Bus Companies Research Articles

Evaluating fare evasion risk in bus transit networks

In Proof-of-Payment Transit Systems (POP-TSs), fare evasion is a crucial issue for Transit Agencies (TAs) and/or Public Transport Companies (PTCs) worldwide. The related research background is based on the standard ratio between evaders and inspected passengers, whereas no research quantified the risk of fare evasion in POP-TSs. The objective of this study is the introduction of a framework covering this gap: it integrates fare evasion factors, prediction models, a risk-based method and returns the risk value on (parts of) routes as a function of the frequency of fare evasion, the related severity and exposure terms. Next, routes are ranked according to the risk value and classified by a 5-level scale, to show the (parts of) routes with the highest risk of evasion. Results show the capability of this framework on about 20,000 real-world data records gathered by a mid-sized Italian bus company through fare inspection logs and passenger surveys. To conclude, this framework is a support tool for TAs/PTCs to improve fare compliance and can be incorporated into any transit managerial system.

Upaya Perusahaan Otobus Antar Kota Antar Provinsi Dalam Meningkatkan Keunggulan Bersaing

The rise of the phenomenon of bus companies competing with each other and competing gaverise to various strategies to win their competitive advantage. For this reason, this study aimsto investigate and analyze a number of factors that cause competitiveness such as quality ofservice, technology and information systems and knowledge management on the competitiveadvantages of bus companies. The population and research sample are all bus companiesbetween cities and provinces in the island of Java, with the unit of analysis of bus companymanagers being observed in 2022 in August - December using physical and virtualquestionnaire media. Primary data analysis techniques were carried out by using statisticaldescriptive tests, testing the quality of research data instruments and other feasibility, testingthe research hypothesis, and multiple linear regression tests with SEM PLS path analysis.Findings indicate that there is a positive and significant influence on competitive advantagethrough the variables of this study, namely service quality, information technology andsystems, and knowledge management applied by bus companies. Theoretical contribution onthe theoretical aspects of detection and measurement which proves a number of variablescapable of influencing the competitive advantage of service companies. Practice/policycontribution, for company managers this research is relevant which has information andreferences in an effort to increase competitive advantage through the variables observed inthis research.Keywords: Competitive Advantage, Service Quality, Information Technology, Knowledge Management

Tinjauan Islam tentang Praktek Hybrid Contract pada Perusahaan Otobus Handoyo

PO Handoyo is a bus company with a unique innovation, namely the implementation of a hybrid contract. One of the hybrid contract practices implemented by POs. Handoyo is the purchase of bus tickets including meals. Hybrid contract is an agreement between two parties to carry out a contract in which there are two or more contracts. This research aims to provide an understanding of what a Hybrid Contract is, and how it is practiced at PO Handoyo, as well as how the Islamic view of the application of the Hybrid Contract on buying trans Java-Sumatra bus tickets includes eating at PO Handoyo. The type of research used in this study is qualitative and literature using primary and secondary data sources. The results of this study are that the application of hybrid contracts in purchasing trans Java-Sumatra bus tickets including is a permissibility and does not belong to multiple contracts which are forbidden.

Intercity bus and rail services: Competition and welfare effects

We study the effects of the deregulation of intercity bus services in Europe on intermodal competition in long-distance land passenger transport and on social welfare. We consider a bus company with a flexible (Internet-based) business model and a rail operator with a rigid cost structure due to indivisibilities. We adjust the standard location model of horizontal differentiation to account for quality differences between modes, and for a bus capacity limit. We show that deregulation may turn the former rail monopoly on a route into a bus monopoly, particularly if bus quality is high enough and/or bus marginal cost is low enough. Since the bus is capacity constrained, then social welfare may be improved through a lump-sum transfer from bus to rail to restore competition and increase the number of travelers. Instead, we show that intermodal competition may reduce welfare (compared to rail monopoly) if the bus is inefficient and/or of low quality, so that bus services should be restricted by imposing quotas or even entry bans. Finally, we relax some assumptions and calibrate the model with data from the Genoa-Milan route in Italy. Numerical simulations confirm theoretical predictions and estimate annual welfare gains on the route under the compensation scheme.

A construction-and-repair based method for vehicle scheduling of bus line with branch lines

Bus vehicle scheduling is vital to reduce operational cost and ensure service quality for bus companies. Bus Vehicle Scheduling Problem of a bus line with Branch Lines (VSP-BL) is common in practice, but there is no study on this problem. In this paper, we propose a Construction-and-Repair based Method (C&RM) to solve the problem. In addition, existing studies seldom consider bus driver scheduling and rostering factors in vehicle scheduling problem, thus that the solution to the problem is hard for driver scheduling and rostering. To address this dilemma, we take driver scheduling and rostering factors into account in the solution method. C&RM includes two stages: The first stage uses a trip assignment strategy to assign timetabled trips to vehicles to construct a solution. Vehicle scheduling and some driver scheduling constraints are considered in this stage. If the constructive solution dose not satisfy all driver scheduling constraints, the second stage adopts a repair method to improve the solution to satisfy all the vehicle scheduling and driver scheduling constraints. Experimental results show that C&RM outperforms the comparative methods on the number of vehicles and in balancing vehicles’ driving tasks; moreover, the solution found by C&RM satisfies all the constraints of driver scheduling and rostering, which facilitates driver scheduling and rostering.

Integrated optimization of multi‐vehicle‐type timetabling and scheduling to accommodate periodic passenger flow

AbstractA method was developed for integrating the process of multitype bus timetable generation and chains of trips formed by considering multiperiod passenger flow characteristics. First, the cumulative passenger demand curve was fitted and combined with the vehicle trajectory. Second, according to the results, the combined departure interval for multiple vehicle types was determined, and a one‐way possible timetable set was established. Third, considering the departure time window, the upward and downward possible timetable sets were connected. A bi‐objective mixed integer nonlinear programming model based on a spatiotemporal network was developed through two‐way matching. The objective of the model was to minimize the generalized fleet cost (a problem solved by the continuous deficit function of multiple vehicle types) and passenger waiting time. For two‐way matching, the computational complexity was reduced according to the postroot jump traversal rule, and the 𝑘‐shortest path algorithm was used to solve the bi‐objective Pareto‐optimal solution set. Finally, the Harbin No. 96 bus line was used as an example to validate the proposed model and algorithm. The optimization reduced the bus purchase cost by 51.28%, energy loss cost by 31.78%, and passenger waiting time by 37.07%, indicating that the proposed model can significantly reduce the costs for bus companies and passengers.

Bus Fleet Accident Prediction Based on Violation Data: Considering the Binding Nature of Safety Violations and Service Violations

The number and severity of bus traffic accidents are increasing annually. Therefore, this paper uses the historical data of Chongqing Liangjiang Public Transportation Co., Ltd. bus driver safety violations, service violations, and road traffic accidents from January to June 2022 and constructs road traffic accident prediction models using Extra Trees, BP Neural Network, Support Vector Machine, Gradient Boosting Tree, and XGBoost. The effects of safety and service violations on vehicular accidents are investigated. The quality of the prediction models is measured by five indicators: goodness of fit, mean square error, root mean square error, mean absolute error, and mean absolute percentage error. The results indicate that the XGBoost model provides the most accurate predictions. Additionally, simultaneously considering safety and service violations can improve the accuracy of the model’s predictions compared to a model that only considers safety violations. Bus safety violations, bus service violations, and bus safety operation violations significantly influence traffic accidents, which account for 27.9%, 20%, and 16.5%, respectively. In addition to safety violations, the service violation systems established by bus companies, such as bus service codes, can be an effective method of regulating the behavior of bus drivers and reducing accidents. They are improving both the safety and quality of public transportation.

Short-Time Bus Route Passenger Flow Prediction Based on a Secondary Decomposition Integration Method

Bus passenger flow is one of the decisive factors for the development of public transportation. Therefore, accurate prediction of real-time passenger flow on bus routes not only helps bus companies to make reasonable scheduling plans to meet the travel needs of passengers but also promotes the sound development of urban public transportation and reduces pollution. In this paper, we propose a secondary decomposition integration method that combines empirical modal decomposition (EMD), sample entropy (SE), and kernel extreme learning machine (KELM) to achieve a short-time prediction of bus route passenger flow. The EMD decomposes the original passenger flow data into several intrinsic mode functions, measures the complexity of the decomposed intrinsic mode functions using SE, and performs a secondary decomposition of the intrinsic mode functions with the highest complexity using EMD, followed by the prediction of the two decomposition results using KELM. The final predicted result is the sum of the two results. The model is verified by the real card-swiping data of two bus lines per minute. Each group of data has 300 data, with 80% of the data as the training set and the remaining 20% as the test set, which can predict the passenger flow per minute. The experimental results show that the short-term bus passenger flow forecasting method proposed in this paper has high accuracy and good robustness.

Sociotechnical Factors Supporting Mobile Phone Use by Bus Drivers

OCCUPATIONAL APPLICATIONS Results of a survey of drivers working for two bus companies in Norway suggest that 20% of drivers sometimes use a mobile phone while driving, even though it is not permitted. Sociotechnical analysis of the system surrounding drivers at one of the companies elicited ways in which social and technical factors combined to support mobile phone use by bus drivers. These factors were arranged under four themes: increased societal dependence on technology; developments in bus driver culture; the need for bus drivers to resolve conflicting goals; and a lack of belief in adverse consequences of using mobile phone while driving. Our findings (i) support claims that driver-centered analyses of mobile phone use or other traffic safety challenges are an insufficient basis for the development of measures and should be supplemented by sociotechnical analyses; and (ii) can inspire the design of more comprehensive measures to help reduce mobile phone use and road safety risks.

Bus timetable optimization model in response to the diverse and uncertain requirements of passengers for travel comfort

<abstract> <p>Most existing public transit systems have a fixed dispatching and service mode, which cannot effectively allocate resources from the perspective of the interests of all participants, resulting in resource waste and dissatisfaction. Low passenger satisfaction leads to a considerable loss of bus passengers and further reduces the income of bus operators. This study develops an optimization model for bus schedules that considers vehicle types and offers two service levels based on heterogeneous passenger demands. In this process, passenger satisfaction, bus company income, and government subsidies are considered. A bilevel model is proposed with a lower-level passenger ride simulation model and an upper-level multiobjective optimization model to maximize the interests of bus companies, passengers, and the government. To verify the effectiveness of the proposed methodology, a real-world case from Guangzhou is presented and analyzed using the nondominated sorting genetic algorithm-Ⅱ (NSGA-Ⅱ), and the related Pareto front is obtained. The results show that the proposed bus operation system can effectively increase the benefits for bus companies, passengers, and the government.</p> </abstract>

COVID-19 and low-cost bus companies in Europe: before and during pandemic crisis strategies and customer perceptions

This paper aims at assessing the operational strategy of FlixBus during the COVID-19, in relation to its main competitors and to customers’ perceptions. We analysed FlixBus strategy based on its supply, and designed an online survey administered to European residents to understand their preferences towards leisure travelling during COVID-19. A sample of 437 respondents was collected and the Exploratory Factor Analysis followed by clustering was used to segment the customers’ perceptions. Results show that willingness to travel, change in modal choice and destination are the factors featuring most the five clusters. An analysis of the Flixbus routes shows an overall dynamic demand-response strategy and a flexible approach closely related to their competitors’ operations at the same time. FlixBus saw the pandemic as a new opportunity, entering in new markets and offering FlixDeal.

Bullying Behavior, Mediating Role of Employee Silence and their Effects on Organisational Citizenship Behavior: Evidence from Seven Iranian Metropolises

Depending on dominant organisational conditions, various factors may affect the service quality and employees' willingness to behave positively. Therefore, this study investigated the effects of bullying behaviour on organisational citizenship behaviour (OCB) through employee silence. This is an applied-descriptive survey consisting of drivers (1820 in total) of private bus companies in seven Iranian metropolises. The statistical population was selected through simple random sampling. After that, questionnaires were distributed, and the collected data were analysed through structural equation modelling (SEM) in SPSS and AMOS. The results revealed the effect of bullying behaviour on employee silence and OCB. Moreover, bullying behaviour had a negative effect on OCB with the mediating role of employee silence. The analysis of employee silence can provide opportunities to prevent negative behaviours in the workplace. Since there is scant research literature on the role of employee silence in the relationship between bullying behaviour and OCB, addressing this issue can help to fill the existing research gap.

Evaluation of complexity of urban bus routes

Bus transport is the main (often the only) passenger transport connecting all cities of Uzbekistan and their rural settlements and has an important social significance. In modern conditions, the main factor that motivates passengers to choose certain routes and modes of transport in public transport is safe and high speed. Operational conditions on city bus routes vary in complexity, requiring a special approach to planning traffic, measures to ensure fast and safe movement on the route, standardization of the quality of services, and the introduction of fair systems of state financial support. The current methods and technologies for determining the level of complexity of the direction recommended by researchers require specialists to conduct complex tests or special knowledge. There is a need for simple and universal methods of assessing the complexity of the route so that the competent authorities regulating the activities of urban public transport and transport operators can quickly make decisions. This article systematizes the factors influencing the complexity of regular routes served by bus companies operating in the structure of urban public transport and proposes a method of assessing the index of route complexity.

Evaluation of Fatigue Risk, Subjective Fatigue, and Work Motivation Level of Intercity Bus Driver

In Indonesia, the bus is one of the affordable transportation for intercity/province routes. However, there are accident risks faced by bus drivers related to fatigue caused by inadequate rest and sleep. The objective of this study is to assess the bus driver fatigue risks level, accompanied by work motivation and subjective fatigue. Using the convenience sampling method, 300 intercity bus drivers from 12 bus companies (male, age between 25-68 years old (44.06 ± 9.83)) agree to involve in the study. Fatigue risk level was estimated by fatigue likelihood score (FLS) which indicated by driving tasks hours and the rest time opportunity. Work motivation and subjective fatigue were measured using 20 questions. The FLS result has a range between 13-39 (scale 0-40) or the risks are categorized into medium to very high. The major finding in this study, while a fatigue risks were relatively high, the subjective fatigue level were low to medium, and work motivations were medium to somewhat high. Statistical test showed that work motivation has a significant correlation with fatigue risks (p < 0.05; r = -0.139), but not with a subjective fatigue level.

A distributed restoration framework for distribution systems incorporating electric buses

Electric buses can enhance the restoration of distribution systems. However, existing studies have focused on centralized restoration between the electric bus and the distribution system, ignoring the subjectivity and privacy of the electric bus company. This paper proposes a distributed restoration framework for distribution systems incorporating electric buses to address the problem. Firstly, a mixed-integer linear scheduling model of electric buses is constructed considering the bus service requirements, space–time characteristics, and energy characteristics. Secondly, a bi-level distributed restoration framework is proposed. The upper level aims to decide the energy restoration tasks of the electric bus company, and the lower level introduces a control center, using a sequential iterative approach to determine each electric bus's energy and bus service tasks. Thirdly, the distributed restoration model is developed using the augmented Lagrangian method and solved via the improved alternating direction multiplier method (ADMM). The improved ADMM can adaptively change the penalty factor to speed up the convergence. Finally, numerical simulations are performed by the IEEE 33-node distribution system. The results show that the participation of electric buses can enhance the restoration of distribution systems and the proposed distributed restoration framework has good convergence and high optimization efficiency.

Los Autobuses del Sur: Mexican Migrant Routes and Economies in the US South

This essay traces the regional expansion of migrant economies through the case of Mexican bus companies established throughout the US South in the 1990s. It draws on familial memories, archival collections, and newspaper articles to illustrate how entrepreneurs in the transit industry expanded their businesses regionally in the late twentieth century as Mexican communities settled and grew across the US South. Specifically, the piece examines how the ruta sureña (southern route) between Houston, Texas, and Atlanta, Georgia, in this era was established by Mexican migrants and facilitated by ethnic Mexican transit entrepreneurs. The bus routes traversing this ruta sureña, alongside migrants’ lived experiences, form part of a broader Latinx South, a region with multiple historical and contemporary points of entry.

Analysis of the Accident Propensity of Chinese Bus Drivers: The Influence of Poor Driving Records and Demographic Factors

Previous studies have shown that bus drivers are a major contributing factor to bus accidents. The aim of this study is to explore the factors that contribute to the presence of accident propensity among bus drivers, as well as the relative importance of each influencing factor and the mechanism of influence. To this end, a C5.0 decision tree model was developed to determine the relative importance as well as rank the importance of the impact of poor driving records and demographic factors on accident propensity, and a binary logistic regression model was developed to analyze the relationship between accident propensity and the different values of each essential influencing factor. Based on our results, we found that: (1) the number of violations had the most significant effect on bus drivers’ accident propensity, followed by age, driving age, and number of alarms; (2) violations and alarms are positively related to bus driver accident propensity; age and driving age are inversely related to bus driver accident propensity; and (3) men have a higher accident risk probability than women. This study’s findings will help bus companies and traffic management authorities to implement more targeted improvements to their bus driver management programs.

Deep Reinforcement Learning based dynamic optimization of bus timetable

Bus timetable optimization is a key issue to reduce operational cost of bus company and improve the transit service quality. Existing methods optimize the timetable offline. However, in practice, the short-term passenger flow may change dramatically from time to time. Timetables generated offline cannot be adjusted in real time to handle the changed passenger flow. In this paper, we propose a Deep Reinforcement Learning based bus Timetable dynamic Optimization method (DRL-TO). In DRL-TO, the problem of bus timetable optimization is formulated as a Markov Decision Process (MDP). A Deep Q-Network (DQN) is applied as the agent to decide whether a bus departs at each minute during the service period. Therefore, departure intervals of bus services are determined in real time in accordance with passenger demand. We identify several new and useful state features for the DQN agent, including the load factor, the carrying capacity utilization rate, passengers’ waiting time and the number of stranded passengers. Considering the interests of both the bus company and passengers, a reward function is designed, which includes metrics of full load rate, empty load rate, passengers’ waiting time, and the number of stranded passengers. Experiments demonstrate that, in comparison to the timetable generated by offline optimization approaches and the manual method, DRL-TO can dynamically determine the departure intervals based on the real-time passenger flow, and generate a timetable with less departure time points (i.e., operational cost) and shorter passengers’ waiting time (i.e., higher quality of service).

The association of job fatigue with mental disorders among bus drivers.

Mental disorders are a global problem with growing importance. However, the contribution of work factors to the development of mental disorders is inconclusive. This study aimed to assess the impact of fatigue and job stress on mental disorders in a prospective cohort of bus drivers. The Taiwan Bus Driver Cohort Study (TBDCS) recruited 1652 bus drivers from a bus company in 2005. Participants self-completed a structured questionnaire in 2007, which included the Demand-Control-Support (DCS) model questions and the Swedish Occupational Fatigue Inventory-Chinese (SOFI-C). Psychiatric care visits and admissions were obtained from the National Health Insurance Research Dataset (NHIRD) from 2003 to 2016 for as a proxy for psychiatric diagnoses. Drivers with a history of psychiatric disorders before the questionnaire survey time were excluded (N=69). During the follow-up period, a new diagnosis with a psychiatric disorder was defined as an event. Cox proportional hazards model was used to estimate the hazard ratio (HR) for new one-set psychiatric disorders, adjusting for age, body mass index, marital status, education, alcohol consumption, smoking, exercise, bus driving experience, shift work, and chronic diseases. Among the 896 bus drivers retained for analysis, 85 were newly diagnosed with a psychiatric disorders. DCS score was not associated with the risk of developing a psychiatric disorders, but bus drivers with high SOFI-C scores (≥5) had an elevated risk for anxiety or mood disorders (HR 3.35, 95% confidence interval 1.23-9.09). Among bus drivers, occupational fatigue, as indicated by high a SOFI-C score, might result in an elevated risk of anxiety or mood disorders. Health service organizations should provide recommendations and guidance for drivers with high fatigue levels to avoid anxiety or mood disorders.

Are Smart Card Ticketing Systems Profitable? Evidence from the City of Trondheim

Electronic ticketing in public transportation based on smart cards is gaining momentum worldwide. It is widely recognized that a smart card system can deliver benefits to both passengers and operators, but due to its complexity, implementation can come at a considerable cost. Therefore, it is likely that a commercial appraisal from the perspective of the public transportation operator alone would reveal that costs are higher than benefits and, hence, economic non-viability. This paper presents the experiences of the Norwegian city of Trondheim, which recently implemented a fully-interoperable electronic smart card system. A social cost-benefit analysis of the scheme is presented, focusing on net overall benefits for the passengers, the bus company, the local transportation authority, and the rest of society. The main conclusion of the paper is that the smart card ticketing system in Trondheim delivers a positive net present value. The paper demonstrates that economic evaluation of smart card ticketing schemes using the principles of social cost-benefit analysis is desirable and possible. Because commercial non-viability may represent constraints to the implementation of such schemes, the findings presented in this paper provide valuable information to those currently working on smart card ticketing strategies.