Case Studies on Transport Policy最新文献

In Italy, where bicycle culture is struggling to catch on, the Extraordinary Plan for Tourism Mobility 2017–22 aims to increase the accessibility of tourist sites through safe and pleasant cycling routes, interconnected with other modes of transport. These same objectives have been pursued by Sardinia, one of the Italian regions more attractive to tourists, through the design of a regional cycle network and a long-distance tourist cycling routes (Ciclovia della Sardegna).

The current study focuses on tourism mobility in the metropolitan city of Cagliari, the largest urban area in Sardinia, and aims to explore how much the existing and planned cycling routes constitute an alternative mobility solution for tourists who intend to reach the beaches. In particular, the study aims to evaluate the level of accessibility offered by bicycling to the beaches, which are among the most visited and attractive places for tourists, before and after the implementation of a regional bike tourism network system. A GIS-based procedure was employed and the method comprised of three main steps: (1) data collection and preparation, (2) GIS analysis, and (3) assessment of results. We performed two main types of analysis using GIS. First, we delineated service areas around each beach for various distances. Then, we overlaid and analyzed these areas in conjunction with the accommodation facilities. Second, we measured the accessibility of beaches using a gravity-based accessibility index.

Our results demonstrate that, following the implementation of the regional cycle network Sardinia, various zones in the metropolitan area of Cagliari significantly increased their level of accessibility to the beaches, while others did not. Importantly, the adopted methodology has proven to be a valid tool for assessing cycling accessibility for different infrastructure scenarios.

There have been ongoing calls for reviving the rail system in Australia to transport cattle and meat products which is thought to be more reliable transport mode than road transport. This paper aims to develop a decision support model for the road-rail network for meat and cattle transportation. This model considers animal welfare, traffic congestion, and meat quality loss due to the delay of transportation as well as the effects of a carbon tax. The proposed model generates an optimal network configuration in which each leg of the journey is conducted by the most reliable and efficient transport mode. We implement this model using the meat and cattle supply chain case of Queensland that that comprises production regions, terminals, abattoirs, seaports and distribution centers. The results indicate that the road–rail multimodal network would be preferred if animal welfare issues were prioritised. Our decision support model is expected to support policy makers in making decisions to design a transport network with optimum balance of economic and environmental goals.

Substantial funding is allocated towards building new transit infrastructure worldwide. Such large undertakings can disrupt the system and result in the suspension of some of the provided transit services. While there is a considerable number of studies that focused on understanding people’s mode choices during normal operations and short-term disruptions, little has been done to investigate travel choices during long-term disruptive periods. This paper aims at examining changes in travel choices during a long-term disruption that occurred during the COVID-19 pandemic in Montréal. Using two waves of surveys, it explores the impacts of the suspension of the Deux-Montagnes train line due to the construction of a new light rail system, the Réseau express métropolitain (REM), on the travel choices of users that previously used the train line. Associations between respondents’ travel choices and socioeconomics, users’ perceptions, and spatial factors were examined, while exploring the difference between users’ anticipated travel choices reported before the suspension and their actual choices during the suspension. The results show that only around one-third of the Deux-Montagnes line’s previous users continued to use transit, while many shifted to using cars to reach the same destinations. Nevertheless, a higher percentage of users who live within an 800-metre buffer from a closed station used alternative transit options during the closure than using cars. Respondents who relied on using cars were the least likely to report that they will use the REM service in the future. The study highlights the overlooked impacts of long-term service closures.

In this paper, we present a mixed qualitative-quantitative approach to analyse the multiple dimensions of the barrier effect caused by the removal of all at-level pedestrian crossings on a railway in a residential area of Santiago, Chile, as part of a new suburban rail service. A set of interviews with a wide range of stakeholders is followed by a quantitative analysis of time delays and extra discomfort for pedestrians, as we measure both the horizontal and vertical detours on walking distance and time, due to having to cross on pedestrian overpasses and underpasses. We find that (i) the new suburban rail service is a source of social inclusion on a metropolitan scale (accessibility gains) and of social exclusion on a more local scale, due to a barrier effect (ii) the confinement of the railway produces strong negative impacts on pedestrians that need to cross the railway, by increasing walking times and by worsening their perception of security and comfort (iii) underpasses and overpasses increase between twofold and fourfold the time needed to cross the railway on average, relative to the case of at-level crossings, (iv) taking into account the increased physical burden and insecurity perceived on overpasses and underpasses, weighted walking times increase up to ten times relative to at-level crossing, and (v) women, elderly people and pedestrians with heavy luggage are more affected by the increased walking time. Traditional methods employed to analyse large-scale transport projects should assess the negative implications of the barrier effect on local communities, as well as the relief measures designed to reduce local segregation, especially in vulnerable communities. The results of this study are useful to quantify the social value of such relief measures, particularly in highly unequal urban settings.

Increasing the number and quality of bicycle parking facilities is essential to promoting cycling. However, quantifying the benefits of such improvements is difficult and has not yet been the focus of research. Apart from rule-of-half-based approaches, logsum analysis is a method for estimating the consumer surplus of measures, reflecting actual behavior.

This paper presents such an analysis of a set of measures on the RWTH Aachen University campus as a case study. Considering only the direct consumer surplus, the economic efficiency of the analyzed measures diverges significantly. The replacement of inadequate front wheel racks has the best consumer surplus-cost ratio, while the construction of bicycle parking stations has the worst. Taking into account modal shift effects and related changes in externalities and reduced demand for car parking, the cost-benefit ratios of the measures would be much higher. Even though the presented logsum approach ignores these second-order effects and focuses exclusively on economic efficiency, it is still useful in practice for prioritizing potential measures. Apart from that, the results show that groups of cyclists benefit differently from certain types of measures depending on their student status, employee group, and the resale value of their bicycle. Additionally, the analysis emphasizes the importance of including informal parking when modeling bicycle parking behavior.

During the COVID-19 pandemic, society realized that many activities could be conducted remotely, achieving similar or superior results. Several trends were anticipated and consolidated, such as remote work and hybrid activities. In this context, the air transport market was also profoundly affected, and we are still trying to understand the size and depth of the ongoing changes. It has become crucial for airline market strategies to evaluate how the behavior of business passenger demand has changed, considering the new conditions created and the intensified use of information and communication technology (ICT) tools, particularly videoconferencing. The article aims to identify and analyze the factors that have influenced the number of domestic business flights in Braziĺs post-pandemic era, focusing on the increased use of ICT. It applied a logit model to a database collected at Congonhas Airport in São Paulo, the second busiest airport in the country and the seventh in Latin America, which operates only domestic flights and is used mainly for business trips. Findings showed that the most significant variables influencing reduced travel for work were the number of trips made, the company’s market segment, and travelers’ perceptions about how the company dealt with topics such as productivity, employee well-being, videoconference use, and airline ticket purchases. With this understanding, airlines can develop more effective advertising strategies, enhance ticket sales, and prospect customers in more promising market niches.

Road traffic crashes are a leading cause of fatalities and injuries worldwide, prompting authorities to implement various strategies to enhance road safety. One common approach involves lowering speed limits in an effort to mitigate the severity of crashes and improve overall traffic safety. Seattle, Washington has been lowering its citywide default speed limits on municipal roads since 2016, among several cities in the US. This research paper presents a comprehensive investigation of the impact of these speed limit reductions on various safety indicators, such as the crash frequency, crash severity, crash characteristics, crash type, crash location, contributing factors, and overall traffic safety performance. The study employs a comprehensive dataset encompassing several years before and after the implementation of lower speed limits. Data analyses indicate varying changes in crash severity distribution between before and after periods in Seattle. Fatal and incapacitating crashes in Seattle decreased by 19% after the initial speed limit lowering in 2016 and further decreased by 3% after the second speed limit lowering in 2018. Pedestrian-involved crashes experienced a 26% significant decrease while speeding-related had a 16% decrease after the city implemented lowering speed limits. There was also a statistically significant 4% decrease in property damage only collisions and a 7% decrease in parked car crashes. Distracted driving / inattention-related crashes also decreased by 4%. The Mid-Block (but intersection related) crashes saw a significant decrease by 6%, and Driveway Junction related crashes decreased by 1%. The findings provide insights into the effectiveness of speed limit reductions in enhancing road safety in urban environments. The findings contribute to the existing body of knowledge on speed management strategies and their impact on traffic safety. The outcomes of this study can inform transportation policymakers and practitioners in Seattle and other urban areas as they make informed decisions regarding speed limit regulations and road safety measures.

This paper seeks to analyse the drivers behind students’ commuting choice in the context of a medium-sized public university (University of Urbino Carlo Bo) in Italy. The study accounts for changes in commuting preferences and choices occurring during the Covid-19 pandemic. The results are based on a 2020 survey on students analysed by means of a mixed multinomial logit model and a latent class model. The University of Urbino is an interesting case study for several reasons. First, it has a higher number of enrolled students (approximately 15,000) than there are residents in the municipality (less than 15,000). Second, Urbino is located far from main roads and transport infrastructures. Third, there are commuting options to and from the city, meaning that local transport policies have a relevant impact on the entire territory. Personal characteristics, distance from home, and price of the transportation mode influence the choice of students. The estimates for the two post-Covid-19 scenarios showed no particular changes in students’ transport habits, except when the number of household members was taken into account. The study provides valuable insights into the attitudes towards change in transportation choices that have recently emerged among a specific student population after an extended lockdown, that is now faced with making decisions marked by evident uncertainty about the possible developments of the Covid-19 virus.

Mobility-as-a-Service (MaaS) is a user-centered system that offers an ensemble of mobility services through a single digital platform. Large-scale adoption of MaaS is expected to reduce car ownership, ease traffic congestion, and provide a financial advantage to users by offering different mobility services at affordable prices. This study analyses how subscription fees impact MaaS adoption. We simulate the choice of subscribe to a MaaS package by using an agent-based modelling approach on a realistic case study. By including the costs associated with vehicle ownership, we assume agents to perceive and experience the trade-off between MaaS fees and ownership expenses. The study aims to unravel the potential users’ characteristics and future perspectives for MaaS widespread adoption and explore the implications of MaaS for sustainability goals and policies. We observed that users who frequently travel long distances and perform more trips per day are more likely to accept higher fees. On the other hand, with cheap subscription fees users tend to use carsharing services for short trips. Finally, the study suggests that subsidizing MaaS or adopting policies to increase car ownership costs can decrease car ownership and increase revenues for the service providers.

From April 1 to May 31, 2022, Shanghai implemented a full lockdown in response to the rapid spread of COVID-19 to protect the vulnerable population. This paper aims to comprehensively assess the impact of this lockdown. Traffic data for March and June of 2022 were collected, including the vehicular traffic volumes from four typical intersections and metro ridership. Other important indicators, including COVID-19 cases, Baidu Index and Shanghai Stock Exchange Index, were also employed. The results show that: (1) In both March and June, except for the intersection near the major hospital, the ratios between the weekday and weekend traffic volumes were higher than those observed before the pandemic, which implies a significant drop in leisure trips during these periods. (2) The evolution of traffic volume in March was largely driven by some important COVID-19-related events, while the traffic volume in June showed a more spontaneous and stepwise recovery pattern. (3) The confirmed cases had a significant impact on the traffic volume in March, but the time lag of the confirmed cases was not found. The impact of confirmed cases on traffic volume in June was not significant. (4) The transfer from public transport to private ones could be observed during this period, but the recovery proportion of Shanghai metro ridership is higher than most other cities examined in this study, suggesting the importance of enhancing public confidence for public transport in the post-pandemic period. These findings can aid in refining potential pandemic measures for future scenarios.