Bus Passengers Research Articles

Dynamic Modal Analysis of a Passenger Bus: Theoretical and Numerical Studies

The dynamic assessment of a passenger bus is of the highest importance when aiming at high safety standards and low emissions for environmental sustainability. This work studies the dynamic response of a bus considering its modal analysis, for which simple dynamic models were developed for fast determination of the lowest frequencies, mainly arising from the suspension flexibility. In addition, complex natural vibration modes, impossible to determine using simplified models, were calculated via finite element method (FEM) modeling. To study the tire elastic behavior, as the key link between the vehicle and the road, specific deformation models, leading to a stiffness matrix to be combined with that of the vehicle spring suspension at each wheel/axis, were developed. This study aims at proposing a set of mathematical formulations to describe the modal behavior of passenger buses in detail, which could be applicable in any other long vehicle with similar conditions. Two main factors are studied, namely the suspension and the tire deformation effect. An acceptable agreement was verified between the simplified approach and FEM model results for the evaluation of natural frequencies and associated modes.

An Improved STL-LSTM Model for Daily Bus Passenger Flow Prediction during the COVID-19 Pandemic.

The COVID-19 pandemic is a significant public health problem globally, which causes difficulty and trouble for both people’s travel and public transport companies’ management. Improving the accuracy of bus passenger flow prediction during COVID-19 can help these companies make better decisions on operation scheduling and is of great significance to epidemic prevention and early warnings. This research proposes an improved STL-LSTM model (ISTL-LSTM), which combines seasonal-trend decomposition procedure based on locally weighted regression (STL), multiple features, and three long short-term memory (LSTM) neural networks. Specifically, the proposed ISTL-LSTM method consists of four procedures. Firstly, the original time series is decomposed into trend series, seasonality series, and residual series through implementing STL. Then, each sub-series is concatenated with new features. In addition, each fused sub-series is predicted by different LSTM models separately. Lastly, predicting values generated from LSTM models are combined in a final prediction value. In the case study, the prediction of daily bus passenger flow in Beijing during the pandemic is selected as the research object. The results show that the ISTL-LSTM model could perform well and predict at least 15% more accurately compared with single models and a hybrid model. This research fills the gap of bus passenger flow prediction under the influence of the COVID-19 pandemic and provides helpful references for studies on passenger flow prediction.

The Effect of Service Quality and Service Value on Suroboyo Bus Passenger Satisfaction

It is important for the public transit operator to understand the effect of service quality and service value on passenger satisfaction, to maintain passengers loyalty and to attract more passengers. This study analyzed the effect of service quality and service value on Suroboyo Bus passengers satisfaction. Data were collected from a random sample of 300 Suroboyo Bus passenger and was analyzed using Structural Equation Modelling. Results show that service quality has significant positive effects on the service value, and both the service quality and the service value have significant positive effects on the passenger satisfaction. The results as well indicate that service quality only explains up to 4.5% variance of service value, while service quality and service value explains up to 48.8% variance of passenger satisfaction. Additionally, Suroboyo Bus passenger satisfaction more affected by service value, than by service quality.

Analysis of intercity bus public transport safety perception modeling using conjoint

Public transport safety is still an issue that needs to be studied by bureaucrats and researchers. This is because public bus accidents are still quite high. This is because many families, involved in traffic accidents, are shocked by the accident. Therefore, the problem of perception of a safe bus needs to be studied. The purpose of this study was to determine the perception model of a safe public bus. Mathematical modeling based on the parameters that have been studied was selected first. While the second objective was to determine the importance value of the parameters that are an indication of the perception of the safety of intercity bus public transportation. This research is a type of perceptual one where the data is taken from the relevant respondents. The method of data collection was carried out using a questionnaire with respondents from bus company owners, drivers, and passengers in the province of East Java, Indonesia. Respondents were asked to answer questions related to the variables of income, speed, comfort, and safety. The method of conjoint analysis is used. The first stage is the result of modeling the perception of a safe bus. Further analysis is carried out to obtain the importance value of the parameters. The result of this research is a utility model for the perception of a safe bus, which is expressed by the equation U, where the variables include income, speed, comfort, and safety. The highest level of importance is income 33.29 %, followed by the security variable with a weight of 25.39 %. This shows that the income factor is a top priority for drivers and management of bus company owners, while road safety is second only to income. In other words, respondents' perceptions are more concerned with income, while safety is still a non-priority factor.

The Model of the Optimal Number of Public Transport Vehicles in Mixed Traffic Flow Conditions: A Case Study

Bus passenger transport is very important for sustainable urban mobility, and due to the characteristics of the street network, it is usually realized in the conditions of mixed traffic flow. Disturbances and sudden changes of traffic flow parameters occurring in the street network in a mixed traffic flow affect the disruptions in schedule and travel time of all vehicles in the traffic flow, including public transport (PT) vehicles. In order to keep to the planned schedule in the peak hours of PT lines carried out in the conditions of mixed traffic flow, the operators introduce new vehicles or reduce the vehicles’ dwell time at terminuses, which is often impossible to do. The use of a larger number of public transport vehicles increases the fuel consumption, pollutants’ emission, and the operating costs. In this paper, a network optimization model was developed for defining the influence of the change of traffic flow parameters in a mixed traffic flow on travel time of PT vehicles. The model takes into consideration uncertain time unevenness of the change of traffic flow parameters, which enables determining the optimization of travel time and defining the necessary number of public transport vehicles for the purpose of keeping to the planned schedule. In order to develop the transport model, counting and analysis of the characteristics of traffic flow at 61 intersections on the city territory were carried out. The model was tested on bus line number 4 of PT in Novi Sad. The model showed that it is possible to achieve certain savings regarding the number of vehicles with the unchanged headway, that is, the unchanged level of service which is offered to the users. With the application of the model in real traffic conditions, significant savings, as well as operating and external costs’ reduction, can be achieved, which contributes to the sustainability of public bus transport in urban environments.

Impacts of Real-Time Transit Information on Bus Passengers’ Travel Choices Based on Travel Behaviour Survey

Real-time transit information (RTI) service can provide travellers with information on public transport and guide them to arrange departure time and travel mode accordingly. This paper aims to analyse travellers’ choices under RTI by exploring the relationship between the related variables of RTI and passengers’ travel choice. Based on the stated preference (SP) survey data, the ordinal logistic regression model is established to analyse the changing probability of passengers’ travel behaviour under RTI. The model calculation results show that travellers getting off work are more likely to change their travel choice under RTI. When data from the control and experimental groups are compared, the differences in route selection are significant. Specifically, passengers with RTI have a more complex route selection than those without, including their changes of travel mode, departure time, vehicles, and stop choices. The research findings can provide insights into the optimisation of intelligent transit information systems and the strategy of RTI. Also, the analysis of passengers’ travel choice under RTI in the transit network can help to improve network planning.

Characteristics associated with willingness to walk further than necessary to the bus stop: Insights for public transport-related physical activity

Background and aimsThere is untapped potential for public transport-related physical activity to make an important contribution to total physical activity and hence improve health. This study aimed to determine the willingness of public transport users to walk further than necessary to a stop, and the characteristics of those willing to do so. MethodsThis study used data from three waves (2016, 2017, 2018) of the Metro Tasmania Customer Satisfaction Survey (CSS), an annual cross-sectional survey of bus passengers in Tasmania, Australia. Linear and logistic regression modelled associations between socio-demographic and transport behaviour characteristics with willingness to travel further to usual bus stop if frequency was improved (yes/no), and if willing, the extra distance (metres) prepared to travel. Analyses were restricted to those reporting walking to their bus stop (n = 1402). ResultsHalf of 1402 bus passengers were prepared to walk further (average 521 m) to their usual bus stop if frequency was improved. A range of characteristics were positively (residential location) and negatively (age, female sex, retired/on pension, no regular motor vehicle access, intermittent public transport use, higher public transport-related physical activity) associated with willingness to walk further to the bus stop. Distance willing to walk varied by a range of demographic characteristics (sex, household income, age, employment status, bus use, public transport-related physical activity). Only age was consistently associated across all three surveys: younger bus passengers were more willing to walk further and recorded greater distances willing to walk. ConclusionsThe characteristics identified provide insights into which population groups may be more amenable to strategies to increase public transport-related physical activity, and which groups may require further investigation to identify reasons for lack of willingness to walk further to bus stops. Improving bus service frequency may increase public transport-related physical activity and confer health benefits.

Optimal assignment of buses to bus stops in a loop by reinforcement learning

Bus systems involve complex bus–bus and bus–passengers interactions. In this paper, we study the problem of assigning buses to bus stops to minimise the average waiting time of passengers. We formulate an analytical theory for two specific cases of interactions: the normal situation, where all buses board passengers from every bus stop, versus the novel “express buses” where disjoint subsets of non-interacting buses serve disjoint subsets of bus stops. Our formulation allows for the exact calculation of the average waiting time for general bus loops in the two cases examined. Compared with regular buses, we present scenarios where “express buses” show an improvement in terms of average waiting time. From the theory we can obtain useful insights: (1) there is a minimum number of buses needed to serve a bus loop, (2) splitting a crowded bus stop into two less crowded ones always increases the average waiting time for regular buses, (3) changing the destination of passengers and location of bus stops do not influence the average waiting time. Subsequently, we introduce a reinforcement-learning platform that can overcome the limitations of our analytical method to search for better allocations of buses to bus stops that minimise the average waiting time. Compared with the previous cases, any possible interaction between buses is allowed, unlocking novel emergent strategies. We apply this tool to a simple toy model and three empirically-motivated bus loops, based on data collected from the Nanyang Technological University shuttle bus system. In the simplified model, we observe an unexpected strategy emerging that could not be analysed with our mathematical formulation and displays chaotic behaviour. The possible configurations in the three empirically-motivated scenarios are approximately 1011, 1011 and 1020, so a brute-force approach is impossible. Our algorithm can reduce the average waiting time by 12% to 32% compared with regular buses and 12% to 29% compared with express buses. This tool can have practical applications because it works independently of the specific characteristics of a bus loop.

Customized bus passenger boarding and deboarding planning optimization model with the least number of contacts between passengers during COVID-19

The COVID-19 epidemic has had a major impact on people’s normal travel. Optimizing the control of the number of passengers boarding and deboarding the customized bus (CB) at CB stops can reduce the contact between passengers in the course of travel, which is meaningful for COVID-19 epidemic prevention and control. In this paper, a dynamic programming model based on nonlinear integer programming (NIP) is established to study the problem of boarding and alighting planning at various CB stops under the influence of COVID-19. Using Gurobi 9.1.1 solver, the optimal plan for passengers boarding and deboarding CB buses could be obtained. Besides, the mathematical model established in this paper can obtain the minimum value of the total number of contacts between passengers during travel under different CB numbers. It is found that the model solution results eventually form a Pareto frontier. When the number of CB buses increases, the total number of contacts between passengers will decrease This study has positive significance for ensuring the normal travel of passengers during the COVID-19 epidemic, and provides useful references for the studies about the planning of the customized bus.

Autonomous Bus Fleet Control Using Multiagent Reinforcement Learning

Autonomous buses are becoming increasingly popular and have been widely developed in many countries. However, autonomous buses must learn to navigate the city efficiently to be integrated into public transport systems. Efficient operation of these buses can be achieved by intelligent agents through reinforcement learning. In this study, we investigate the autonomous bus fleet control problem, which appears noisy to the agents owing to random arrivals and incomplete observation of the environment. We propose a multi-agent reinforcement learning method combined with an advanced policy gradient algorithm for this large-scale dynamic optimization problem. An agent-based simulation platform was developed to model the dynamic system of a fixed stop/station loop route, autonomous bus fleet, and passengers. This platform was also applied to assess the performance of the proposed algorithm. The experimental results indicate that the developed algorithm outperforms other reinforcement learning methods in the multi-agent domain. The simulation results also reveal the effectiveness of our proposed algorithm in outperforming the existing scheduled bus system in terms of the bus fleet size and passenger wait times for bus routes with comparatively lesser number of passengers.

Внедрение автоматизированных систем в деятельность автотранспортных предприятий на примере СПб ГУП «Пассажиравтотранс»

The research presents the results of testing foreign software products Optibize™ of Optibuscompany and Mobileye Shield+ of Mobileye company, providing automation and optimization of such processes of public transport passenger transportations as dispatching and control of accidents during the movement of vehicles. These processes affect such indicators of passenger service’s quality as speed, accessibility and safety of public transport, which determine the relevance of the research topic. The experience of using automated systems in foreign countries is studied and their pilot testing in the conditions of domestic carrier’s work is carried out also. The testing took place on the basis of the largest in the North-West region of Russia operator of bus passenger transportation SPb SUE «Passazhiravtotrans» within the framework of international cooperation agreements with official representatives of companies pro-ducing automated systems of the State of Israel. During the empirical study the functionality of automated systems is confirmed, the performance indicators of vehicles on pilot routes are collected, and the actual test results obtained are indicated. Economic effects both in terms of optimizing the technological parameters of the enterprise and in terms of increasing the economic efficiency of production activities are identified. The revealed effects determine the practicability of introducing systems into the activities of companies, taking into account the necessary adaptation to the specifics of public transport management in the Russian Federation. The results of the study are of practical relevance for large passenger road transport carriers and regulatory authorities.

SOSIALISASI DAN EDUKASI PEMILAHAN SAMPAH PADA MASYARAKAT DI PARKIR BUS PARIWISATA SUNAN BONANG KABUPATEN TUBAN

The problem of waste is becoming increasingly complex due to limited space for processing waste, incompatibility in spatial planning, lack of waste processing facilities, low public knowledge regarding waste processing, the large number of land conversions for housing, and the rapid increase population in the Tuban Regency. This community service activity was carried out at the location of the religious tourism bus parking of the Sunan Bonang Tomb. Garbage scattered at the parking location comes from bus passengers who do not have the awareness to throw garbage in its place. In addition, the other main sources of waste come from traders at tourist parking locations and pedicab drivers. This condition is mostly caused by the low of knowledge and awareness of the community regarding waste and its processing. This education and socialization of waste sorting is carried out to traders, visitors and pedicab drivers around the bus parking location. In this activity, the majority of traders have good knowledge regarding waste sorting into organic and inorganic waste, while for pedicab drivers, the majority do not have good knowledge regarding waste sorting. It is hoped that in the future this community service activity can be carried out in a sustainable manner, so that later the waste at the bus parking location can be used into something useful

Investigation of bus evacuation flow rates for tunnel fire quantitative risk assessment

ABSTRACT To increase the knowledge of bus evacuation in tunnel fire scenarios, we investigated the bus evacuation flow rate in the event of a tunnel fire, starting with a video analysis of the 2012 Hsuehshan tunnel fire in Taiwan, to gain a preliminary understanding of an actual bus evacuation flow rate. Two evacuation situations were manifested with different flow rates: the first one in which bus passengers non-urgently evacuated as in the case of a daily bus experience (the first seven evacuees, 0.28 PPS (Person Per Second)) and another situation in which passengers feel the urgency to evacuate (the next twelve evacuees, 0.67 PPS). Based on the investigation of the real fire incident, we conducted a bus evacuation experiment and a bus alighting observation. And the results of flow rates of normal exit were within 0.69–0.88 and 0.21–0.48 PPS, respectively. These results were similar to the actual flow rates in the two assumed evacuation situations in the Hsuehshan tunnel fire incident (nonurgent and urgent), respectively. Our approach can provide a viable approach to describe evacuation flow rates during tunnel fires. Moreover, using the flow rate of the normal alighting situation was preferable for highly reliable tunnel fire safety evaluation.

Multi-stage deep learning approaches to predict boarding behaviour of bus passengers

Smart card data has emerged in recent years and provide a comprehensive, and cheap source of information for planning and managing public transport systems. This paper presents a multi-stage machine learning framework to predict passengers’ boarding stops using smart card data. The framework addresses the challenges arising from the imbalanced nature of the data (e.g. many non-travelling data) and the ‘many-class’ issues (e.g. many possible boarding stops) by decomposing the prediction of hourly ridership into three stages: whether to travel or not in that one-hour time slot, which bus line to use, and at which stop to board. A simple neural network architecture, fully connected networks (FCN), and two deep learning architectures, recurrent neural networks (RNN) and long short-term memory networks (LSTM) are implemented. The proposed approach is applied to a real-life bus network. We show that the data imbalance has a profound impact on the accuracy of prediction at individual level. At aggregated level, FCN is able to accurately predict the rideship at individual stops, it is poor at capturing the temporal distribution of ridership. RNN and LSTM are able to measure the temporal distribution but lack the ability to capture the spatial distribution through bus lines.

Pengaruh Service Quality, Preceived Value dan Brand Image Terhadap Loyalitas Pelanggan Trans Lulo Kota Kendari

This study aims to analyze the relationship between the variables of Service Quality, Preceived Value, Brand Image and Consumer Loyalty through a case study on Trans Lulo Bus passengers in Kendari City. The sampling technique used in this research is to use the purposive sampling method. The sample used in this study is the Kendari city community who have used the Kendari City Translulo transportation service. The number of samples in this study were 94 people. The analytical method used in this study uses Structural Equation Modeling (SEM) using the SMART PLS 3.0 program. The results of this study indicate that Brand Image and Service Quality have a positive and significant effect on customer loyalty, then perceived value has a positive and significant effect on brand image. While perceived value does not have a positive and significant effect on Customer Loyalty, then Service Quality has no significant effect on Brand Image

Research on new energy electric shared bus route optimization based on floyd algorithm

With the rapid development of cities, the problem of public transport congestion is becoming more and more serious, which affects the commuting punctuality and ride experience of workers. Shared bus has the characteristics of flexible route, comfortable ride and high punctuality rate, and is developing rapidly. In order to save energy and reduce emissions and reduce the impact of vehicles on the urban environment, shared buses are mostly electric buses with new energy sources. As the new energy electric bus is limited by the range and the uncertain demand of shared bus passengers, it is particularly important to plan the driving route in advance. This paper takes typical shared bus routes in LG City as an example, and carries out operation route planning on Visual C++ platform. Plan bus routes according to road conditions and passenger travel needs. The scheme shows that the Floyd algorithm can optimize the shared bus route, ensure sufficient power operation, effectively reduce the company’s operating cost, and assist the decision of route scheme. The research results of this paper have practical guiding significance and reference value for the sustainable development of urban commuting in the future.

Design of Information Service System of Urban Bus Terminal under the Background of Mobile Internet

With the rapid development of highway transportation industry, the traditional manual passenger transport management mode can no longer meet the requirements of the development of highway passenger transport industry in the new period. From the perspective of passenger service in urban bus terminal, this paper puts forward a design scheme of passenger service information system in passenger terminal based on mobile Internet technology in view of the increasing service demand of passengers and passenger terminal. By using modern computer technology and information technology, the information service system of urban bus passenger station is upgraded, so as to realize timely and accurate collection and transmission of information, maximize information sharing, and enhance the on-site decision-making and command ability of the station. By integrating the information of various modes of transportation, we can realize the way of information sharing and provide high-quality information services for passengers.

On the design of an optimal flexible bus dispatching system with modular bus units: Using the three-dimensional macroscopic fundamental diagram

This study proposes a novel flexible bus dispatching system in which a fleet of fully automated modular bus units, together with conventional buses, serves the passenger demand. These modular bus units can either operate individually or combined (forming larger modular buses with a higher passenger capacity). This provides enormous flexibility to manage the service frequencies and vehicle allocation, reducing thereby the operating cost and improving passenger mobility.We develop an optimization model used to determine the optimal composition of modular bus units and the optimal service frequency at which the buses (both conventional and modular) should be dispatched across each bus line. We explicitly account for the dynamics of traffic congestion and complex interactions between the modes at the network level based on the recently proposed three-dimensional macroscopic fundamental diagram (3D-MFD). To the best of our knowledge, this is the first application of the 3D-MFD and modular bus units for the frequency setting problem in the domain of bus operations.Numerical results show the improvements in the total system cost made by adjusting the number of combined modular bus units and their dispatching frequencies to the evolution of both, the car and the bus passenger demand. A comparison with the commonly used approach that considers only the bus system (neglecting the complex multimodal interactions and congestion propagation) reveals the value of the proposed modeling framework. Finally, a sensitivity analysis of the effect of the operating unit cost of modular bus units, the size of the bus network, and the size of the bus fleet sheds light on the robustness of the proposed optimization framework.

Measuring accessibility to health care services for older bus passengers: A finer spatial resolution

Health care accessibility is a vital indicator for evaluating areas where there are medical shortages. However, due to the lack of population data with a satisfactory spatial resolution, efforts to accurately measure health care accessibility among older individuals have been hampered to some extent. To address this issue, we attempt to measure accessibility to health care services for older bus passengers in Nanjing, China, using a finer spatial resolution. More specifically, based on one month's worth of bus smart card data, a framework for identifying the home stations (i.e., a passenger's preferred station near their residence) of older passengers is developed to measure the aggregate demand at the bus stop scale. On this basis, a measurement that integrates the Gaussian two-step floating catchment area (2SFCA) and the adjusted 2SFCA methods (referred to as the adjusted Gaussian 2SFCA method) is proposed to measure accessibility to health care services for older people. The results show that: (1) almost all home stations experience inflated demand, especially those located in the suburbs; (2) despite abundant health care resources, home stations in urban districts are rarely identified as high accessibility stations, due to high demand densities among the older population; and (3) more attention should be paid to two types of home stations – those with a medical institution and those with bed shortages, respectively. The first type is predominantly distributed in the periphery of the city, in the suburbs where the travel time required to access the nearest health care service by bus is longer. The second type is mostly located in the outskirts of urban districts and in the central area of one suburb. These findings could help policy makers to implement more appropriate measures to design and reallocate health care resources.

Public bus transport service satisfaction: Understanding its value to urban passengers towards improved uptake

To accurately direct investments towards sustainable transit, current transport status and factors driving passengers towards private cars instead of public transport (PT) should be identified first. Past research advocated improvements in PT to shift mode-usage but has yet to model the different causal effects that direct bus users to cars in rapidly developing yet congested areas. On-board questionnaire survey data from intra-city Abu Dhabi bus passengers (n = 1520, variables = 31) over a month were gathered in this study during both weekends and weekdays. The study modelled existing bias of travellers and quality attributes as antecedents of bus service's perceived value for money (VfM) and satisfaction from level of service (LoS) and mode choice (car vs. bus) as the ultimate consequence. Findings revealed that any previous biased opinions of travellers adversely affected satisfaction and perceived value, while quality attributes had a positive effect. Mode use was influenced by satisfaction from LoS (frequency of buses and network coverage), which was a positive consequence of perceived VfM (quality of ride and level of fare trade-off). Journey time and bus-stop waiting area quality also positively influenced satisfaction from fare level while passenger socio-demographic distribution showed that most respondents travelled more than five times a week by bus and were full-time workers and transport agencies may target service improvements around office-hours.