Journal articles on the topic 'Overcrowding in Buses'
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Agrawal, Kinshuk, Hemant K. Suman, and Nomesh B. Bolia. "Frequency Optimization Models for Reducing Overcrowding Discomfort." Transportation Research Record: Journal of the Transportation Research Board 2674, no. 5 (April 23, 2020): 160–71. http://dx.doi.org/10.1177/0361198120912230.
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One of the most important aspects of improving public bus transport attractiveness is reducing overcrowding in buses. However, most of the mathematical models that focus on designing bus services minimize the total social cost without considering the overcrowding discomfort. Further, they are mostly non-linear in nature and use heuristic and meta-heuristic approaches. Thus, they are difficult to understand and use by practitioners. This work addresses these gaps through models that include overcrowding discomfort and are also easy to implement and contextualize by practitioners. The authors develop one non-linear and two linear models to determine the optimum frequency of buses and apply them over a network of 34 routes of Delhi. The results reveal that the existing number of buses in Delhi is not sufficient to cater to the existing travel demand of peak hours, even after their optimum allocation. The authors also present a step-by-step procedure to enable practitioners to determine the minimum additional number of buses required to reduce the target discomfort and waiting time.
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Suman, Hemant Kumar, and Nomesh B. Bolia. "Mitigation of overcrowding in buses through bus planning." Public Transport 11, no. 1 (April 25, 2019): 159–87. http://dx.doi.org/10.1007/s12469-019-00197-x.
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Varghese, Varun, and Bhargav Adhvaryu. "Measuring Overcrowding in Ahmedabad Buses: Costs and Policy Implications." Transportation Research Procedia 17 (2016): 145–54. http://dx.doi.org/10.1016/j.trpro.2016.11.070.
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Mtonga, Kambombo, Santhi Kumaran, Chomora Mikeka, Kayalvizhi Jayavel, and Jimmy Nsenga. "Machine Learning-Based Patient Load Prediction and IoT Integrated Intelligent Patient Transfer Systems." Future Internet 11, no. 11 (November 12, 2019): 236. http://dx.doi.org/10.3390/fi11110236.
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A mismatch between staffing ratios and service demand leads to overcrowding of patients in waiting rooms of health centers. Overcrowding consequently leads to excessive patient waiting times, incomplete preventive service delivery and disgruntled medical staff. Worse, due to the limited patient load that a health center can handle, patients may leave the clinic before the medical examination is complete. It is true that as one health center may be struggling with an excessive patient load, another facility in the vicinity may have a low patient turn out. A centralized hospital management system, where hospitals are able to timely exchange patient load information would allow excess patient load from an overcrowded health center to be re-assigned in a timely way to the nearest health centers. In this paper, a machine learning-based patient load prediction model for forecasting future patient loads is proposed. Given current and historical patient load data as inputs, the model outputs future predicted patient loads. Furthermore, we propose re-assigning excess patient loads to nearby facilities that have minimal load as a way to control overcrowding and reduce the number of patients that leave health facilities without receiving medical care as a result of overcrowding. The re-assigning of patients will imply a need for transportation for the patient to move from one facility to another. To avoid putting a further strain on the already fragmented ambulatory services, we assume the existence of a scheduled bus system and propose an Internet of Things (IoT) integrated smart bus system. The developed IoT system can be tagged on buses and can be queried by patients through representation state transfer application program interfaces (APIs) to provide them with the position of the buses through web app or SMS relative to their origin and destination stop. The back end of the proposed system is based on message queue telemetry transport, which is lightweight, data efficient and scalable, unlike the traditionally used hypertext transfer protocol.
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Silva, Ricardo, Soong Moon Kang, and Edoardo M. Airoldi. "Predicting traffic volumes and estimating the effects of shocks in massive transportation systems." Proceedings of the National Academy of Sciences 112, no. 18 (April 20, 2015): 5643–48. http://dx.doi.org/10.1073/pnas.1412908112.
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Public transportation systems are an essential component of major cities. The widespread use of smart cards for automated fare collection in these systems offers a unique opportunity to understand passenger behavior at a massive scale. In this study, we use network-wide data obtained from smart cards in the London transport system to predict future traffic volumes, and to estimate the effects of disruptions due to unplanned closures of stations or lines. Disruptions, or shocks, force passengers to make different decisions concerning which stations to enter or exit. We describe how these changes in passenger behavior lead to possible overcrowding and model how stations will be affected by given disruptions. This information can then be used to mitigate the effects of these shocks because transport authorities may prepare in advance alternative solutions such as additional buses near the most affected stations. We describe statistical methods that leverage the large amount of smart-card data collected under the natural state of the system, where no shocks take place, as variables that are indicative of behavior under disruptions. We find that features extracted from the natural regime data can be successfully exploited to describe different disruption regimes, and that our framework can be used as a general tool for any similar complex transportation system.
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Surmařová, Simona, Martin Vrána, and Jan Ilík. "Travel behaviour changes during the pandemic: Prague-Pilsen rail case study." Review of Economic Perspectives 22, no. 4 (December 1, 2022): 317–32. http://dx.doi.org/10.2478/revecp-2022-0015.
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Abstract The COVID-19 pandemic has affected many aspects of our everyday lives. Governments have taken numerous measures to contain the spread of the pandemic, which has had a direct impact on daily mobility, modal choice and the function of public transport. This study uses quantitative and qualitative data to describe how the pandemic influenced travel on the Prague-Pilsen (Praha-Plzeň) railway line. The results of the case study on the Prague-Pilsen railway line are consistent with experiences in other countries. 38% decrease in passenger numbers was found between 2019 and 2020. Although numbers are increasing again, they still have not reached the pre-pandemic level. The number of connections has also decreased by a third on average (2019 to 2020). We also conducted in-depth interviews with train passengers on the above-mentioned route. Two-thirds of passengers stated that the frequency of their journeys had not been affected by the pandemic. However, like the other participants, they described other changes caused by the pandemic. Fear of infection played an important role, and the inconvenience of overcrowding was mentioned several times. The switch from buses to trains was mentioned, as was the fact that more and more travellers prefer to travel first class. In some cases, changes in the temporality of trips were also documented. The survey suggests that respondents travel less frequently by train for systematic, functional, health or social reasons.
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Nurlaela, Siti, and Andrew William. "TransJakarta Service Evaluation in Controlling COVID-19 Transmission Using Twitter Sentiment Analysis." Journal of Regional and City Planning 34, no. 2 (August 18, 2023): 156–74. http://dx.doi.org/10.5614/jpwk.2023.34.2.2.
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This study attempted to understand passenger perception of using public transport by utilizing Twitter data about the services of the TransJakarta Busway. Tweets were the main data source to capture users’ responses toward these services. Users’ perceptions were analyzed by sentiment analysis using a naïve Bayes algorithm. Furthermore, content analysis was used to inform improvements in service maintenance. The findings showed that the pandemic had a major impact on TransJakarta services, from a decrease in users, route closures, and fleet reductions to changes in user behavior. Most Tweets were negative regarding (1) poor bus frequency, leading to long queues and passenger overcrowding at bus stops and inside buses; (2) failure to maintain social distancing measures; (3) frequent violations of the 50% bus capacity reduction during peak hours, and showing a lack of consideration in measuring demand size during peak hours; (4) staff’s weak control of implementing the health protocol exacerbated poor services. This study suggests service improvement based on peak hour demand analysis to offset the implications of a 50% capacity restriction by providing proper bus frequencies and headway arrangements considerable enough to avoid crowding, followed by optimal monitoring of health protocol by staff. Tweet data may inform poor management in controlling the transmission of COVID-19 on public transportation. Hence, using Twitter data could replace conventional data collection methods like user interviews. Beneficial information from Tweet data can be captured at relatively low costs. Therefore, it may aid the evaluation of PPKM policy implementation to create more resilient public transportation during pandemics.
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Camargo, Julián, Luis González, Diego Segura, Fabian Garay, and Nubia Rincón. "Orientación de Pasajeros con Discapacidad Visual dentro del Sistema de Transporte Masivo Transmilenio, mediante Geolocalización Satelital." Ingeniería 22, no. 2 (May 5, 2017): 283. http://dx.doi.org/10.14483/udistrital.jour.reving.2017.2.a08.
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Context: Although the mass-transport system Transmilenio provides audio information for travelers’ guidance, this is not helpful enough to blind users who are not able to transit easily within the system. For these reason, portable guidance devices are needed to improve the level of autonomy of the visually impaired people while using the transport system.Method: A review of aid devices to improve the level of autonomy of people with visual impairment was conducted so as to define the most practical technology for building an affordable device usable in the city of Bogotá. Subsequently, the functional modules of the device were defined, including file storage, sound reproduction, user interface and satellite geolocalization and location. Once built, the operation of the device was tested with 10 volunteers in condition of visual impairment who were oriented with the device between two main stations of one Transmilenio line; a final statistical study was conducted on the operation and usability perception of the device by the users.Results: 100% of the users were able to reach their destination successfully in the pilot test. In regards to the usability perception, users highlighted features such as sound indications for setting the device and orientation guidance throughout the journey. On the other hand, one of the main difficulties found was to correctly identify the bus approaching the stop and similarly locating the corresponding boarding door, as multiple bus routes may alight in the same door.Conclusions: The device was built incorporating low-cost technologies intended to make it affordable in an eventual mass—scale production. Likewise, a discreet design was chosen so as to lessen the risk of robbery, which unfortunately is a frequent issue in the Transmilenio system due to overcrowding of buses and stations. Additionally, we remark that the prototype can be made smaller by using special—purpose circuit boards. Policy-makers may take into account these considerations for an eventual wide implementation as part of governments’ plans for mobility inclusion in mass-transport systems for disabled people, in comparison with other alternatives such as smart cell phonesLanguage: Spanish.
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GIRMA, Mulugeta, and Berhanu WOLDETENSAE. "PASSENGERS’ PERCEPTIONS ON SECURITY AND SAFETY IN PUBLIC TRANSPORTATION IN ETHIOPIA: A CASE STUDY OF ADDIS ABABA." Scientific Journal of Silesian University of Technology. Series Transport 113 (December 1, 2021): 61–73. http://dx.doi.org/10.20858/sjsutst.2021.113.5.
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Due to its low fares, public bus transportation as a means of urban road mobility is a popular choice, particularly among city inhabitants. However, owing to its high level of crowdedness, it poses a greater risk of security and safety, particularly during peak hours. Moreover, passengers have continued to voice their dissatisfaction about the services offered, as well as the criminality that occurs in the station and on the bus. The problem is exacerbated in developing countries due to increased travel demand and a lack of appropriate and integrated solutions. Consequently, the purpose of this study is to evaluate commuters' perceptions of their concerns about using public bus transportation in the city, with an emphasis on security and safety in bus operations. A questionnaire survey was used to obtain data from 500 users in the city for the study. Using the SPSS software, the data was analyzed. To find out what they think, a descriptive analysis was used. Overcrowding of buses, personal insecurity, and infrequent bus service are the three biggest concerns in using public bus transportation in the city, according to the results. Furthermore, most of the respondents were concerned about crime; specifically, pickpockets, inappropriate touching, and disrespectful language of drivers and conductors are the three top types of crime that concern passengers who use public bus transportation in the city. Additionally, most people felt more insecure while riding the bus and getting on/off the bus, particularly in the evening and between 9:00 and 12:00 p.m. local time. Thus, it is advised that the Addis Ababa City Transport Authority, the Public Bus Transport Enterprise, and other interested parties place a strong emphasis on security and safety when providing public transportation in the city. Furthermore, it is critical to perform regular victim surveys of passengers (as well as operators) to establish whether they have been criminally victimized on the bus system and by what type of crime. Equally important, regularly assess the likely usefulness of new crime prevention measures for reducing bus-related offenses and prepare an annual bus crime reduction strategy.
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Taranum, Arshiya, Satya Reddy, Muhammed Muntazeem G., and Bhaskar Kurre. "Factors associated with open air defecation in a rural field practice area of a medical college: a cross sectional study." International Journal Of Community Medicine And Public Health 7, no. 3 (February 27, 2020): 909. http://dx.doi.org/10.18203/2394-6040.ijcmph20200939.
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Background: Open defecation is the practice where people go out in fields, bushes, forests, open bodies of water or other open spaces rather than using the toilet to defecate. The health hazards due open air defecation are soil and water pollution, contamination of foods and propagation of flies which results in the spread of diseases like typhoid, cholera, dysenteries, diarrheas, hookworm diseases, ascariasis, viral hepatitis and other intestinal infections.Methods: A cross sectional study was conducted at Singanodi village. 122 houses were selected for interview. One member from each household, preferably the head of the family was interviewed. The questionnaire included the socio-demographic features, practices about sanitary latrine usage and awareness about the diseases due to open air defecation. Data was entered in MS Excel and analysed using SPSS vs 20.Results: In the study the prevalence of open air defecation was found to be 63.1%. Majority of the study participants (52.5%) had sanitary latrines in their houses. 15.6% of the household practices open air defecation in spite of having toilets in their homes. Significant association was found between education and overcrowding with open air defecation.Conclusions: The study reinforces the importance of creating awareness about the importance of sanitary latrines and involvement of Government, NGO and communities is essential to stop open air defecation practices.
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Jahangir, Selim, Ajay Bailey, Musleh Uddin Hasan, Shanawez Hossain, Marco Helbich, and Martin Hyde. "“When I Need to Travel, I Feel Feverish”: Everyday Experiences of Transport Inequalities Among Older Adults in Dhaka, Bangladesh." Gerontologist, July 19, 2021. http://dx.doi.org/10.1093/geront/gnab103.
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Abstract Background and Objectives Buses are the most common form of public transport for older adults in developing countries. With over 37% of total trips, buses are the principal mode of transport in Dhaka. The majority of older adults are dependent on buses because of their affordability relative to other modes such as auto-rickshaws, rideshares, and taxis. This study aims to investigate key barriers in accessing buses in Dhaka and the consequences of these barriers to the everyday mobility of older adults. Research Design and Methods Thirty participants aged 60 and older were recruited from 2 socioeconomically different neighborhoods in Dhaka. We employed a thematic analysis of visual surveys and in-depth interviews to understand older adults’ spatial and cultural context and their experiences using buses in their everyday lives. Results Boarding and deboarding buses were common barriers for older adults due to overcrowding and traffic congestion. In addition, older adults faced challenges such as ageism, gender discrimination, and undesirable behavior by transport personnel and co-passengers. These barriers affected their independent mobility and influenced their access to work and social life, contributing to their social exclusion. Discussion and Implications This study illustrates the challenges faced by older adults when accessing public transport and the need to improve access to work, health care, and social life. Inclusive transport policies are essential in low- and middle-income countries to improve the well-being of older adults.
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"Ticket Collection with Destination Prediction in Bus Services in Urban Areas using Time Based Predictive Algorithm." International Journal of Engineering and Advanced Technology 9, no. 1S (December 14, 2019): 126–31. http://dx.doi.org/10.35940/ijeat.a1025.1091s19.
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In the new age of automation and machine assisted function of the human way of life people still tend to notice verification and checking of tickets in local land transport such as trains and buses to still be operated by man. This project is a proposal of a new platform and method to book these tickets of buses on a local level. This can lead to decrease in the overcrowding of buses, easy time management of commuters, and smooth functioning of the bus business. Initially the bank details of the passenger must be linked to the app.Machine learning predictive parsing algorithm in combination with data mining features enable the prediction of the passengers to and fro details on a daily and timely basis. Then a SMS alert for ticket payment proof is sent to the user. In admin side, they calculate amount details using this application. Per day amount details of specific route or bus can be calculated by accessing the database. There is also a provision where the IMEI numbers of the consumers is collected. Through GPS system the IMEI numbers of the mobiles inside the bus is checked with the IMEI numbers of those in the database. Ticket defaulters are identified if the IMEI numbers are not present in the database. The entire trail of the transit is on a non-paper sever.
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Pan, Long, E. O. D. Waygood, and Zachary Patterson. "Would You Wait? Bus Choice Behavior Analysis Considering Various Incentives." Transportation Research Record: Journal of the Transportation Research Board, February 21, 2022, 036119812210768. http://dx.doi.org/10.1177/03611981221076843.
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During the peak hour, ridership is much higher, and this can lead to problems such as overcrowding for customers and vehicle bunching for the operator as dwell times increase for the lead bus. In this paper, we examined whether to avoid overcrowding people might be willing to wait for the next bus knowing there were seats and if they were offered an incentive. Three distinct types of incentive were offered, defined according to goal-framing theory. To obtain the choice data, a discrete choice experiment was developed and incorporated into an online survey that was distributed to public transport users. A binary logit model and a mixed multinomial logit model were used to investigate how different factors influence public transport users’ bus choice behavior. Results show several considerations that increase the likelihood of users agreeing to the request to wait. These include the weather being sunny/fine, not very cold, or both, the purpose being seeing a friend or shopping, longer in-vehicle time, shorter proposed bus waiting time, and the incentive. The results of the mixed multinomial logit model show variation among the respondents with regard to the incentives. We found that age, gender, work status, possession of a driver ID, and vehicle availability are significant predictors for incentive preference. In that our models target specific groups of users with tailored incentives, the results indicate how to persuade public transport users to avoid overcrowded buses.
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Borges Santos, Veruska, Carlos Eduardo S Pires, Dimas Cassimiro Nascimento, and Andreza Raquel M. de Queiroz. "A Decision Tree Ensemble Model for Predicting Bus Bunching." Computer Journal, May 8, 2021. http://dx.doi.org/10.1093/comjnl/bxab045.
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Abstract Travel delays and bus overcrowding are some of the daily dissatisfactions of public transportation users. These problems may be caused by bus bunching, an event that occurs when two or more buses are running the same route together, i.e. out of schedule. Due to the stochastic nature of the traffic, a static schedule is not effective to avoid the occurrence of these events; thus, preventive actions are necessary to improve the reliability of the public transportation system. In this context, we propose a decision tree ensemble model to predict bus bunching. We use an ensemble of Random Forest, eXtreme Gradient Boosting and Categorical Boosting models applied to Global Positioning System, General Transit Feed Specification, weather and traffic situation data. The efficacy of the proposed model has been demonstrated using real data sets and has been compared with four baselines: Linear Regression, Logistic Regression, Support Vector Machine and Relevance Vector Machine. According to the results, the proposed model can achieve an efficacy between 74 and 80% and can be used to predict bus bunching in real time up to 10 stops before its occurrence.
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Asgharzadeh, Mohammad, Behroz Mahdavipoor, Vahid Asgharzadeh, Mahya Pourostadi, Hossein Samadi Kafil, Ali Vegari, Zahra Taghinejad, Adel Bairamy, and Jalil Rashedi. "Why the COVID-19 Is Not Significantly Reduced in Iran?" Iranian Journal of Public Health, July 5, 2021. http://dx.doi.org/10.18502/ijph.v50i7.6616.
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Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was transported from China to Iran via passengers. The virus is transmitted through droplets from coughing, sneezing, talking and contact with infected surfaces. Due to high transmissibility in places such as clinics, medical offices, buses and offices where there are large crowds, it spread rapidly in Iran and caused the mortality of a significant number of people, especially the elderly with underlying disease. Preventing travel and gatherings, as well as applying house quarantine in Apr 2020, reduced COVID-19 somewhat but then due to lack of attention to social distancing, reducing the use of masks by the people and inappropriate decisions by the national committee on combating coronavirus (NCCC), including reducing the working hours of public offices and shops, reducing the staff of government offices, monopoly on the distribution of essential materials and supplies, the presence of overcrowding in clinics of medical centers, hospitals, and private clinics caused the decline of the disease in the country to decrease. Measures can be taken to prevent the spread of the virus as much as possible, including: rapid detection of infected people, their isolation, contact tracing, quarantine of people over 65 and under 15, protection of the elderly, prevention of gatherings, forcing the use of protective equipment in possible gatherings, and electronicizing public services.
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Lwanga, Alan, Hussein H. Mwanga, and Ezra J. Mrema. "Prevalence and risk factors for non-collision injuries among bus commuters in Dar es Salaam, Tanzania." BMC Public Health 22, no. 1 (May 13, 2022). http://dx.doi.org/10.1186/s12889-022-13284-9.
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Abstract Background Migration of people from rural to urban areas has led to the increase in demand for transportation services in the cities. However, authorities have failed to cope with this problem in a consistently manner. This has led to the increase in non-collision injuries among commuters. This study aimed at investigating the prevalence and risk factors for non-collision injuries among commuters using public transport in Dar es Salaam, Tanzania. Methods A cross sectional study was conducted in Dar es Salaam involving 290 commuters from 7 bus routes travelling to and from the city centre using public transport which are privately owned and commonly known as “daladala”. Stratified random sampling was used to sample buses based on the passenger carrying capacity (i.e. 15-24, 25-34 and 35-45 passengers). Systematic random sampling was used to get a total of three commuters from each bus for the interview. Results Lifetime prevalence of non-collision injuries was 71%, while these rates were 70 and 39% in the last 12 and 6 months, respectively. Commuters aged between 18 and 28 years experienced non-collision injuries the most (56%) in the last 12 months. Most non-collision injuries occurred on weekdays in the evening from 5:00 pm to 10:00 pm. Strong association was observed between the occurrence of non-collision injuries and commuting time between 5:00 pm to 10:00 pm (adjusted OR = 9.24; 95% CI: 2.68-19.54); boarding and disembarking (adjusted OR = 9.21; 95% CI: 3.77-25.11) and scrambling during boarding (adjusted OR = 5.03; 95% CI: 2.51-21.32). The lower limbs (adjusted OR = 8.64; 95% CI: 2.72-21.76) and the upper limbs (adjusted OR = 13.55; 95% CI: 5.32-33.21) were the most affected body parts. Conclusions This study has demonstrated high prevalence of non-collision injuries among commuters using public transport in Dar es Salaam. Travelling in the evening between 5:00 pm to 10:00 pm on the weekdays, boarding and disembarking especially when scrambling for the bus during boarding, overcrowding in the bus especially when the bus is already full with no seats available are the major risk factors for non-collision injuries.