Monash University, Institute of Transport Studies: World Transit Research (WTR)
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Service quality attributes affecting the satisfaction of KTM Komuter services
No full textThis research aims to evaluate the service quality within the commuter system of Klang Valley, Malaysia, specifically the KTM Komuter, by constructing empirical statistical models known as KOMIQUAL models. The primary objective is to identify and quantify the significance or impact of various variables on commuter quality and service, focusing on the Port Klang-Sentul route in the year 2010. The empirical investigation conducted at fourteen commuter stations in Klang Valley was prompted by concerns about severe overcrowding of passengers on rail stations, platforms, and within rail coaches. In addition, some major stations were selected because they faced high demand for passengers. Valid questionnaire responses were statistically analyzed using factor analysis and the Structural Equation Modeling-Analysis of Moment Structures (SEM-AMOS) Graphics and software. Findings showed that the major service characteristics like parking facilities, train efficiency, people services, and space comfort had the highest positive effect on service quality. This research would help the operator to monitor and improve the service
Exploring hierarchy shift of travelers’ public transport dependence using an improved Apriori algorithm
No full textSpecial external environments will lead to significant changes in the use behavior and dependence degree of different PT travellers, but it is difficult to analyze the mechanism of the hierarchy shift of travelers’ public transportation (PT) dependence. Exploring travelers’ dependence on PT is conducive to understanding individuals’ travel choice behavior and optimizing PT operation organizations. Developing methods for analyzing the internal causal relationship between travelers’ dependence on PT and the key influencing factors under the special condition is an issue. Therefore, the individual travel chains are constructed by associating and matching the multisource PT big data and travel survey data. Thereafter, the K-means algorithm and an improved Apriori algorithm are developed to mine the frequent association rules of groups, and a framework of cross-hierarchy policy implications is derived based on the differences in association rules. Finally, the stated preference survey method is used to measure the effectiveness of the policies
Estimation of the anticipation effects of the metro project on real estate dynamics in Bogotá, Colombia
No full textStudies of the impacts of rail-based mass transit systems on land values and real estate prices are scarce in the Colombian context. Most studies have focused on estimating the impacts of bus rapid transit systems (BRT), mainly in Bogotá. There is an emerging literature on rail-based systems impacts on urban development and land values in Medellín, Colombia, while there is also an emerging interest regarding the effects of the announcements of the two metro projects of Bogotá in the city’s urban spatial structure. This paper develops a quasi-experimental research design looking at the anticipatory effects of the two lines of the Bogota Metro program on real estate market dynamics between 2007 and 2023. We used databases generated by the private sector with new housing developments including housing unit attributes and we estimated spatial variables and urban attributes associated with the location of each real estate development project. Through hedonic price models with control variables that incorporate attributes at different scales, our study estimates the effects of the Bogota Metro Line 1 project (in construction since 2021) on prices per square meter of real estate development projects over time. Results of the analysis suggest that the regulations implemented by the city, establishing an 800-meter impact area along Line 1, have had positive effects on real estate market prices after 2016, while results found no changes on real estate development dynamics in terms of prices per square meter due to the announcements of the planned second line of the metro project. We also included statistical analysis using isochrones based on walking distances to future metro stations. We found that the positive effects are taking place in all isochrones for the first line, while there are differences in the case of the second line of the metro project. Based on these findings, we provide guidelines for future research including public policy recommendations for the local and national government regarding value capture opportunities associated with the announcement of large-scale rail based urban transport projects
Policy implications of the transit metropolis project: A quasi-natural experiment from China
No full textThe Chinese government has initiated the Transit Metropolis project, aimed at developing a transit-oriented urban transportation system that progressively enhances the utilization of public transit and encourages private car users to shift towards public transit. Using panel data from 221 cities from 2009 to 2018, we employed a multi-period propensity score matching-differences in differences approach to examine the effects of this project on public transit usage and private car ownership. We utilized the status of a city as a coastal city as an instrumental variable for the Transit Metropolis project to conduct an endogeneity test, ultimately finding no evidence of endogeneity. Even when accounting for competitive policies such as the low-carbon city policy, the results remained consistent, confirming the robustness. The findings suggest that the project has effectively increased public transit use without significantly decreasing private car ownership. However, these impacts vary geographically. Specifically, in Eastern region of China, the project significantly enhanced public transit usage, whereas no comparable significant effect was observed in the Central & Western regions. Regarding private car ownership, the project did not have significant effects in either the Eastern, or the Central & Western regions. These insights provide a reference for further implementing Public Transit Priority policies, help enhance the competitiveness of public transit, and promote the development of transit-oriented urban transportation structures
Strategies to Optimize the Deployment of Roadway Maintenance Machines for Overnight Maintenance in Urban Rail Systems
No full textThis research investigates the effectiveness of several strategies to deploy roadway maintenance machines (RMMs) in preparation for overnight maintenance in rapid transit systems. Owing to the short windows of time available for maintenance activities in the overnight period (i.e., when revenue service is suspended), efficient deployment of RMMs is an important aspect of ensuring adequate productive time for crews at work locations. Four deployment strategies are investigated: optimizing the long-term yard storage locations of RMMs; optimizing the assignment of RMMs to work zones; optimizing the use of nonrevenue locations within the network to “preposition” RMMs closer to their work zones; and optimizing the routing and scheduling of RMMs through the network to reach the work zones. The strategies have been tested using data from the Washington Metropolitan Area Transit Authority. The results indicated that the proposed strategies reduced the time needed for RMM deployment. In the case of prepositioning, the median prepositioned RMM was deployed 23 min earlier than in the baseline (i.e., routing and scheduling alone) scenario, and the median RMM receiving a new yard storage location was deployed 16 min earlier. This was achieved without widespread negative impacts to RMMs that could not benefit from the proposed strategies for operational reasons. The results also demonstrated the potential of the routing and scheduling model as a tool to evaluate the deployment time impacts of distance-minimizing strategies, considering factors such as conflicts between RMMs and the availability of tracks to avoid disruptions to revenue service
Household activity pattern problem with automated vehicle-enabled intermodal trips
No full textDriverless or fully automated vehicles (AVs) are expected to fundamentally change how individuals and households travel and how vehicles use roadway infrastructure. The first goal of this study is to develop a modeling framework of activity-constrained household travel in a future multi-modal network with private AVs, shared-use AVs, transit, and intermodal AV-transit travel options. The second goal is to analyze the potential impacts of AVs—including intermodal AV-transit travel—on (a) household-level travel behavior, (b) household travel costs, (c) demand for transport modes, including transit, and (d) vehicle kilometers traveled or VKT. To meet the first goal, we propose and formulate the Household Activity Pattern Problem with AV-enabled Intermodal Trips (HAPP-AV-IT) that incorporates AV deadheading and intermodal AV-transit trips. The modeling framework extends prior HAPP-based formulations that model household-level travel decisions as vehicle (and person) routing and scheduling problems, similar to the pickup and delivery problem with time-windows. To meet the second goal, we apply the HAPP-AV-IT to two case studies and conduct many computational experiments. We use synthetic activity location data for synthetic households and a fictitious medium-size network with a road network, transit network, residential locations, activity locations, and parking locations. The computational results illustrate (a) the critical role that household AV ownership plays in terms of household travel decisions, modal demand, and VKT, (b) that with AVs, deadheading accounts for 30–40 % of vehicle operating distances, (c) that around 10 % of households in the study region benefit from AV-based intermodal trips, and (d) that those 10 % of households see 5 % reductions in household travel costs and 25 % reductions in VKT on average in the most transit friendly scenario. This last finding suggests that intermodal AV-transit trips may exist in a driverless vehicle future, and therefore, transit agencies and transportation planners should consider how to serve this market. We also propose and test a simple heuristic algorithm that quickly solves HAPP-AV-IT problem instances
A flexible non-normal random coefficient multinomial probit model: Application to investigating commuter\u27s mode choice behavior in a developing economy context
No full textThere is growing interest in employing non-normal parameter distributions on covariates to account for random taste heterogeneity in multinomial choice models. In this study, we propose a flexible, computationally tractable, structurally simple, and parsimonious-in-specification random coefficients multinomial probit (MNP) model that can accommodate non-normality in the random coefficients. Our proposed methodology subsumes the normally distributed random coefficient MNP model as a special case, thus eliminating the need to a priori decide on the distributional assumption for each coefficient. The approach employs an implicit Gaussian copula to combine the univariate coefficient distributions into a multivariate distribution with a flexible dependence structure. Using our new flexible MNP framework, we investigate the commute mode choice behavior for workers in the city of Bengaluru, a metropolitan city in southern India. Results from our analysis indicate that sociodemographic variables, commute characteristics, and mode-related attributes significantly impact the commute mode choice decision. Importantly, our results indicate the presence of unobserved taste heterogeneity in the sensitivities to the travel time and travel cost variables; moreover, the distribution of the travel time coefficient is found to be significantly non-normal. In terms of data fit, our proposed model statistically outperforms the traditional MNP model as well as an MNP model that imposes normality on the travel time coefficient. The pitfalls of ignoring non-normality in the distribution of parameters are also discussed, as are several policies to promote a shift from private modes of transportation to more sustainable public transportation/walk modes
A risk-averse two-stage stochastic programming approach for backup rolling stock allocation and metro train rescheduling under uncertain disturbances
No full textDisturbances occur inevitably during daily operations of the metro system, leading to train delays and low service quality. Different from common deterministic reactive train rescheduling frameworks, taking the inherent uncertain characteristic of disturbance into account, this paper formulates a two-stage stochastic programming model to address the integration of proactive backup rolling stock allocation and reactive train rescheduling. Specifically, the backup rolling stock allocation plan is optimized in the first stage, while the train timetable and rolling stock circulation are rescheduled under different disturbance realizations in the second stage. The objective is to achieve a balance between allocation costs and negative disturbance impacts, which is evaluated by the mean-conditional value-at-risk criterion on account of the risk-averse attitude of train dispatchers. For computational tractability, the proposed model is reformulated as an equivalent mixed-integer linear programming (MILP) model. To improve computational efficiency, an innovative solution framework is designed. The integer L-shaped method is used to decompose the MILP into a master problem and a series of subproblems, with three acceleration techniques introduced to expedite the subproblem-solving process. Finally, numerical experiments are carried out based on the Beijing Batong Metro Line to verify the performance of the proposed mathematical model and solution framework. The results indicate that the proposed method outperforms benchmarks. Furthermore, comprehensive analysis is conducted on the effects of different parameter settings to provide some managerial insights for dispatchers
Workshop 7b report: Sustainable transport systems designed to meet the needs of both users and residents
No full textThe provision of public transport should address not only users\u27 but also non-users’ needs which span beyond traditional accessibility to cover affordability, reliability, sustainability, safety, health, and ultimately equity. Budget constraints often means that trade-offs among these aspects of a transport system are inevitable. While trade-offs are often made based on traditional cost benefit analysis, economists and researchers increasingly account for social and environmental impacts of public transport provision. Workshop 7b of the 18th International Conference on Competition and Ownership in Land Passenger Transport set out to address the factors that contribute to decision-making processes and the challenges of implementing new approaches. It included ten papers which report evidence about transport poverty, accessibility index, value of travel time saving for children, personal safety on public transport, social inclusion, community building, and service time extension for special events. The workshop discussed what factors should be considered in transport service designs to make transport systems more equitable and inclusive for users and non-users and what implications does transport service design and accessibility have for community building. Drawing on these discussions, the workshop developed a set of research and policy recommendations designed to cater diverse users and needs
A multi-period asymmetric transit frequency design problem
No full textTransit frequency design is critical in determining the performance of public transit services. In the literature, single-period frequency design is often considered but ignores the demand variation over time of day. Moreover, in high-demand bus networks, the demand patterns are asymmetric in both directions of some bus routes. This study investigates a bus operation strategy to address these two issues. In this strategy, for each route, a class of buses serves both directions while the other class only serves one direction with high travel demand, leading to the two directions having different frequencies. A bilevel optimization problem is formulated for this strategy. The upper level problem is a multi-period asymmetric transit frequency design problem, which aims to determine the route frequencies of different classes of buses associated with each period to maximize the operating profit or social welfare. This upper level problem also considers deadhead trips between the bus depot and terminals or between terminals of different routes across periods. The lower level problem is a schedule-based user equilibrium transit assignment problem, taking elastic demand, the common line choice of passengers, and capacity constraints into account. A hybrid algorithm combining an enhanced artificial bee colony algorithm with the method of successive averages is proposed to tackle the bilevel optimization problem and then applied to the study of the Tin Shui Wai bus network to demonstrate the model properties. The effectiveness of the proposed algorithm is also examined. The results indicate that the proposed algorithm can produce better solutions compared with the modified hybrid genetic algorithm. Moreover, the proposed multi-period asymmetric design outperforms the existing design, which can achieve less passenger travel time and greater demand satisfaction, operating profit, and social welfare