Monash University, Institute of Transport Studies: World Transit Research (WTR)
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11112 research outputs found
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Exploring sleepiness and stress among London bus drivers: An on-road observational study
No full textBus driver sleepiness is commonplace but often goes unreported within the industry. Whilst past research has begun to shed a light on the prevalence, potential causes, and consequences of bus driver sleepiness, this is often done using self-report methods. This is the first study to investigate sleepiness amongst city bus drivers on-road using a live bus route with drivers’ regular schedules. A total of 16 participants completed two drives of their regular bus route once during an early morning shift and once during a daytime shift whilst physiological and self-report measures of sleep and stress were taken. Prior to these drives, drivers recorded their sleep in a diary and wore an actigraph to obtain objective sleep measures. Results showed that most drivers did not obtain sufficient sleep prior to early morning shifts, and often did not obtain as much sleep as they would need in order to feel rested before work. Sleepiness and stress were observed in both shifts. During early morning shifts sleepiness was likely a result of working during circadian lows and not obtaining enough sleep prior to the shift. In contrast, sleepiness during the daytime shift was likely a result of completing a highly demanding task in complex traffic which not only contributed to fatigue, but also led to increased levels of stress. As well as demonstrating the prevalence of sleepiness amongst bus drivers, these findings show that the causes of sleepiness can be multifaceted and often come about due to a combination of work and personal factors. In addition, the experience of sleepiness is not the same for all drivers, with individual differences in the experience of sleepiness playing a large role. These differences highlight the need for individualised interventions which should be considered by policymakers alongside the combination of causal factors within a larger systems approach
Mode choice modelling of work trips using latent variables for a medium-sized city in India
No full textDecline in the use of public transit by commuters have increased the use of private vehicles, causing higher levels of traffic congestion, accidents, etc. The present study aims to identify major latent attributes influencing the behaviour of government employees working in the study area by using an integrated mode choice model. The unobservable attributes that influence mode selection decisions were analysed using the semantic differential technique and a five-point bipolar adjective scale. Conventional mode choice models and latent variable integrated mode choice models were developed for four different modes. Sensitivity analysis was carried out to assess the impact of significant variables which has revealed that 15% decrease in travel time on public transport could lead to a 17% increase in ridership. This study also identified significant variables that influence mode selection decisions and formulated policies to increase the use of public transport in medium-sized cities
Feasibility study on commercial deployment of automated public transport vehicles in New Zealand
No full textThis research was carried out for NZ Transport Agency Waka Kotahi (NZTA) with the aim of improving our understanding of the ability of automated forms of public transport to complement or substitute public transport on New Zealand’s roads. As technology advances, automated vehicles are emerging in the land-transport system in parts of the world. There is currently limited knowledge and understanding about the deployment of automated vehicles, particularly automated public transport vehicles. Automated vehicles can impact the way people and goods are moved, which in turn can impact on physical infrastructure as well as digital infrastructure requirements. This research has found that whilst technological leaps and progress have been made, automated public transport technology is progressing and a pilot / trial approach would still be required to understand the applicability of automated public transport in the New Zealand context. The review of trials between 2013 and 2020 suggested that Level 4 (or higher) automated systems are not ready to replace conventional public transport at present, but there is potential for automated public transport vehicles to complement existing public transport services. This includes a potential role in the first / last mile, specific uses within university campuses, sports events and tourism destinations, as well as in constrained environments where the highly specific guidance from the automated system could be utilised. With these systems potentially providing different social impacts and different cost structure to the existing public transport systems, an objective and cost-based evaluation was developed to assist with consistent evaluation of such a system in New Zealand
Transit Agency Assessment of Their Capability to Adopt New Mobility Strategies
No full textThis research identified current challenges, constraints and interest in the implementation and management of new mobility services (on-demand and micromobility) for United States transit agencies. Twenty-four semi-structured interviews with employees of transit agencies were conducted, and NVivo, a qualitative analysis software, was used to classify agency involvement, constraints, and challenges with services. The most common constraints and challenges for on-demand services (cited by more than five agencies) were labor shortages, software performance, fare integration, vehicle shortages, and funding. For agencies not offering on-demand services, developing strong backbone networks with fixed-routes was a priority, and cost-effectiveness, service area design, and funding were additional concerns. The top constraints and challenges among transit agencies with respect to micromobility (cited by more than four agencies) included fare integration, obstruction of public space, funding, adequate supporting infrastructure, and development of equitable service. For integrating new mobility services, most transit agencies (14 of 20, 70%) expressed interest in becoming mobility managers, but larger agencies (those with more than 10 million unlinked passenger trips) were split between mobility manager and partner roles. This research suggests that transit agencies have evolved in the new mobility space, but some constraints and challenges still stand in their way. Policy makers and decision makers can help transit agencies by encouraging open-source software development, improving labor contracts, increasing funding opportunities, and coordinating land-use, transportation, and transit planning. Future research should continue investigating barriers to entry for new mobility services and identify how transit agencies can increase coordination with technology and micromobility companies
Evaluating the impact of rail transit network expansion on travel behavior in Shenzhen, China: A causal analysis across different stages of development
No full textResearch regarding the impact of rail transit development on travel behavior has received significant attention in recent decades. Numerous studies have examined the influence of newly established rail lines on travel behavior. However, there is a noticeable lack of studies on how the expansion of a rail transit network alters daily travel behavior. This study addresses this research gap by investigating the travel behavior impacts of the rail transit network expansion in Shenzhen. A machine learning (ML) enhanced difference-in-differences (DID) model is developed to determine the causal effects of enhanced transit accessibility on travel behavior changes. Our findings suggest that enhancements in rail transit accessibility significantly boost rail transit use and decrease travel by private cars and buses. We also discovered that the effects fluctuate at different stages of rail transit network development. These findings bear significant relevance for strategies and policies concerning rail transit development and transport demand management
Managing transit-oriented development: A comparative analysis of expert groups and multi-criteria decision making methods
No full textA key challenge for transport managers and planners in sustainable development is evaluating transit facilities\u27 performance. While Multi-Criteria Decision-Making (MCDM) tools are often used, they can be influenced by experts\u27 subjective biases. This study applies MCDM to assess Mass Rapid Transit (MRT) stations in Jakarta, Indonesia, focusing on Transit-Oriented Development (TOD). The primary goal is to compare stakeholder perspectives and MCDM methods, complemented by a sensitivity analysis and validation with real-world smart card data. The findings reveal significant differences in criteria weighting between Indonesian and non-Indonesian experts, and between academic and non-academic experts, especially in transit connectivity and land use diversity. The study also shows variations in station rankings across different MCDM methods. Sensitivity analysis identifies transit connectivity as the most critical criterion. Simple Additive Weighting (SAW) with linear normalisation aligns well with actual usage data and shows robustness in sensitivity analysis, making it the most reliable method for TOD evaluation. The study highlights the need for continuous TOD performance monitoring and the regular collection of real-world data on ridership and TOD indicators
Air quality improvement at urban bus stops: Optimal air purification placement using CFD
No full textNitrogen dioxide (NO2) levels are often elevated near roadways due to vehicle emissions, while sulfur dioxide (SO2) is predominantly found near petrochemical complexes as a result of industrial activities such as oil refining and chemical manufacturing. Considering the detrimental effects of these emissions on the environment and human health, the optimal placement of air purification systems at two bus stops in Ulsan, a heavily industrialized city in South Korea, was investigated in this study to reduce NO2 and SO2 concentrations. Computational fluid dynamics (CFD) simulations were performed to identify strategic installation locations, resulting in a significant reduction in pollutant levels. The largest impact was noted for the Deokha Market bus stop, whereby the added health risk (AR) decreased by 1.93 % and the exposure reduction effectiveness (ERE), a measure of air purification system efficiency, increased by 13.8 %. Similarly, at the Hyomun Intersection bus stop, placing the system near the sidewalk led to a significant reduction in AR by 1.60 % and an increase in ERE by 11.63 %. Additionally, air purification systems at Ulsan bus stops are expected to reduce NO2 levels by 9.1 ppb, decreasing mortality risk by 1.44 %, saving 7 lives annually, and yielding an economic benefit of 33.06 million USD
A tactical planning framework to integrate paratransit with formal public transport systems
No full textDespite the crucial role of informal paratransit services in mobility systems, their planning and integration with formal public transport systems have received limited attention. We present a novel framework to integrate public transport and paratransit at the tactical planning level. We formulate this integration as a two-step Transit Network Frequency Setting Problem (TNFSP). The first step of TNFSP involves a headway-based network-wide multi-modal transit assignment, followed by an integrated frequency optimisation in the second step. The proposed approach is applied to the network of Visakhapatnam, a medium-sized Indian city with 9 % and 18 % share of paratransit and formal transit. After validating the base model using real-world data, we perform scenario-based analysis to derive the optimal fleet size, network configuration, and frequency of both systems to minimise externalities. Integrated planning and frequency optimization can lead to 50–60 % reduction in travel time and emissions compared to current approach of separately planned systems
A collective incentive strategy to manage ridership rebound and consumer surplus in mass transit systems
No full textThis paper models and analyzes a collective incentive strategy with passenger departure time equilibrium to maximize the total passenger surplus, which could further enhance the sustainability of transit systems in the post-pandemic era. In the proposed collective incentive strategy, passengers with transit passes have dynamic discounts where the discount value depends on the total number of passengers enrolled in the incentive program. A bi-level optimization model is established by considering passengers\u27 demand elasticity and responses to the strategy, which eventually determines the starting time and duration of the collective incentive strategy during the time of the day. We further analyze the properties of the proposed collective incentive model to identify the analytical solutions and performance. Analytical results indicate that there exists a threshold demand elasticity below which the total surplus of commuters with and without transit passes can be improved simultaneously. Properties also show that there could exist multiple local optimal solutions of incentive strategy duration for a given starting time. A case study is conducted with the metro system in Toronto: the results show that the proposed collective incentive strategy could improve both the fare revenues and ridership by 33.31 % and 83.56 %, respectively
Austria’s KlimaTicket: Assessing the short-term impact of a cheap nationwide travel pass on demand
No full textMeasures to reduce transport-related greenhouse gas emissions are of great importance to policy-makers. A recent example is the nationwide KlimaTicket in Austria, a country with a relatively high share of transport-related emissions. The cheap yearly season ticket introduced in October 2021 allows unlimited access to Austria’s public transport network. Using the synthetic control and synthetic difference-in-differences methods, we assess the causal effect of this policy on rail travel demand by constructing a data-driven counterfactual out of European railway companies to mimic the number of passengers of the Austrian Federal Railways (ÖBB) without the KlimaTicket. Overall, the results indicate that the KlimaTicket has no short-run passenger growth effects. While passenger numbers recovered faster after the COVID-19 pandemic, in 2023, the passenger growth rate of the ÖBB is even lower than it would be under no treatment