Monash University, Institute of Transport Studies: World Transit Research (WTR)
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The real-time dynamic online feeder service with a maximum headway at mandatory stops
No full textOn the one hand, fully flexible demand-responsive feeder services efficiently tailor their service to passengers\u27 needs. Traditional services, on the other hand, offer predictability and easier cost control. This paper considers a semi-flexible feeder service that combines positive characteristics of both traditional and fully flexible services. There are two types of bus stops in this service. Mandatory bus stops have a maximum allowable headway for bus departures. Optional stops are only visited when there is demand for transportation nearby. When new passenger requests arrive, the performance of this feeder service is optimised in real time. A metaheuristic with two phases is developed to optimise the service. The dynamic optimisation method is compared to a model that optimises the service when all requests are known beforehand. The results show that the dynamic method has an average gap of 6.5% with respect to the static model and an average acceptance rate of 95.1%. A case study in the city of Antwerp shows that, when compared to existing transit options in the region, this feeder service can increase the service quality by 31.6% when enough resources are available
Data aggregation impacts on built environment-mode share models around public transit stations
No full textThis study examines how data aggregation influences the relationship between the built environment (BE) and mode share around 2,794 rail and BRT stations in the United States, using both inferential and machine learning methods. The results indicate that data aggregation impacts the outcomes of BE-mode share models, regardless of the data analysis approach. Models using network buffers are less affected by data aggregation compared to those using circular buffers, Thiessen polygons, or administrative boundaries (block groups). In addition, the optimal buffer sizes for capturing BE effects and minimizing sensitivity to data aggregation for active and public transit modes are 800 meters for BRT stations and 1000 meters for rail stations, while 1200 meters is effective for private vehicle mode share at both rail and BRT stations. Furthermore, key BE features in commuting mode share models—such as employment density, jobs per household, intersection density, residential density, distance from the central business district, job accessibility (active), and regional population density—remain robust against data aggregation. We recommend that urban and transportation planners account for aggregation biases and apply multiple methods when evaluating BE\u27s impact on mode share around public transit stations to inform more effective policy recommendations
A tour-based mode choice model accommodating the influence of attitudes, perceptions, and inter- and intra-household interactions
No full textThe paper examines the influences of attitude and perceptions on mode choice decisions while accounting for household interactions. A nested ICLVmodel is estimated, incorporating six types of tour typology at the upper level, and the lower level considers four modes (active, PT, MTW, and car) under each tour type. The formulation of tour typologies, consist of a combination of activity types (maintenance, discretionary, and a mix of both these activities) and ‘with-whom’ travel arrangements (household members and non-household members), is an important contribution of the study. Three latent constructs—green lifestyle, perceived residential neighborhood, and safety consciousness—extracted from 10 measurement items are integrated into the nested framework to account for the taste heterogeneity arising from variations in the perceptions and attitudes of decision-makers. This model is estimated at the household level by considering the activity-travel diary data of Bhubaneswar city, comprising 858 households, 1454 adult individuals, and 2214 joint tours. The tour typologies reveal that intra-household interactions are more pronounced than inter-household interactions involving non-family members. The results from the structural model of the ICLV framework indicate that household socio-demographics and built environment variables significantly influence the attitudes and perceptions of adult household members. With the inclusion of latent factors in the nested ICLV model estimation, a substantial part of the intrinsic taste (or distaste) variability was captured that was previously ascribed to alternative specific constants. Additionally, the study contributed to the literature by deriving distinct values of travel time savings for PT (₹19.978/hr.), MTW (₹30.687/hr.), and car (₹39.635/hr.) for different tour typologies. A sensitivity analysis of selected control variables is carried out, and policy interventions from a broad viewpoint are also discussed
Evidence-based transport policy analysis driven by agent-based simulation: the case of mobility in Ústí nad Labem
No full textThere is a raise in public awareness on environmental and health issues in recent years, therefore many municipalities changed their transport policy direction to become more sustainable, especially active mobility based. This study makes use of an activity-based demand model to simulate urban mobility and policies for sustainable transport modes in the Usti nad Labem district using an agent-based model simulator driven by a co-evolutionary algorithm. Two policy scenarios were created by considering the transport literature and analyzing the characteristics and behaviors of citizens as well as the properties of the study area. Three scenarios—the actual situation, a cycleway-infrastructure case, and a bus priority case—were simulated for the study area with MATSim software. Both policy scenarios resulted in a decrease in car usage, with a higher drop seen in the cycleway-infrastructure scenario. 9.11% higher public transport ridership and 2.45% more of public transport modal share are observed in the bus priority compared to the actual situation, however the car-related emissions did not decrease. 6.36% more of cycling modal share was also noticed in the cycleway-infrastructure scenario which, the transport modal shift is enhanced by 2.6 more times than in the bus priority scenario. Car driving hours were significantly reduced in the cycleway scenario (5535 h less in a day) where 445.3 tons of car-related CO2 emissions would be saved annually, therefore environmental benefits of cycling modal share increase in the study area is undoubtable in long-term
Exploring the travel behavioral differences for the elderly mobility on public transit
No full textDeveloping an integrated transportation system has required strategies to improve mobility in public transportation networks. This study aims to construct a route choice model incorporating heterogeneous travel behaviors and suggest policy improvements considering travel behavioral characteristics for the elderly in transportation planning. A stated preference survey has been established to explore the travel behaviors on public transit. The behavioral differences of elderly travelers are compared with young adult travelers by the parameters of travel time attributes. Travel time multipliers are developed to compare the time impedance for the travels on public transit using the concept of willingness to pay. Travelers are reluctant to increase the transfer time for all types, resulting in multipliers ranging from 1.91 to 2.11. The results provide the implications of transport policy for the elderly considering a convenient transfer on the integrated transit system in an aging society
Resilience enhancement of multi-modal public transportation system via electric bus network redesign
No full textThe multi-modal public transportation system incorporating the electric bus network and the metro network plays a crucial role in meeting the daily transportation demands in urban areas. However, the inadequate connectivity between the electric bus network and the metro network has resulted in poor resilience of the multi-modal public transportation system. When disruptions occur at metro links or metro stations, stranded passengers cannot be rapidly evacuated through bus lines. Therefore, operators need to redesign the multi-modal public transportation system to enhance the integration between the electric bus network and the metro network. Since it is challenging to modify the fixed metro network, we thus focus on introducing redesign plans for the electric bus network, enabling the multi-modal public transportation system to exhibit the desired resilience in scenarios of disruptions. This paper proposes a two-level framework integrating electric bus network redesign at the tactical level and resource deployment at the planning level. For the redesign problem at the tactical level, this paper designs a tailored branch-and-price algorithm to generate high-quality redesign solutions for the electric bus network. For the resource deployment problem at the planning level, this paper determines the locations of charging facilities and the number of electric buses based on the redesigned electric bus network, considering uncertain passenger demands and metro capacities. We propose a two-layer robust optimization model for the resource deployment problem and develop a tailored column-and-constraint generation algorithm to solve it. Finally, this paper tests the performance of the developed models and algorithms on a set of instances in Beijing. The impact of the uncertainty budget, the number of electric buses, bus capacity, and charging time of electric buses on the system performance is discussed
Comparing the efficiency of urban bus systems in Brazil, France, Spain and United States using social, financial, and environmental indicators
No full textAnalyzing efficiency is vital for public transport, given its significant resource consumption and operation in contexts with limited competition. Although the literature has been studying the efficiency of transport systems for a while, the number of studies that compare public transport internationally still needs to be improved. Research indicates that varying political and economic capacities across countries pose considerable challenges to transitioning towards more sustainable mobility. This issue is further exacerbated by the prominent role of subnational governments in public transport governance, as they dispose of fewer resources than their national counterparts. This study introduces an international methodology for evaluating the efficiency of urban bus systems in 50 cities across Brazil, France, Spain, and the USA. The systems were further categorized by population size. The methodology utilizes crew, energy consumption, fleet, CO2 emissions, and urban population as inputs, while fare revenues, catchment area, and ridership serve as outputs. Data Envelopment Analysis (DEA) was applied to the sample across various scenarios. European systems demonstrated the highest efficiencies. Large European and non-large Brazilian systems were the most resilient though different regions displayed sensitivity to distinct metrics. The proposed methodology offers a comprehensive framework for assessing urban bus network efficiency internationally
An importance-performance analysis of public transport to the university campus based on best-worst scaling
No full textUniversity campuses represent important transport attraction poles in cities due to the large number of students, faculty and administrative staff who commute to the campus daily. The campus location can significantly increase traffic around the area, especially during the class entry and exit times. Therefore, public transport systems are essential to facilitate access to the university campus worldwide, especially for students. This study aims to evaluate the level of importance and satisfaction with factors that affect public transport use among university students. In this context, a best-worst scaling experimental design is used to carry out an important performance analysis (IPA) of public transport services to university campuses in Gran Canaria by estimating a Mixed Logit model. Thus, it will be possible to determine what attributes should be prioritised when implementing policies for improving these services. The results showed that public transport managers and university authorities should primarily focus on providing direct services and improving punctuality and bus frequency. Our results also provide valuable insights into the search for the best policies that match students’ transport mobility preferences with the service provision
Exploring the factors shaping attitudes and intentions towards automated buses: Empirical evidence from Northeast England
No full textThis paper presents an insightful journey into understanding how travellers in the Northeast England perceive and interact with both conventional and emerging automated bus services. Employing a comprehensive methodology, our research scrutinizes data collected from 417 regional respondents via online questionnaires, integrating a blend of quantitative, qualitative, and spatial data points. This approach not only uncovers nuanced attitudes towards public transportation but also sheds light on the potential implications and acceptance of automated bus (AB) services, a fundamental element in shaping the future of urban mobility. The narrative aimed at (i) identifying present socio-demographic clusters and their travel behaviour, (ii) analysing perceptions regarding public transport with an emphasis on bus services, (iii) discovering attitudes towards AB systems and (iv) establishing the likelihood of a travel shift towards ABs.
The quantitative analysis applied Multiple Correspondence Analysis, unveiling five distinct socio-demographic clusters: (1) full-time employed, car-dependent individuals; (2) flexibly working individuals with mixed travel modes; (3) retired, car-dependent persons; (4) unemployed individuals primarily relying on walking and bus services; and (5) employed students utilizing various public transport and active travel modes. Furthermore, Categorical Principal Component Analysis revealed four key attitudinal components influencing bus service perceptions: (a) safety, quality, and comfort; (b) accessibility and availability; (c) cost and reliability; and (d) punctuality and preferences for alternatives. The qualitative dimension covered content and sentiment analysis on responses to open-ended questions about automated buses. This analysis highlighted mixed sentiments, with 56 % positive and 44 % negative mentions. Key connotations with automated buses included expectations of reduced accidents and safer roads, enhanced reliability and frequency of services, potential job losses, diminished social interaction, and concerns over personal security. The study culminates in a spatial analysis, synthesizing the socio-demographic clusters, attitudinal components, and a comparative assessment of traditional versus automated bus services
Evaluating sustainable urban mobility for public transit incorporating the geospatial modeling approach
No full textCities have established public transit infrastructures to provide equitable services to every citizen at a low cost, thus minimizing traffic congestion. Public transportation facilities, including bus stops, urban railway stations, and terminals, provide physical convenience to passengers. Considering economic efficiency, the location selection of public transport facilities causes an imbalance in public transit accessibility within the city. Therefore, to alleviate spatial imbalance, it is necessary to devise a public transportation system evaluation method. This study uses revealed travel data to develop a competitiveness index for sustainable urban mobility in public transit. The developed competitiveness index considers two aspects: (1) mobility factors referring to in-vehicle, transfer, and waiting times, and (2) travel demand and economic factors of travel costs. Square cells of 500 m × 500 m were used to apply the geographical explanatory variables in Seoul. The developed competitiveness index ranged from −22.7 to 23.25, thus confirming the difference in sustainable mobility services between the urban center and outskirts. Notably, a spatial cell with subway stations has a high competitiveness index because subway facilities are the main factors that increase the competitiveness of public transit. Multiscale geographically weighted regression, which identifies interactions through spatial dependence and heterogeneity, is employed to analyze the causal relationship between spatial mode competitiveness and socioeconomic characteristics. The developed index is expected to contribute to the establishment of public transportation policies and systems to alleviate imbalances by identifying areas vulnerable to public transit services