation, and nonlinearity. Aiming at the complex volatility possessed by the time-series data of the bus passenger flow, a new hybrid-strategy bus-passenger-flow prediction model based on wavelet packet decomposition, an attention mechanism, and bidirectional long–short-term memory is proposed to improve the accuracy of bus-passenger-flow prediction. The differences between this study and the existing studies are as follows: Firstly, this model combines decomposition strategies and deep learning. Wavelet packet decomposition can decompose the original data into a series of smoother data components, allowing the model to be more adequate in capturing the temporal characteristics of passenger-flow data. And the model can consider the information after the predicted moment via backward computation. In addition, the model is equipped with the ability to focus on important features by incorporating an attention mechanism to minimize the interference of irrelevant information. Bus-passenger-flow prediction experiments are conducted using the Harbin bus-passenger-flow dataset as an example. The experimental results show that the model proposed in this paper can obtain more accurate bus-passenger-flow prediction results than the five baseline models can obtain.

Numerical Analysis of Drag Reduction Using Aerodynamic Designs in a Passenger Bus

Numerical Analysis of Drag Reduction Using Aerodynamic Designs in a Passenger Bus