Monash University, Institute of Transport Studies: World Transit Research (WTR)
Not a member yet
11112 research outputs found
Sort by
Framework for the Analysis and Enhancement of the Accessibility of Large-Scale Urban Transit Networks: A Data-Driven Study for the City of Lyon, France
No full textAccessibility to a fixed point of interest is a powerful indicator for quantifying the strengths and weaknesses of a multimodal pedestrian and transit network. However, it is difficult to predict the impact on accessibility deriving from the insertion of a new infrastructure and its contribution to the urban landscape. This paper uses graph science and multisource open data to implement a tool for studying accessibility in combination with several network performance indicators. The tool allows determination of whether a transit infrastructure project can be beneficial for its potential users. In this paper, we propose to compute gravity-based accessibility, temporally bounded by an isochrone . We assume that the user always favors the shortest route, her rationality conditioned by real-time applications provided by network operators. By the proposed approach, the impacts on accessibility deriving from the construction of a new infrastructure, such as a new transit line, can be effectively quantified and the actors of urban planning can visually evaluate the consequences of their projects to make more informed decisions
Toolkit for the Assessment of Safety at Bus Stops
No full textSafety at bus stops is a major concern of transit agencies. This research aimed to develop a data-driven method for estimating bus stop safety scores that will assist transit agencies in ranking and prioritizing bus stops for improvement considerations. This study presents a bus stop scoring methodology that uses a data-driven approach based on multiple data sources. The methodology was developed using six criteria: bus stop characteristics inventory, roadway characteristics inventory (RCI), land use and demographics, pedestrian crash frequency, annual average daily traffic, and annual ridership. Crash data were collected from SignalFour Analytics, and roadway characteristics data were retrieved from the Florida Department of Transportation RCI database. The Florida Geographic Data Library was used for retrieving census and land use data, while the Florida Transit Information System was employed to extract information on transit stops. A data-driven method was used to develop a priority list for improvements among the selected bus stops. The methodology was implemented in a case study including three transit agencies: Hillsborough Area Regional Transit Authority, Jacksonville Transportation Authority, and Miami-Dade Transit. A bus stop priority list was generated for each agency, with the highest-ranking bus stop location having the greatest need for safety improvements. Based on the analysis, safety measures that could improve safety at the highest-ranking bus stop locations include: installing a shelter, installing pedestrian safety features, conducting pedestrian safety outreach programs, and/or conducting further site investigation
Creating most needed customized bus services: A collaborative analysis of user-route dynamics
No full textCustomized buses (CB) are emerging mobility services as a complement to conventional transit. However, knowledge remains limited regarding the interplay between supply and demand dynamics in CB systems. Utilizing the Shanghai Yidong CB services as a case, this study develops a multi-task deep-learning framework to collaboratively analyze the homogeneity and heterogeneity in the influencing mechanisms of CB users and route service survival time. Key findings include: 1) Behavioral inertia and built environment significantly influence both supply and demand dynamics; 2) The built environment’s impacts vary, with destination areas being crucial for route services and origin areas for users; 3) For route services, the entropy and intensity of the built environment are critical, while specific built environments are more crucial for users; and 4) a synergistic analysis for three specific categories of routes, the University-oriented, Transportation Hub- oriented, and Economic Center-oriented CB routes, helps formulate targeted strategies for transits’ sustainable development
Equity of access to rail services by complementary motorized and active modes
No full textThe public transport system only serves its true purpose when people living in the region have adequate and direct access to its services. Rail systems, including light rail, metro, urban, suburban, and long-distance trains, are the key fixed structural elements of any transport system that provide faster access for both shorter and longer trips and are regarded as a more efficient and environmentally friendly option to move a larger number of passengers than road transport. However, it is not feasible in terms of investment and financial sustainability to provide rail services everywhere, especially in rural zones. Thus, connectivity with all the other available (active and motorized) modes is crucial to improve accessibility and reduce inequities. In this paper, we developed a methodology to quantify and contrast the access to the existing rail services between zones of a metropolitan area and corresponding inequities. We considered not only the usually analyzed active modes, pertaining to a certain level of proximity to the rail stations, but also motorized modes (e.g., car and bus) that can enable the connection to rail services where these are not easily accessible by walking or cycling. First, the accessibility to the existing rail stations is quantified using place-based gravity measures, considering the travel times for the complementary modes with and without incorporating the stations\u27 attractiveness, measured by service frequency. Second, the global inequity levels of the spatial distribution of the rail network in the metropolitan area are evaluated using the Gini index. Third, local inequities, at a scale of small census blocks, are measured considering the access (supply) and the population (potential demand). While the local-scale analysis allows to identify the most unfavored zones, the global inequities by complementary modes aim to inform targeted strategies to improve the integration of those modes with rail services. The methodology was applied to the Metropolitan Area of Porto, Portugal, where we observed a non-uniform distribution of rail services and a decrease in access towards the periphery. However, considering the population living in each zone, both underserved and well-served zones are mostly present in the most populated/central areas
Obstacle Detection Method of Underground Electric Locomotive Rail Based on Instance Segmentation
No full textReal-time and accurate obstacle detection is a vital technology for electric locomotives, especially as driverless vehicles are introduced. A method of obstacle detection for underground electric locomotive rail based on instance segmentation is developed to solve the problems of misdetection and missing detection, low detection accuracy, and slow detection speed of rail obstacles. The method of locating the track mask, demarcating the effective driving boundary, expanding the track mask, and forming the effective driving area is adopted to verify whether the target is an obstacle based on whether the target is located in the effective driving area, to avoid the problem of misdetection and missing detection of the target obstacle. The YOLACT++ (You Only Look At CoefficienTs) model is improved, and path augmentation and target classification loss function replacement strategies are adopted to enhance the model’s ability to detect target details and increase the accuracy of target segmentation. Compared with traditional image processing, this method can detect both straight rail and turnout. The mean average precision of boundary box mAP0.5(box) and mask mAP0.5(mask) of the improved YOLACT++ model reaches 98.52% and 98.55%, which is higher than that of the YOLACT++ model, and the detection frame rate reaches 21.9 frames per second
Thresholding-based cellular automata for transportation network derived future urban growth patterns in a peri-urban area
No full textThe present study uses the standalone Cellular Automata (CA) model to predict the transportation network-derived future urban growth patterns of a rapidly expanding peri-urban area in the Mumbai Metropolitan Region. The Landsat satellite images of 1999, 2009, and 2019 are used to deduce the study region\u27s land use/land cover (LULC) patterns. The road networks, suburban railway stations and proposed metro stations are considered the primary drivers of urban growth. The classification results show an increase in built-up area by 48 km2 (104%) from 1999 to 2019, decreasing the open land and vegetation by 21%. The fine-tuned CA gives an area under the relative operating characteristic curve of 0.907, locational accuracy \u3e72% and quantitative accuracy of \u3e89%, indicating a good model fit. The calibrated model is used to simulate the urban growth of 2029 for two scenarios: first a no-metro case and second considering the proposed metro\u27s impact. While the built-up area increases by 28%–120 km2 for the no-metro case, including the proposed metro increases the built-up prediction to 133 km2. The enhanced built-up highlights the role of metro development in triggering significant growth in the region. Although the present study uses Kalyan and contiguous area, the general structure of model and its ability to function with a limited data makes it adaptable across diverse regions at different stages of development worldwide. Such an urban growth model can serve as a practical tool for planners in prompt decision-making
Broad support vs. deep opposition: The politics of bus rapid transit in low- and middle-income countries
No full textIt is no secret that decision-making around mass transit infrastructure can be highly political. Transport policy research, however, has tended to view political dynamics mainly as barriers. There is a need to better understand how and under what conditions political interests and institutions can enable mass transit projects, especially in cities which are not yet locked into car-centric transport systems. This paper addresses this gap with new inductive evidence from 32 expert interviews on the politics of bus rapid transit (BRT) in low- and middle-income countries. It develops two novel analytical frameworks, one on the politics of system adoption and another on the politics of system durability. The first framework highlights how BRT proposals often pitch broad but shallow political support against narrow yet deep political opposition. This renders them inherently contentious. Proposals move forward when their implementation generates political benefits for powerful decisionmakers. The second framework challenges the conventional view that BRT systems prove durable when their operations perform well. Instead, it posits that systems endure when their operations mitigate or adapt to adverse political feedback. The paper offers a novel holistic perspective on how to understand the politics of BRT, and presents a critical intervention in the BRT literature which has tended to focus on isolated political dynamics, such as the need for a local champion or resistance from paratransit operators
Design and analysis of ride-sourcing services with auxiliary autonomous vehicles for transportation hubs in multi-modal transportation systems
No full textAutonomous vehicles (AVs), which can be fully controlled by remote/online operators, could be an extension of ride-sourcing services provided by transportation network companies (TNCs). Meanwhile, substitutive and complementary relationships between ride-sourcing and public transit could also help TNCs increase their profit under certain strategies. Unlike previous studies that generally ignored either AVs or interactions between public transit and ride-sourcing, we introduce AV-involved operational strategies into a multi-modal system. In this paper, we focus on transportation hubs in an urban area and let the TNC assign AVs to these hubs for serving only within that particular hub at a differentiated fare; meanwhile, passengers could choose among AVs, human-driven vehicles (HVs), combined modes with public transit and AVs or HVs, or other travel modes to fulfill their travel needs. We develop a mathematical model to investigate the impacts of such an operational strategy, and formulate an optimisation problem to maximise the TNC\u27s profit and minimise total waiting time simultaneously by adjusting AV fare and fleet size. We further propose a comprehensive modeling framework with the analytical model, optimisation problem, calibration method, and heuristic algorithm, making it a general approach for different real-world scenarios. Following the framework, we conduct a case study based on real-world datasets of public transit and ride-sourcing services in Hangzhou, China. Different market schemes are analyzed and compared with the currently existing situation. The results demonstrate that by adopting this auxiliary-AV-oriented operational strategy, the TNC\u27s profit and public transit ridership can both be increased, and passengers could enjoy a shorter waiting time for HV ride-sourcing trips. Moreover, the TNC is more inclined to allocate more AVs to hubs with large commute needs and uncongested traffic, leading to a high profit for the TNC and a short waiting time for passengers. Societal preferences towards AV trips are also analyzed. The results provide in-depth references for real-world AV-related ride-sourcing operational problems
Behind the wheel: Probing into personality, skills, and driving behavior’s role in bus rapid transit crashes
No full textObjective
Personality traits and driving skills are significantly associated with driving behaviors and crashes. In the case of professional bus drivers, the relationships amongst these variables have not been sufficiently examined in terms of road crashes. Therefore, this study seeks to examine the relationship between personality traits, driving skills, driving behaviors, and crash involvement among Bus Rapid Transit (BRT) drivers. Methods
The study employed a comprehensive data collection strategy involving self-reported questionnaires, including the driver behavior questionnaire, driver skill inventory, and Big Five inventory, alongside Global Positioning System (GPS)-extracted speeding data from a sample of 166 drivers. To explore the relationship between variables, the study utilized the Partial Least Squares Structural Equation Model (PLS-SEM) as the analytical method. Result
The findings reveal that self-reported violations and actual speeding performed by drivers were positively associated with crash involvement, whereas positive driving behavior negatively influences violation, errors, speeding and crash involvement. The study also found that the safety skills were negatively associated with violations, errors, and speeding, while higher perceptual-motor skills were associated with higher instances of speeding violations, resulting to a higher possibility of getting involved in a crash. Finally, the study reveals that certain personality traits (extraversion and neuroticism) were positively associated with violations, errors, and speeding, leading to a higher risk of getting involved in crashes, whereas certain personality traits (conscientiousness and agreeableness) were associated with safe driving. Conclusion
The study findings offer valuable insights into the predictors of crashes among professional BRT drivers, which can be used to enhance driving practices, ensuring the safety of the public. Moreover, these findings provide transportation agencies with better management and decision-making capabilities to implement effective interventions to improve road safety
Modal disparity in commuting efficiency: A comparison across educational worker subgroups in Shanghai
No full textThe majority of modal disparity studies focus on accessibility to jobs and to non-work activities with little attention paid to actual commuting behavior. How modal differences in commuting behavior change when set against the minimum and maximum commutes possible within a fixed urban structure is much less known. In commuting efficiency studies, the mode of commuting flows has not been intersected with socio-economic characteristics. Using the 2015 1 % National Population Sample Survey (NPSS) in Shanghai, we apply the excess commuting framework to fill this research gap by measuring the modal disparity between public transport and cars, in commuting efficiency by education level of workers. Results show that public transport users are less efficient commuters than car users, indicating great capacity exists for optimizing public transportation. However, the modal disparity decreases with increasing educational attainment, because car commuting efficiency is decreasing at a faster rate than for public transport. Based on these findings, urban transportation policy should focus on improving jobs-housing balance of public transport, and building a friendly green travel environment to rectify car-oriented bias in urban spatial structure and narrow the difference between public transport users and car users, especially for the poorly-educated