Bus Travel Research Articles

Frequency of instrumental activities of daily living is associated with objectively measured physical activity in stable patients with cardiovascular disease

Abstract Introduction Implementation of instrumental activities of daily living (IADL) has the necessary items for independent living in community-dwelling, which is reported as a relevant factor for better prognosis in patients with cardiovascular disease (CVD). Physical activity (PA) is well-known to have benefits in reducing the risk of all-cause mortality and CVD. Although IADL and PA are similar behaviors and crucial intervention targets to prevent the recurrences of CVD in patients who participate in phase III cardiac rehabilitation, these interrelations remain unclear. Purpose This study aimed to evaluate the association between IADL frequency and objectively measured PA, including step counts and time of vigorous activity, in stable patients with CVD. Additionally, we examined whether detailed types of IADL frequency were associated with PA. Methods This was a single-center cross-sectional observational study. We included patients with CVD who received outpatient care with stable condition for at least six months. Participants completed Frenchay Activities Index (FAI) questionnaire as an assessment of IADL frequency. The FAI contains 15 items, classified as housework and leisure activity. We used accelerometers to measure the objective number of steps and minutes of moderate to high-intensity physical activities for two weeks and calculated their averages per day as indicators of PA levels. The associations of FAI total score and 15 FAI sub-items with physical activities (the number of steps and minutes of moderate to high-intensity physical activities per day) were analyzed using a multivariate linear regression model. Results Studied patients consisted of 1126 stable patients with CVD (mean age, 72.6 ± 10.0 years; 848 males). After adjusting for clinical confounding factors, high FAI total score was significantly associated with higher levels of physical activities (the number of steps per day: unstandardized coefficient [В] for FAI increase of 1 point = 78.1 [95% confidence interval {CI}, 54.9–101.4], Figure 1-A; the minute of moderate to high-intensity PA per day: В = 0.184 [95%CI, 0.063–0.304], Figure 1-B). In the sub-items of FAI, four items of housework activities (washing up, light housework, heavy housework, and local shopping) and six items of leisure activity (walking outside for > 15 minutes, actively pursuing hobbies, driving a car or bus travel, gardening, reading books and gainful work) were also positively associated with the number of steps per day. Conversely, only two items of leisure activity (walking outside and actively pursuing hobbies) were associated with moderate to high-intensity PA per day (Figure 2). Conclusions The frequency of IADL has a positive association with objectively measured PA, suggesting that IADL might be useful behavior to administrate PA in stable patients with CVD. Moreover, leisure activity in IADL is especially relevant to vigorous PA in these patients.Figure 1Figure 2

North West Transport Hub: a new life for Londonderry’s 150-year-old Waterside Station

A derelict 150-year-old railway station building in Northern Ireland has been reborn as a state-of-the-art multimodal transport hub with integrated rail, bus and active travel facilities. The 1875 Waterside Station in Derry/Londonderry was abandoned after bomb damage in the 1970s, and its hastily built replacement nearby soon reached capacity. A European Union-funded project has restored the old rail terminus to its former role and added a bus station, park-and-ride facility and links to the city’s greenways for cyclists and pedestrians. This paper provides an overview of the North West Transport Hub project, from inception to completion in 2022.

Probabilistic Forecasting of Bus Travel Time with a Bayesian Gaussian Mixture Model

Accurate forecasting of bus travel time and its uncertainty is critical to service quality and operation of transit systems: it can help passengers make informed decisions on departure time, route choice, and even transport mode choice, and it also support transit operators on tasks such as crew/vehicle scheduling and timetabling. However, most existing approaches in bus travel time forecasting are based on deterministic models that provide only point estimation. To this end, we develop in this paper a Bayesian probabilistic model for forecasting bus travel time and estimated time of arrival (ETA). To characterize the strong dependencies/interactions between consecutive buses, we concatenate the link travel time vectors and the headway vector from a pair of two adjacent buses as a new augmented variable and model it with a mixture of constrained multivariate Gaussian distributions. This approach can naturally capture the interactions between adjacent buses (e.g., correlated speed and smooth variation of headway), handle missing values in data, and depict the multimodality in bus travel time distributions. Next, we assume different periods in a day share the same set of Gaussian components, and we use time-varying mixing coefficients to characterize the systematic temporal variations in bus operation. For model inference, we develop an efficient Markov chain Monte Carlo (MCMC) algorithm to obtain the posterior distributions of model parameters and make probabilistic forecasting. We test the proposed model using the data from two bus lines in Guangzhou, China. Results show that our approach significantly outperforms baseline models that overlook bus-to-bus interactions, in terms of both predictive means and distributions. Besides forecasting, the parameters of the proposed model contain rich information for understanding/improving the bus service, for example, analyzing link travel time and headway correlation using covariance matrices and understanding time-varying patterns of bus fleet operation from the mixing coefficients. Funding: This research is supported in part by the Fonds de Recherche du Quebec-Societe et Culture (FRQSC) under the NSFC-FRQSC Research Program on Smart Cities and Big Data, the Canadian Statistical Sciences Institute (CANSSI) Collaborative Research Teams grants, and the Natural Sciences and Engineering Research Council (NSERC) of Canada. X. Chen acknowledges funding support from the China Scholarship Council (CSC). Supplemental Material: The e-companion is available at https://doi.org/10.1287/trsc.2022.0214 .

Pre-peak fare discount policy for managing morning peak demand of interregional bus travel: a case study in Seoul metropolitan area

ABSTRACT Pre-peak fare discount policies have become increasingly common in urban transit services and show potential to spread morning peak-hour demand. This study analyzes the departure time choice behavior of interregional bus passengers during morning hours. A mixed logit model is applied to estimate the probability of shifting departure time as a function of fare discount rate, in-vehicle congestion, and other influential factors, accommodating heterogeneity of passenger preferences. The analysis data are obtained through a stated preference survey, which is conducted to passengers who regularly use the interregional bus in Seoul metropolitan area. Choice models are segmented by departure time periods (peak, pre-peak, and post-peak) and occupation types (fixed time worker, flexible time worker, and student). Marginal utilities of the unobserved preferences are estimated to suggest policy implications. From the experimental analysis, target passengers for shifting departure time during peak hour are suggested as flexible time workers and students.

Estimation of the aggregation degree of public transport use among elderly people based on urban built environment

With the accelerated aging process, the increased willingness of elderly people to travel, and the concessionary bus travel policy implementation, public transport, especially buses, has become one of the important ways for China's elderly people to participate in social activities. Meanwhile, the increased use of public transport by elderly people results in serious conflicts with commuters. In order to understand details about when, where and why public transport trips of the elderly become large, this study investigates the aggregation degree of public transport use among the elderly as well as its determinants mainly from the viewpoint of spatial characteristics. Based on Smart card data and Baidu Map API, the aggregation degree of public transport use in elderly people is rated on a scale of 1 to 5. And then its correlation to the microscopic built environment is analyzed by using negative binomial regression. The results indicate that public transport use by elderly people is highly aggregative in both spatial and temporal dimensions. It is also found that the urban built environment has a significant effect on the aggregation degree of public transport use in the elderly and significant variables for four time periods on both weekdays and weekends are quite different. The proximity of housing estates, elderly activity centers, universities for the elderly, and medical and shopping facilities near bus stations increases the aggregation degree of public transport use by elderly people. This study will provide a reference basis for optimizing the public transport system in the aging society.

VARIABILITY OF PARATRANSIT TRAVEL TIMES: THE CASE OF KUMASI, GHANA

ABSTRACT While much has been reported about bus travel times and their variability for formal bus services, little is known about travel time variation for paratransit, the dominant means of transportation in most low- and middle-income countries (LMICs). This study quantifies the components of paratransit travel time on a selected route in Kumasi, Ghana. It analyzes the variability of travel times within the day and from day to day. A mobile phone app was employed to conduct a travel time survey onboard paratransit vehicles on the study route. GPS and stop-related data were collected. Various travel time variability measures and heat map was used for within day and day-to-day variability analysis in both directions of the study section. About 16% of travel time in the study section was spent dwelling (boarding and alighting). The variation in travel times across the day was comparatively higher than those of formal bus services and fluctuated across the day with no distinct pattern within any given time period. Both early and late trips contributed to this variation across the day. Fridays had significantly different variability from other weekdays.

SPATIAL MAPPING OF TRAVEL INFORMATION AND ASSESSMENT OF ROAD CONNECTIVITY

Abstract. Roads play a crucial role in the urban spatial structure. A place's development and growth depend on the road network connectivity and accessibility being the socio-economic and transportation carrier. It involves the mobility of people and goods from one place to another. The choice of mode of travel depends on the living standards, connectivity, and vicinity to the work area. The study uses satellite data to analyze road network connectivity using the connectivity indices of Mangalore City Corporation, a port city in India. The connectivity indices alpha, beta, gamma, and eta showed the Area's good connectivity with proper roads and interconnectivity. Using Dijkstra's algorithm, the least cost path is identified on which the spatial mapping of the travel information is made. The travel information raster served the commuter in knowing the time, distance, and cost of modes from all possible origins to each city center. Specifically, it serves as the base map for bus routes, their cost, and travel time for significant city bus stations. The cost of travel, Duration, and distance information is mapped for two-wheeler and four-wheeler commuters. The study used the Modis Land Use Land Cover Data to identify inaccessible road network areas.

Im/mobilising bus travel as an infrastructure of care: student experiences in a mid-size city

Many universities are transforming campuses by responding to globally significant, locally specific, economic, political, and social imperatives. Some are implementing urban and regional transformations in higher education delivery to increase student access and diversity. Their success can depend upon infrastructures provided by other parties. Public transport is an example. Transit accessibility and equity affect quality of life, livelihoods, life course, and liveability in cities. Growing numbers of international studies consider factors shaping student travel to and from university campuses by public transport; fewer address local socio-spatial experiences of travel. Informed by debates about differential accessibility of suburban and city campuses, we examined student experiences at an Australian regional university undergoing transformation. We report on a study assessing multiple trips to and from two campuses to five destinations. Rich insights were drawn from experiences of antisocial behaviour, vulnerability, and sub-optimal service provision and reveal why some students think public transport is a mode of last resort. Universities and their stakeholders need to know more about student experiences of mobility. Such knowledge could inform tailored transport interventions and universities’ willingness to encourage public transport providers to view their services as infrastructures of care.

ANALISIS PEMILIHAN MODA TRANSPORTASI UMUM MENUJU STASIUN GAMBIR MENGGUNAKAN TRANSPORTASI ONLINE DAN BUS TRANSJAKARTA

Public transportation acts as a sustainable mode of transportation to reduce the increasing level of pollution and traffic congestion. Public transportation has many types, in Jakarta, for example, online transportation and Transjakarta buses. This study aims to analyze the characteristics of online transportation travellers and Transjakarta buses, analyze the chances of choosing between the two modes of public transportation, and determine the level of service according to the community. Data collection using questionnaires distributed at Gambir station. Characteristics of travelers were analyzed using descriptive statistics. The probability of choosing a mode is analyzed using the binary logit difference model with the help of multiple linear regression equations. The level of service of the two modes of public transportation was analyzed using a Likert scale. The results showed that the characteristics of online transportation travellers are dominated by female, of productive age, highly educated, worked as an employee, earned quite a lot of money, traveled for vacation or recreational purposes, and the reason for choosing the mode was getting to the destination quickly. The characteristics of Transjakarta bus travellers are dominated by male, productive age, highly educated, work as an employee, earn quite high, travel for vacation or recreational purposes, and the reason for choosing the mode is the low price. The dominant choice of public transportation mode is online transportation. The level of online transportation services for the security and convenience aspects is in the good category, and the ease and reliability aspects are in the very good category.Keywords: characteristics of travellers, transportation mode, likert scale

Empowering revealed preference survey with a supplementary stated preference survey: demonstration of willingness-to-pay estimation within a mode choice case

Mode choice models play a pivotal role in transport demand modelling and help transport planners, engineers and researchers with policy and infrastructure investment evaluation. Recent mode choice studies primarily use revealed preference (RP) data to reflect individuals’ true behaviour. However, this may not be the best practice, given the lack of information in RP data. This study uses a nonlinear utility specification for a multinomial logit mode choice model development using high-quality travel data collected by a GPS-based smartphone application complemented by stated preference (SP) data. The model results highlight the impact of sociodemographic variables on mode choice behaviour and individuals’ willingness-to-pay (WTP) when the model is jointly developed compared to stand-alone SP and RP models. The main message of this study is that in addition to collecting RP, which is a reliable and unbiased source of data, collecting complementary SP data is beneficial as it provides information that is not otherwise available in RP data. This may include a proper variation in the public transport cost variable as demonstrated in this study. Moreover, to better understand the travellers' behaviour regarding the trade-off between time and cost a mixed multinomial logit (MMNL) model in the willingness to pay space is developed on the SP data. capturing the unobserved heterogeneity within the estimated WTPs, the MMNL model outputs reveal a higher variation in WTP of car in-vehicle travel time compared to bus in-vehicle travel time.

Bus Travel Training Programs to Identify Active Ingredients for Learning Among Transition-Age Youth With Cognitive Deficits

Abstract Date Presented 04/22/2023 This systematic review examines bus travel training to improve the mobility of cognitively impaired youth. The evidence is positive, but older and of low quality. Active ingredients are identified. More innovation and rigorous research are required. Primary Author and Speaker: Sarah E. Anderson Contributing Authors: Spencer R. Kaple, Nicole O. Tonyan, Jennifer P. Lundine, Carmen DiGiovine, Emily S. Patterson, Scott Swearingen, Amy Darragh

Bus Travel Time Prediction Based on the Similarity in Drivers’ Driving Styles

Providing accurate and real-time bus travel time information is crucial for both passengers and public transportation managers. However, in the traditional bus travel time prediction model, due to the lack of consideration of the influence of different bus drivers’ driving styles on the bus travel time, the prediction result is not ideal. In the traditional bus travel time prediction model, the historical travel data of all drivers in the entire bus line are usually used for training and prediction. Due to great differences in individual driving styles, the eigenvalues of drivers’ driving parameters are widely distributed. Therefore, the prediction accuracy of the model trained by this dataset is low. At the same time, the training time of the model is too long due to the large sample size, making it difficult to provide a timely prediction in practical applications. However, if only the historical dataset of a single driver is used for training and prediction, the amount of training data is too small, and it is also difficult to accurately predict travel time. To solve these problems, this paper proposes a method to predict bus travel times based on the similarity of drivers’ driving styles. Firstly, the historical travel time data of different drivers are clustered, and then the corresponding types of drivers’ historical data are used to predict the travel time, so as to improve the accuracy and speed of the travel time prediction. We evaluated our approach using a real-world bus trajectory dataset collected in Shenyang, China. The experimental results show that the accuracy of the proposed method is 13.4% higher than that of the traditional method.

Short-term bus travel time prediction for transfer synchronization with intelligent uncertainty handling

This paper presents two novel approaches for uncertainty estimation adapted and extended for the multi-link bus travel time problem. The uncertainty is modeled directly as part of recurrent artificial neural networks, but using two fundamentally different approaches: one based on Deep Quantile Regression and the other on Bayesian neural network. Both approaches use a recurrent neural network to predict multiple time steps into the future, but handle the time-dependent uncertainty estimation differently. We present a novel sampling technique in order to aggregate quantile estimates for link level travel time to yield the multi-link travel time distribution needed for a vehicle to travel from its current position to a specific downstream stop point or transfer site.To motivate the relevance of uncertainty-aware models in the domain, we focus on the connection protection application as a case study: An expert system to determine whether a bus driver should hold and wait for a connecting service, thus ensuring the connection, or break the connection and reduce its own delay. Our results show that the proposed quantile sampling method performs overall best for the 80%, 90% and 95% prediction intervals, both for a 15 min time horizon into the future (t+1), but also for the 30 and 45 min time horizon (t+2 and t+3), with a constant, but very small underestimation of the uncertainty interval (1–4 pp.). However, we also show, that the Bayesian model still can outperform the DQR for specific cases. Lastly, we demonstrate how a simple decision support system can take advantage of our uncertainty-aware travel time models to prioritize the difference in travel time uncertainty for bus holding at strategic points, thus reducing the introduced delay for the connection protection application.

Service Area Analysis for Determining the Accessibility to Bus Stops - A Case of Daund, Indapur and Baramati of Pune District

Abstract: Public transportation plays a vital role in the daily lives of millions of people in India, providing an affordable and convenient mode of travel. However, the accessibility of bus stops, the crucial starting point for public bus journeys, remains a significant concern. Accessibility is one of the most important outcomes of the transportation system. Public transport accessibility has gained vital importance in designing and evaluating the transit system in terms of mobility, and sustainability and has gained a considerable impact on life satisfaction in the form of perceived accessibility. Moreover, researchers have revealed several impacts and correlations of the provision of public transport accessibility to the environment and daily life. Therefore, the purpose of the study is to determine the service areas of bus stops in three taluks of the Pune district namely the Daund, Indapur and Baramati with specified impedance i.e., travel time using the ArcGIS Network Analyst tool. Through this study, the non-served areas can be identified and considered as critical zone that can be superimposed with various parameters to find an optimum location of additional facilities that would improve the public transportation system in the study region.

A comparative evaluation of the safety performance of bus priority route configurations

One way to promote public transport use in cities lies in establishing bus priority routes (BPRs) on main traffic arterials, to reduce bus travel times. But, BPRs require infrastructure changes in road layouts, creating more complex traffic settings that may have safety implications. Previous research indicated that design features affect BPRs' safety, but findings regarding the impacts of various BPR configurations are scarce. In this study, we examined the safety performance of three BPR configurations: barrier-separated central, open centre-lane and curbside BPRs, in Israel. Multivariate regression models were fitted to identify design features affecting accident occurrences on urban arterials with BPRs, using a database on all BPRs in operation. The comparative evaluations showed that barrier-separated BPRs were characterised by lower accident rates on road sections but by substantially higher accident numbers at junctions, relative to other BPR types, and particularly when bus-overtaking was possible. Hence, the use of barrier-separated bus routes should be reduced and bus-overtaking settings should be avoided, when implementing BPRs. In the comparison of curbside and center-lane BPRs none of them demonstrated a superior safety performance: the centre-lane BPRs were safer on sections while at junctions both types had advantages for certain accident types, thus, both forms are applicable in future BPR designs.

A New Big Data Approach to Understanding General Traffic Impacts on Bus Passenger Delays

This paper presents a new method to quantify the potential user time savings if the urban bus is given preferential treatment, changing from mixed traffic to an exclusive bus lane, using a big data approach. The main advantage of the proposal is the use of the high amount of information that is automatically collected by sensors and management systems in many different situations with a high degree of spatial and temporal detail. These data allow ready adjustment of calculations to the specific reality measured in each case. In this way, we propose a novel methodology of general application to estimate the potential passenger savings instead of using simulation or analytical methods already present in the literature. For that purpose, in the first place, a travel time prediction model per vehicle trip has been developed. It has been calibrated and validated with a historical series of observations in real-world situations. This model is based on multiple linear regression. The estimated bus delay is obtained by comparing the estimated bus travel time with the bus travel time under free-flow conditions. Finally, estimated bus passenger time savings would be obtained if an exclusive bus lane had been implemented. An estimation of the passenger’s route in each vehicle trip is considered to avoid average value simplifications in this calculation. A case study is conducted in A Coruña, Spain, to prove the methodology's applicability. The results showed that 18.7% of the analyzed bus trips underwent a delay exceeding 3 min in a 2,448 m long corridor, and more than 33,000 h per year could have been saved with an exclusive bus lane. Understanding the impact of different factors on transit and the benefits of a priority bus system on passengers can help city councils and transit agencies to know which investments to prioritize given their limited budget.

Performing the City: Space, Movement, and Memory in O Ben’Groes at Droed Amser

Abstract In considering some of the aspects that are brought to the site-specific process, this article explores how theatre renegotiates patterns of intraurban movement, enacting complex approaches to space and memory. The focus is on O Ben’Groes at Droed Amser, a Theatr Genedlaethol Cymru and National Theatre Wales production, created in collaboration with BBC Cymru Wales and BBC Arts in 2020 as part of Theatr Genedlaethol Cymru’s new programme in response to the COVID-19 emergency and the challenge of creating original dramatic work during lockdown. By allowing virtual audiences to join author and poet Karen Owen on a bus journey from her home and the street where she grew up to Bangor city centre, the production articulated the experience of the city in terms of individual and collective memory, bringing together issues of performance, representation, history, and heritage to reveal alternative layers to the reality of the urban landscape. Memory, I argue, emerged from this production as a performative construct open to renegotiation through a range of present relationships to landscape. In addition to this, the production also offered an alternative to the privileged figure of the walker, performing a subversion of codified patterns of movement.

DEVELOPMENT OF AN ONLINE AND TRAIN BUS TICKET RESERVATION SYSTEM FOR A TRANSPORTATION SERVICE INMUMBAI (QUICK-BT)

The use of bus traveling is a large growing business in India and other countries; the manual use of bus reservation is presently very strenuous and also consumes a lot of time by having to stay on a long queue. For this reason, an efficient system is to be proposed in this paper to ease the issue of bus reservation amongst indigenes within the country. The system is a web – based application that allows visitors to check bus availability, buy and pay bus ticket online. In order to achieve the design, Bombay Electric Supply & Transport (BEST) was chosen as a case study because of its strategic importance. Structured Systems Analysis and Design Methodology (SSADM) will be adopted. In this paper, the proposed bus reservation system was developed using Extensible Hypertext Markup Language (XHTML), PHP Hypertext Preprocessor (PHP), Structure Query Language (SQL), Ajax, Cascading Style Sheet (CSS), and JavaScript. This document gives formatting instructions for authors

Is It Possible to Compete With Car Use? How Buses Can Facilitate Sustainable Transport

The need to prioritise the development of bus transport has attracted widespread attention in the literature. This study aims to investigate how buses can be used to facilitate a sustainable transport system, using Heze, in China, as a case study. Our results show that older people, unemployed residents, and those whose points of departure or arrival are within the city centre are more likely to travel by bus. In addition, compared to other travel modes, travel by bus tends to become more popular as travel time and distance increase. We predict the probabilities of people using buses for journeys of different travel times and over varying distances and rank them in order. The results suggest that bus travel could potentially replace car travel when the travel time is between 15 and 30 minutes or the travel distance is more than 9 km. In terms of policy implications, governments and planners should pay more attention to creating additional bus lanes, extending the bus network and its infrastructure, optimising bus-related facilities and services, particularly for older adults, and increasing the punctuality and reliability of bus travel.

Same Network, Same Access to Urban Opportunities? Accessibility Via Public Transportation for Wheelchair Users

Public transport plays a fundamental role in providing access to urban opportunities. People with mobility restrictions face greater obstacles than other members of society. This article seeks to explore the obstacles faced by wheelchair users in Montevideo, Uruguay. To do so, we designed a set of trips to actual destinations for five types of activities to compare time costs between wheelchair users and people without mobility restrictions. We estimated time costs for sidewalk segments, waiting time, onboard bus travel time, and coupling time (i.e., idle time due to the lack of bus provision closer to the activity starting times) and found that, relative to people without mobility restrictions, each of these transit components poses high costs for wheelchair users. From a policymaking perspective, our findings point out the importance of expanding universal design in public transport. They also call attention to other factors that explain travel time such as sidewalks segments and the temporal organization of urban activities that may turn into schedule mismatches.