Case Studies on Transport Policy最新文献

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.

In response to the escalating demands of urban logistics and the environmental impacts of last-mile deliveries in cities, this study assesses the transition to electric vehicles (EV) in the last-mile delivery transportation sector. We developed a methodology to project last-mile fleets and assess whether electrification considering a scrappage policy makes economic sense. This method utilizes socio-economic, geographic, and technical data to assess annual delivery volumes, travel distances, total ownership costs, and breakeven analysis for diesel and electric vehicles, focusing on Brazilian urban centers. Results show that in 2030, in all urban densities, EV have lower operating costs, and they are the more economical choice for all cities or lifespans by 2035. EVs stand out, particularly with extended vehicle lifespans and increased delivery frequencies. Our findings provide a versatile method for assessing the technical and economic feasibility of electric vehicles across diverse demographic areas.

Speed limits that change as per real time traffic, road, and weather conditions are termed as Dynamic Speed Limits (DSL). Road users are informed of speed limit changes in DSL scheme by electronic signs or Variable Message Signs (VMS) placed above the lanes or side-mounted along highways. In India, most of the highways have static speed limits. The speed limits are kept lower at locations or stretches adjacent to roadside schools, market areas, bus stops and intersections, for enhancing safety of Vulnerable Road Users (VRUs). This causes higher travel time to through traffic while travelling through these stretches. DSL has the potential in reducing the travel time and the variability of speed of vehicles, thus helps in enhancing road safety. The present work investigates the feasibility of DSL on various segments of a typical Indian highway passing through various roadside developments and human activities using cost-benefit analysis. The travel time benefits due to DSL are estimated by comparing the travel times with static and dynamic speed limit conditions. The results indicate that there is a significant amount of saving in aggregate travel time of all vehicles passing through the stretch due to the application of DSL. The benefit cost ratios greater than unity indicated that it is beneficial to deploy DSL on several segments of the highway passing through roadside schools, market areas, bus stops and intersections. The Benefit-Cost Ratio is also used advantageously to prioritize viable locations for deployment of DSL. The findings from the present work are likely to be of interest to policy makers in different developing countries where infrastructure/facilities for VRUs are deficient, road safety is a major concern and speeding is identified as a major problem.

Despite the key role that global supply chains (GSC), and more specifically, the transport and logistics function, might play in the performance of regions, there is a lack of analytical tools that turn the data generated by supply chain operations into quantitative metrics allowing policymakers to identify early signals of potential vulnerabilities and assess how resilient the GSC are at regional level. In an effort to fill this gap, we present a Transportation Resilience Index (TRI) that permits evaluating how transport chains affect supply chain resilience and, consequently, regional resilience. Our index, based on publicly available data –statistics on foreign trade flows provided by the Spanish Customs, the World Bank’ Logistics Performance Index and the UNCTAD’ Bilateral Liner Shipping Connectivity Index − differentiates between the determinants over which the company has direct decision-making control, and those linked to the selection of the supply market (market and macro dimensions). The TRI is applied to the Spanish regions (NUTS2) by using the Benefit-of-the-Doubt (BoD) approach to Data Envelopment Analysis (DEA) and applying a Common Set of Weights (CSW) for the selection of the weights to the index components. In our specific analysis, the market and macroeconomic components account for 84% of the total weight of the TRI. Despite the lower relative weight of the company dimension, the high degree of homogeneity in the market and macroeconomic scores means the company dimension plays a key role in the relative resilience of the Spanish regions.

Controversial transport policies, such as the proposed ban on non-electric motorbikes in Hanoi, Vietnam, often challenge the status quo and spur resistance among road users. This paper aims to unpack the causal implications of the motorbike ban, with an emphasis on elucidating potential transformations in urban mobility patterns and public sentiment in Hanoi. The research methodology is rooted in an mixed-methods approach. It begins by applying Spatial Propensity Score Matching (SPSM) to a bespoke transport survey to mitigate geographical confounding in the identification of the ban’s causal effects on societal attitudes and behaviours. Subsequently, it applies Ordinal Logistic Regression to quantify the causal influences of diverse socio-economic and demographic factors on public opinion towards the motorbike ban. Together, these methods yield a robust analysis of the policy’s prospective impacts.

Through this framework, the study provides insights into the key factors influencing individual’s opinion on controversial transport policies, such as the motorbike ban in Hanoi. Specifically, the approach reveals 4 key geographical insights into socioeconomic status, public transport perception, motorbike dependency, and automobile affinity among people in Hanoi.

In Dakar, the capital of Senegal, the urban transport policy aims to restructure and modernize the supply of public transport. The implementation of this policy since the years 2000 has led to the creation of the public bus company Dakar Dem Dikk and the replacement and reorganization of a number of minibuses owned by informal operators, which locally go under the name of Tata. However, this new supply still coexists with older, more or less informal, transport modes, mainly “Cars Rapides” and “Ndiaga Ndiaye” minibuses, collective clandestine taxis, and “yellow and black” taxis. The question then arises as to the impact of the new public transport supply on the mobility practices of the city’s residents. Data from two household mobility surveys, undertaken respectively in 2000 and 2015, in the Region of Dakar is used to conduct a diachronic analysis of mobility behavior. The results highlight the extent to which changes in public transport supply have modified flows and mode use for different categories of urban residents, in a context where daily mobility is highly dependent on public transport.

The development of urban public transport systems today has focused on increasing their operability, trying to minimize travel times and mobilize the greatest number of users by increasing operational speed, renewing the vehicle fleet, and increasing frequencies, among others. However, in addition to restructuring the operating distance and the location of the bus stops, this process of increasing operational capacity has paid little attention to the people's perception of these stop systems’ location and coverage. This causes, largely, users’ apathy to take advantage of the system, promoting the use of other means of transport, or in the least cases, to make stops within the system in unauthorized locations.

Considering the above, the aim of this research is to analyze the overage variation of bus-stop sets, based on the perception of users in normal and eager conditions, through the application of an analysis of population and zonal coverage, in which physical and operational variables of interest are considered, complemented with geostatistical models and digital tools that allow implementing a set of bus stops creating an inclusive environment with a broader vision of the ideal conditions for the definition of bus-stop sets. Within the research process, it is necessary to structure a statistical sampling, which allows for characterizing the population of public transport systems. Therefore, Manizales, the capital of the department of Caldas − Colombia, through its 12 district clusters and 378,000 inhabitants, is taken as a focus of study. However, due to the conurbation agreement with the municipality of Villamaría, the inclusion of its urban framework is carried out, resulting in a total population of 424,300 inhabitants.