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This study proposed a method for optimizing a multi-period freight network design problem with industrial relocation (MPNDP-IR). Firstly, a land-use transport interaction (LUTI) model is developed to quantitatively describe the intricate interactions between industrial relocation behavior and freight network upgrades. Then, the proposed LUTI model is integrated into a bilevel programming framework to effectively optimize the multi-period network investment strategies and maximize benefits from relocated industries and freight transshipment. Finally, taking the Yangtze River Economic Belt (YREB) as a case study, the study results indicate that the sensitivity to location utility significantly affects the scope of the beneficial impacts of freight network investment policies, thereby affecting the industrial relocation pattern. Among manufacturing activities, the raw material and chemical industry is most responsive to such network investment policies along an important railway corridor. Under the low-sensitivity scenario, the relocation pattern of such an industry aligns with a gradient relocation mode; while, under the high-sensitivity scenario, it tends to choose a "fly-in" mode. This study provides a decision support method tailored for the MPNDP-IR. It not only simulates the coevolution of different industrial activities and freight network upgrades but also evaluates the spatiotemporal impact of multi-period network investment policies in the context of industrial relocation. • Identify the trend of industrial relocation and regional attractiveness for relocated industries. • Extend the application of the LUTI model for multiperiod transportation policy. • Provide a spatial econometric method for analyzing for coevolution of industrial activities and transportation networks. • Optimize multiperiod freight network policies balancing the diverse interests of different stakeholders. [ABSTRACT FROM AUTHOR]

This research examines the factors influencing the adoption and utilization of Mobility as a Service (MaaS), particularly focusing on carsharing and micromobility. Our objective was to understand how policy, physical infrastructure, social interactions, and individual attributes shape the use of MaaS. To this end, we conducted a systematic literature review using an adapted socio-ecological model. Our methodology involved a comprehensive search in the Scopus database using keywords related to MaaS and socio-ecological aspects, which yielded 420 relevant articles. These articles were analyzed for their alignment with the socio-ecological model across the specific dimensions of Personal Attributes, Community Interactions, Physical and Infrastructural Aspects, and Governance and Policy, as well as their relevance to MaaS. Key findings indicate that political decisions, including cooperation with public transport, environmental zones, and monetary incentives, significantly impact MaaS adoption. The study highlights the importance of policy in implementing micromobility models. Additionally, physical factors like infrastructure, geographic considerations, and urban design are crucial. Social context elements such as age, gender, education, and income also play a significant role, with higher education and income levels, as well as younger age groups, being more likely to adopt MaaS. Individual factors, including personal preferences and ecological consciousness, are pivotal, with perceived economic benefits being a primary driver for carsharing adoption. In carpooling, beyond the expected impacts of financial incentives, we highlighted the critical role of social norms and peer influences, particularly how visible carpooling by peers can drive adoption rates--a key finding for designing targeted social marketing strategies. For micro-mobility, the crucial finding was that infrastructure adaptations (such as the integration of dedicated lanes) not only support usage but also significantly enhance user safety and satisfaction, suggesting that physical infrastructure investments must be at the forefront of urban planning for effective micromobility integration. In conclusion, this research underscores the complex interplay of policy, physical, social, and individual contexts in MaaS utilization. It advocates for a balanced, context-specific approach to promoting shared MaaS, addressing both user-specific needs and broader transportation policy objectives. The study also suggests future research directions, including the impacts of MaaS on transportation, the role of technology and data, and the socio-economic aspects. [ABSTRACT FROM AUTHOR]

Fighting climate change has become a major task worldwide. One of the key energy sectors to emit greenhouse gases is transportation. Therefore, long term strategies all over the world have been set up to reduce on-road combustion emissions. In this context, the road freight sector faces significant challenges in decarbonization, driven by its limited availability of low-emission fuels and commercialized zero-emission vehicles compared with its high energy demand. In this work, we develop the Mobility and Energy Transportation Analysis (META) Model, a python-based optimization model to quantify the impact of transportation projected policies on freight transport by projecting conventional and alternative fuel technologies market acceptance as well as greenhouse gas (GHG) emissions. Along with introducing e-fuels as an alternative refueling option for conventional vehicles, META investigates the market opportunities of Mobile Carbon Capture (MCC) until 2050. To accurately assess this technology, a techno-economic analysis is essential to compare MCC abatement cost to alternative decarbonization technologies such as electric trucks. The novelty of this work comes from the detailed cost categories taken into consideration in the analysis, including intangible costs associated with heavy-duty technologies, such as recharging/refueling time, cargo capacity limitations, and consumer acceptance towards emerging technologies across different regions. Based on the study results, the competitive total cost of ownership (TCO) and marginal abatement cost (MAC) values of MCC make it an economically promising alternative option to decarbonize the freight transport sector. Both in the KSA and EU, MCC options could reach greater than 50% market shares of all ICE vehicle sales, equivalent to a combined 35% of all new sales shares by 2035. [ABSTRACT FROM AUTHOR]

In response to increasing environmental demands, modeling emissions from older vehicles presents a significant challenge. This paper introduces an innovative methodology that takes advantage of advanced AI and machine learning techniques to develop precise emission models for older vehicles. This study analyzed data from road tests and the OBDII diagnostic interface, focusing on CO2, CO, THC, and NOx emissions under both cold and warm engine conditions. The key results showed that random forest regression provided the best predictions for THC in a cold engine (R2: 0.76), while polynomial regression excelled for CO2 (R2: 0.93). For warm engines, polynomial regression performed best for CO2 (R2: 0.95), and gradient boosting delivered results for THC (R2: 0.66). Although prediction accuracy varied by emission compound and engine state, the models consistently demonstrated high precision, offering a robust tool for managing emissions from aging vehicle fleets. These models offer valuable information for transportation policy and pollution reduction strategies, particularly in urban areas. [ABSTRACT FROM AUTHOR]

Space is often produced digitally before it is produced physically. This article investigates how the right to the city can be broadened to include the appropriation of digital spaces to produce 'lived' transportation spaces. Focussing on mobilisation against highway expansion in Dallas, Texas, we ask the following: (1) what are the mechanisms through which space is conceived, perceived, and lived through the lens of mobility justice; (2) how might claims for technical information challenge dominant transportation policies and projects; and (3) how might participants inhabit digital spaces? We conduct a qualitative analysis of transportation planning narratives, visualisations, and public comments in three documents: the Dallas City Center Master Assessment Process, Coalition for a New Dallas' I-345/45 Framework Plan, and public survey data regarding proposed highway changes (n = 1241). Findings demonstrate how residents challenge transportation 'needs' as often determined in conceptual planning spaces. Further, technologies can be appropriated to produce differential spaces, which can alter the trajectory of highway projects. Challenging the legitimacy of institutionalised knowledge through the appropriation and production of digital spaces forms part of a larger claim to the right of the city. [ABSTRACT FROM AUTHOR]

Despite the significant role of alleyways in urban spatial configuration and accessibility as critical structures of urban infrastructure, there remains a noticeable gap in understanding their specific role in urban transportation policies. The main aim of the present study is to investigate the role of configurational accessibility of alleyways in facilitating wayfinding within organic street network systems. A mixed method was applied using Space Syntax and empirical observations. Moreover, Pearson correlations and t-tests were used to discern the association between variables and compare independent groups using SPSS software. The findings from the syntactical analysis strongly indicate that alleyways significantly impact configurational accessibility within urban network systems. Furthermore, the complex and labyrinthine structure of organic alleyways was found to significantly hinder the intelligibility of urban areas, making navigation more challenging. The results revealed a significant correlation between vehicle mobility and connectivity values, with higher levels of mobility consistently linked to increased connectivity values. The outcomes also indicated that alleys connected to main streets play a crucial role in facilitating wayfinding within urban network systems. This study contributes to a more profound understanding of the role of alleyways in urban network systems for urban planners and transportation engineers, paving the way for more targeted sustainable urban planning strategies. • Alleyways connecting main streets boost connectivity and vehicle mobility in organic urban networks. • The maze-like structure of organic alleyways complicates urban intelligibility and makes wayfinding harder. • The research indicates a significant correlation between vehicle mobility and alleyway connectivity. • Two alleyway types found: those connecting alleys and those linking main streets, with the latter easing traffic. • Planners should improve alleyway clarity to enhance wayfinding and support sustainable transportation in organic contexts. [ABSTRACT FROM AUTHOR]

This research analyzed car-ownership in the US during and after the COVID-19 pandemic, by utilizing a nationally representative household survey spanning from January 2020 to March 2022. Using a multilevel Hurdle model with month and state random effects, vehicle ownership trends are separately modeled for car-owning and carless households within the same modeling framework, while accounting for endogeneity and unobserved heterogeneity. An increase in the total amount of economic stimulus funding received increased the odds of vehicle ownership, while high car prices, high levels of housing expenditures, living in multi-family dwelling, and being from minority and low-skilled worker families negatively affected car-ownership. Greater household labor force participation, increases in household size and young persons in the household, living in states with high COVID caseloads and with moderately stringent Stay-at-Home social distancing mandates affected car-ownership propensities differently for car-owning and carless households. The significance of the research is that it disentangled pandemic-related and transportation policy variables from changes in household structure, living arrangements and employment-related characteristics. The analysis jointly considered how short-term pandemic-related influences as well as long-term demographic and occupational factors differently affect car-ownership for car-owning households and those without cars. Policy implications are drawn for consumer protection in the car ownership process, auto loan forbearance in future economic disruptions, strategies for public transportation which has continued to suffer from lower levels of use, and sustainability programs due to higher volumes of older used cars. • Increase in economic stimulus funding increased the odds of car-ownership. • High car prices and high housing costs negatively affected car-ownership. • Greater proportion of workers affected car-owning and carless households differently. • Stringency of Stay-at-Home levels and COVID caseloads also had different effects. • Pre-existing racial, occupational and dwelling effects persisted. [ABSTRACT FROM AUTHOR]

Transport of cargo by short-sea shipping is at the forefront of the European Union's transportation policy. It has the promise to alleviate congested land transport and decrease pollution [European Commission. 2021. Putting European transport on track for the future]. However, the shortage of qualified personnel might impede this solution. Autonomous sailing of ships could help, especially if the whole trip is automated. In this study a control system is designed that is capable of sailing a round-trip with a model-scale feeder vessel in Marin's Seakeeping and Manoeuvring Basin. The Guidance-Navigation-Control framework is used to sail this journey with attention given to smooth switching between the operational modes. A set of experiments is conducted to validate the controller and identify crucial parts in the operation. The experiments showed that the controlled vessel can sail a round-trip with different levels of waves and wind disturbances coming from different directions. Furthermore, the round-trip can be modified such that the approach angle to the quay changes and the ship still successfully docks at the quay. It was found that the approach to the quay is most difficult during transition from high to low speed, when the bow thrusters have yet to become effective, and a large change in course is needed. This can be circumvented by changing the trajectory to the quay to have a longer straight approach, or it can be corrected when the bow thrusters become active. [ABSTRACT FROM AUTHOR]

We estimate an equilibrium sorting model of housing location and commuting mode choice with endogenous traffic congestion to evaluate urban transportation policies. Leveraging fine-scale data from travel diaries and housing transactions identifying residents' home and work locations, we recover rich preference heterogeneity over both travel mode and residential location decisions. While different policies produce the same congestion reduction, their impacts on social welfare differ drastically. In addition, sorting undermines the congestion reduction under driving restrictions and subway expansion but strengthens it under congestion pricing. The combination of congestion pricing and subway expansion delivers the greatest congestion relief and efficiency gains. (JEL H76, O18, P25, R23, R31, R41, R48) [ABSTRACT FROM AUTHOR]

AbstractEmission models developed using scaled tractive power (STP) distributions are extensively utilized to estimate heavy-duty trucks (HDTs) emissions, for effectively capturing vehicle operating characteristics. The granularity of actual gross vehicle weights (AGVW) in current emission models for on-road HDTs is insufficient for accurate emission estimation. To address the gap, this article developed a model of weight-specific STP distributions for on-road HDTs. Trajectory data of 10 HDTs with varying actual gross vehicle weights (AGVWs) were collected, and the relationships between AGVW and STP distributions were quantified using Gaussian and polynomial functions. Evaluation based on various indicators reveals that the developed model can deduce STP distributions accurately and efficiently by only inputting the unique variable AGVW and performs well in emission estimation. Compared with real-world data, the mean RMSE and overlap rate of STP distributions are 0.04 and 0.84, respectively. Take an HDT weighing 51.5 tons as an example, CO2, NOX, CO, and HC emission factor estimation errors are 3.6%, 4.3%, 3.5%, and 1.9%. Compared to Motor Vehicle Emissions Simulator (MOVES), the model can reduce the mean estimation errors by 12.3%, 10.9%, 6.3%, and 6.1% for CO2, NOX, CO, and HC emission factors, with a maximum reduction of up to 24.4% for CO2 when the speed is 88 km∙h−1. The accurate emission estimation provided by the model can bolster the development and implementation of transportation decarbonization policies. [ABSTRACT FROM AUTHOR]

Transitioning to a fully Level-5 autonomous vehicle (AV) environment presents numerous challenges, notably influenced by public adoption intention. Previous studies have shown limitations in scope, population, and methodology. This study expands the Technology Acceptance Model to investigate AVs adoption intention across various city sizes in China. Through surveys in China, 2,662 responses were gathered in 2021 from mega, large, and small-to-medium cities. Using Multiple Indicators and Multiple Causes models, the study examines influencing factors on AVs adoption intention and population heterogeneities. Key findings emphasize the importance of adoption attitude, information provision, and perceived AV usefulness. Additionally, the impact of financial incentives, convenience, and several other factors varies across city sizes. The insights gained from the study can be utilized to develop more cost-effective policies and strategies tailored to different subgroups of the population to fully utilize the potential benefits of AVs while minimizing unintended consequences across diverse urban settings. [ABSTRACT FROM AUTHOR]

This paper simulated a simultaneous un-berthing of two container ships. The simulation was intended to determine the number and capacity of tugboats considering an emergency situation in a port. A port provides the number and capacity of tugboats based on the regulation of the Transportation Ministry. In an emergency condition at the terminal and the maximum environmental conditions of wind, wave, and current, the vessel should be un-berthed simultaneously. In this study, two container ships are un-berthed simultaneously in eight scenarios. The available tugboats are simulated using the MMG model to pull the vessels from the jetty turn them in the approaching channel and pass the main channel to achieve the anchorage area. The trajectories of maneuvering using the existing tugs are compared to the normal passage using the appropriate capacity of tugboats. The number and capacity of the tugboat to comply with the safety criteria and avoid collision between the un-berthed ships is proposed. [ABSTRACT FROM AUTHOR]

The global reliance on electric vehicles (EVs) has been rapidly increasing due to the excessive use of fossil fuels and the resultant CO2 emissions. Moreover, EVs facilitate using alternative energy sources, such as energy storage systems (ESSs) and renewable energy sources (RESs), promoting mobility while reducing dependence on fossil fuels. However, this trend is accompanied by multiple challenges related to EVs' traction systems, storage capacity, chemistry, charging infrastructure, and techniques. Additionally, the requisite energy management technologies and the standards and regulations needed to facilitate the expansion of the EV market present further complexities. This paper provides a comprehensive and up-to-date review of the state of the art concerning EV-related components, including energy storage systems, electric motors, charging topologies, and control techniques. Furthermore, the paper explores each sector's commonly used standards and codes. Through this extensive review, the paper aims to advance knowledge in the field and support the ongoing development and implementation of EV technologies. [ABSTRACT FROM AUTHOR]

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The advancement of emission reduction benefits in ridesplitting relies on a comprehensive carbon reduction incentive policy initiated by the government and implemented through the collaborative efforts of multiple stakeholders. The aim of this study is to understand the implementation mechanism and explore the carbon reduction potential of the Carbon-Inclusive Policy. A framework has been developed to explore an evolutionary stabilization strategy through a three-party evolutionary game model, which considers the crucial stakeholders of the government, shared mobility companies, and travelers. A comprehensive sensitivity analysis has been conducted across various scenarios on key factors to ensure the robustness and accuracy of findings. The study's primary findings indicate that the government's level of commitment to the Carbon-Inclusive Policy significantly influences strategic decisions and the pace of evolution among the three stakeholders in the evolutionary game. Companies critically assess the economic viability of ridesplitting, particularly in light of development costs and subsidy incentives. Government backing and increased ridesplitting adoption by travelers serve to mitigate risks, incentivizing companies to actively promote ridesplitting. Furthermore, the study emphasizes the necessity of balancing individual, company, and societal interests for sustainable transportation development, advocating for reasonable carbon tax credits and the promotion of novel development concepts such as Environmental, Social, and Governance (ESG) principles. These findings serve as a significant resource for policymakers navigating the complexities of integrating carbon considerations into transportation policy frameworks, contributing to a deeper theoretical understanding of Carbon-Inclusive Policy implementation in the sector. [ABSTRACT FROM AUTHOR]

Using Coefficient of Variation and GIS spatial analysis, we detected the spatial and temporal evolution and development patterns of border trade in Yunnan counties, analyze the de‐ velopment pattern of border trade in depth by combining with the model of border trade develop‐ ment level, and explore the driving mechanism of border trade by using geographic probes. The results show that: ① the overall trend of county border trade in Yunnan Province is on the rise, and the total volume varies unevenly among counties, with Ruili City in the west and Mengla County in the south as the representative counties with higher total trade volume, while the over‐all trade volume in Ximeng County in the southwest and Lushui County in the northwest is smaller. ② From 2010 to 2020, the development pattern of county border trade in Yunnan Prov‐ ince varies. ③ During the same period, the border trade development in the western and south‐ eastern border counties is high and the growth rate is stable; the development in the northwestern and southwestern counties is low and the growth is fast; the development in the southern coun‐ ties is high and the growth is slow. ④ The main driving factors affecting the border trade in the counties factors are policy and transportation factors, and the secondary driver is GDP per capita, while there are differences in the driving factors of border counties with different neighboring countries. [ABSTRACT FROM AUTHOR]

AbstractProblem, research strategy, and findingsTakeaway for practiceWe predicted the amount, share, and value of land dedicated to roadways within and across 316 U.S. primary metropolitan statistical areas. Despite the amount and value of land dedicated to roadways, our study provides the first such estimate across a broad range of metropolitan areas. Our basic approach was to estimate roadway widths using a 10% sample of widths provided by the Highway Performance Monitoring System and apply our estimates to the rest of the roadway system. Multiplying estimated widths by segment length and netting out double counting at intersections provided estimates of land area. We also matched roadway segments and areas to existing land value estimates and satellite-based measures of urbanized land. We found that a little less than a quarter of urbanized land—roughly the size of West Virginia—was dedicated to roadway. This land was worth around $4.1 trillion in 2016 and had an annualized value that was higher than the total variable costs of the trucking sector and the total annual federal, state, and local expenditures on roadways. Conducting a back-of-the-envelope cost–benefit analysis, we found that the country likely has too much land dedicated to urban roads.Federal, state, and local agencies dedicate substantial time, money, and resources to providing roadways. Even with relatively generous assumptions and no external costs from driving, however, we estimated that the average cost of expanding roadways exceeded the benefits by a factor of nearly three when accounting for land value. Policymakers should question policies focused on roadway expansion and consider options to reduce the amount of space dedicated to roadway in favor of more housing, offices, and other land uses. In addition to our findings, we provide a novel data set that academics and policymakers can use to draw their own conclusions about the state of America’s urban roadways. [ABSTRACT FROM AUTHOR]

Neighborhood sustainability assessment (NSA) systems assess neighborhood sustainability through different themes. Most NSA systems originated from developed countries, with limitations in assessing micro-level transportation infrastructure. The NSA systems lack alignment with Indian regulations and policies and have limitations in assessing informal transportation modes, affordability, and street-vending-related issues. This research developed the sustainable transportation assessment index (SusTAIN) framework to assess mixed-use neighborhoods in India and overcome the limitations of NSA systems. The method was to identify and evaluate qualitative and quantitative indicators and sub-indicators from NSA systems, Indian transportation regulations and policies, and transportation system studies from the literature. Indicators were integrated into the four subthemes of (i) accessibility, (ii) mobility nodes and network, (iii) external factors associated with mobility, and (iv) land-use and socioeconomic factors' assessment. The authors evaluated the framework through the Geographical Information System (GIS), site surveys, and benchmark values from the literature. This research demonstrated the interrelationship of indicators and the sub-indicators between them. Finally, the authors discussed the SusTAIN composite index formation method. The framework is vital for the local application of national sustainable urban development policies. The SusTAIN framework application enables local governments to evaluate the transportation sustainability of neighborhoods and identify potential optimization areas. [ABSTRACT FROM AUTHOR]

Structural models of traffic congestion, such as the bottleneck model, are used to answer important, policy‐relevant questions. However, existing models typically assume that no travelers are inframarginal regarding when to travel; that is, given equilibrium travel times, no travelers strictly prefer their ex ante departure time to all others. In this article, I address this shortcoming by incorporating inframarginal travelers into these models. This change significantly improves these models' ability to fit the data and changes policy prescriptions. In the case of congestion pricing, it typically changes the optimal toll by at least 25% and significantly worsens the distributional impacts. [ABSTRACT FROM AUTHOR]

Sustained efforts and investments in different sectors are essential for the overall development of a region. Various studies around the globe underscore the importance of investment in road transport infrastructure in many developing countries to achieve their development targets. The relationship between infrastructure investment and economic growth is often found to be inconsistent. This ambiguity leads to a lack of consensus on an appropriate scale of investment required among the policy makers. So, it is often necessary to depend on empirical evidence by developing causality direction, which significantly contributes to policy implications in developing countries. The objective of this analytical study is developing a relationship between the road transport infrastructure and economic growth of Nepal. For this, relevant data from 1998 to 2022 were used to perform a unit root test and determine the order of integration, followed by cointegration analysis to determine the long-run relationship between the variables. In addition, the vector error correction model (VECM) was employed to find the direction of causality. The findings indicate unidirectional long-run causality from gross capital formation, exports of goods and services, expenditure on road transport infrastructures, and road length to the GDP of Nepal. Furthermore, the expenditure on road transport infrastructures is observed to have a short-run impact on economic growth. This study recommends that a suitable transportation policy should be implemented to boost investment on road transport infrastructures to achieve sustainable economic growth in Nepal-like developing nations. [ABSTRACT FROM AUTHOR]

The present research investigates the advancement of sustainable transportation by promoting electric vehicles, expanding public transit, and implementing tax increases on fossil fuels and automobiles, via crucial strategies. The present study has examined a market with a fossil fuel vehicle (FFV) manufacturer, an electric vehicle manufacturer, and the government. The manufacturers' pricing strategies are geared towards optimizing profits, whereas the government's objectives for transportation are centered on attaining sustainability across economic, environmental, and social dimensions. The government has considered two strategies, one taxation-based and the other non-taxation-based, to achieve its objectives. In the taxation-based strategy, fixed taxes on fossil-fuel vehicles and fossil fuels are considered, while in the non-taxation-based strategy, subsidies for purchasing electric vehicles and the number of buses purchased for public transportation are predefined. Based on this, eight scenarios with different values for the predefined factors of each strategy have been defined to attain their respective objectives. Game theory has been utilized to determine an optimal solution based on Norwegian data, owing to the interconnected decision-making among stakeholders. By analyzing the findings, managers can enhance their decision-making capabilities. The results suggest that appropriately adjusting subsidies, taxes, and bus numbers within specific thresholds is crucial for mitigating air pollution and achieving other objectives. The assertion that electric cars are a definitive solution may not be accurate, as it depends on the source of the generated electricity. While excessive subsidies in non-renewable energy countries can lead to increased pollution, even in Norway, where most electricity is renewable, rising demand for electric vehicles contributes to air pollution due to increased production. In countries where electricity generation is not primarily from renewable resources, the growth of electric vehicles further exacerbates pollution. Simultaneous increases in fuel taxes and tariffs on fossil fuel vehicles negatively impact the demand for fossil fuel vehicles and government revenues. Therefore, it is recommended that an increase in fuel taxes be implemented to optimize both government revenues and social welfare. This approach safeguards public revenues, promotes societal well-being, and mitigates air pollution. • Examining the impact of promoting Evs and public transportation on sustainable transportation development. • Pricing of electric and fossil fuel vehicles using game theory and based on a case of Norway. • Studying the impact of tax, subsidies, and public transportation expansion on sustainable transportation goals. • Investigating vehicle selection based on government policies (allowing EV access to dedicated bus lanes). • Examining the Rebound effect of excessive promotion of electric vehicles or buses. [ABSTRACT FROM AUTHOR]

Transportation systems are a basis of disability-related activity involvement in society. In Tehran, the capital of Iran, a paratransit system for disabled people has been operating since 2013, but the market share is gradually losing for reasons unknown to practitioners. Although paratransit systems for people with disabilities exist in many cities, no comprehensive study has been completed to identify attitudinal and contextual barriers to the continuance intention to use the system, particularly in a low-income developing country. Thus, due to limitations faced by qualified experts in this field, the adoption of efficient transportation policy and engineering interventions is still limited. The Technology Continuance Theory (TCT) is employed in this study as a structural equation modeling framework to analyze and quantify relationships based on the data gathered by face-to-face interviews. The mediation/moderation analyses in this paper reveal that (i) stress, (ii) self-efficacy, (ii) social isolation, (iv) mode captivity, (v) experience of usage, and (vi) type of disability are of prime importance in disabled people's intention to reuse the paratransit system. Stress is examined through serial mediation analysis. The analysis reveals that stress due to the system's uncertain attributes significantly influences satisfaction. Self-efficacy and social isolation are presented for the moderation and moderated-mediation analyses. It is found that the urban mobility performance of the system is of more importance to disabled people with lower self-efficacy (high social isolation); however, their stress is not significantly reduced even by increasing the usefulness of the system. The mode captivity is also redefined in this context and entered as a moderator. It is found that, for captive riders, satisfaction does not have a dominating role in the intention to use the paratransit system, as the users are constrained by taking what is available or nothing. The usage experience is another moderator, and our analysis shows that attitude is a determinant of behavior for long-term users, while satisfaction with a transient effect is a dominating factor for short-term ones. Finally, the users are categorized by type of disability , and the moderation analysis shows that for people with physical disabilities, the system's performance is the most influential factor in their satisfaction, while for people with sensory disabilities, other factors related to amenity, safety, and support are also prominent. This paper ultimately presents explicit and thorough policy considerations and practical implications. The article's concluding remark will comprise a disclosure of previously undisclosed insights that underlie the study's findings. • Transportation systems are a basis of activity participation of disabled people. • We try to investigate factors the operator of a paratransit system must consider to attract and retain users. • Technology Continuance Theory is employed in this study as a structural equation modeling framework. • This analysis finally suggests detailed, clear, and specific engineering measures. [ABSTRACT FROM AUTHOR]

Introduction: Infrastructure regularly supports male pursuits more than women's. Recent transportation scholarship focuses on this inequity by quantifying the daily travel of women and men for everyday care provision, often termed "the mobility of care." Care trips include dropping off and picking up family members, accompanying young children and old adults to medical appointments, and acquiring household goods. This study analyzes gendered travel behavior in the National Capital Region of the United States, including Washington, D.C. Methods: The basis of this study's analysis is data from the 2017/2018 Regional Travel Survey conducted by the National Capital Region Transportation Planning Board. The survey included records from approximately 16,000 households, 2,000 in Washington, D.C. Our study sample contained 19,274 unique people who made 49,215 trips. Many of these trips were made using the local bus and subway systems. Following an established methodology, the researchers recoded trip purpose data into five broad categories: care, work, shopping, leisure, school, and all other purposes. We then ran descriptive and statistical analyses of travelers aged 18 through 65 to measure the frequencies of household demographic characteristics and person-level trips for all purposes made by five travel modes: walk, bike, car, bus, and subway. Results: Based on our analysis, trips for work represent the majority of trips (34.7%), followed by shopping (28.2%), care (22.3%), leisure (8.5%), other (4.1%), and school trips (2.3%). Our findings indicate that women make more carerelated trips during the day than men (25.1% vs. 18.8%). They also make fewer work-related trips than men (30.3% vs. 40.2%). Regression analyses revealed correlations between care-related travel by all modes and public transportation by age, race, location of residence, and income. Discussion: The mobility of care, done mostly by women, is one of the primary reasons that people travel in and around Washington, D.C., and its suburbs. However, D.C.'s bus and subway systems are primarily designed to support the mobility of work done mostly by men. As a result, our study identifies the need for improvements in gender-responsive infrastructure, including public transportation policies and programs that explicitly address the mobility of care, improve access to care, and reduce the environmental impact of cars. [ABSTRACT FROM AUTHOR]

This paper offers a comprehensive exploration of the implementation of fully electric transportation systems within urban college campuses. Urbanization and environmental concerns have intensified the need for sustainable transportation solutions, and college campuses serve as ideal testbeds for innovative mobility initiatives. The paper begins by establishing the context through background research, which highlights the adverse effects of urban air pollution and the role of electric vehicles (EVs) in mitigating these issues. The driving forces behind the adoption of fully electric transportation systems are discussed, Benefits, challenges, and implications of implementing electric transportation systems are meticulously examined. The anticipated benefits encompass improvements in air and noise pollution, reduced operational costs, and enhanced campus reputation. Nevertheless, the challenges of infrastructure costs, charging management, and operational intricacies are acknowledged. The paper underscores that successful implementation goes beyond immediate advantages, positioning campus electric transportation systems as living laboratories for research and innovation in sustainable mobility. Additionally, these systems serve as models for neighboring communities and influence regional transportation policies. The paper concludes by laying the groundwork for forthcoming discussions. It highlights the subsequent sections' focus on planning, stakeholder engagement, technological integration, and operational management, which collectively shape the implementation. The paper will employ the application of Systems Thinking approaches, tools, and techniques in order to properly analyze and tackle the problem statement at hand. [ABSTRACT FROM AUTHOR]

As the aspirational Complete Streets movement sweeps North America with multimodal transportation policies and plans, communities need practice-ready tools that reinforce social inclusion and sustainable development through the movement's implementation. Here we present two such tools: (1) gender analysis, which considers gendered experiences and roles in the context of Complete Streets so as to benefit diverse travelers with improved safety, transportation choices, support for caregivers, and more; and (2) an approach called SDG 360 Thinking, a holistic analysis of Complete Streets policy co-benefits, unintended harms, and trade-offs using the UN Sustainable Development Goals. We piloted these tools in workshops with community members and technical experts. Workshop participants gained new insights, made connections across sectors, took more inclusive and diverse perspectives, and made recommendations about Complete Streets policies. These tools are practical, easy to understand, and could be broadly impactful for communities. [ABSTRACT FROM AUTHOR]

The article explores the transport policy in Albania with focus on the development of sustainable and integrated transport network to drive economic competitiveness. Topics discussed include planning and management of transportation infrastructure development projects, regulation of transport modes and networks and their use to promote regional connectivity, and progress of the transport sector in terms of resource efficiency, social inclusion, sustainability and environmental protection.

The article explores the transport policy in Serbia that is essential for promoting economic cooperation and competitiveness. Topics discussed include planning and management for developing transport policy and implementing infrastructure projects, regulation and operation of transport modes and networks, cross-border cooperation on transport networks to enhance regional connectivity, and sustainable transport networks for resource efficiency and environmental protection.

As part of the shift in policy to promote active travel, the UK's Manual for Streets (MfS) guidance proposed new approaches for priority intersections design in residential areas, promoting lower geometric visibilities for drivers on minor road arms to reduce collision severity, and the low-speed (i.e., 20 mph) limit zone policy. However, the relationship between speed, visibility, and collisions has not been explored comprehensively for these low-speed limit residential areas. This study aimed to evaluate the impact of shorter visibilities on vehicle-bicycle collisions at priority intersections in Portsmouth, UK. Using piecewise Structural Equations Modeling and Artificial Neural Network models, 120 locations in the city were analysed to understand the complex interplay between vehicles' speed, speed limits, visibilities, geometries, traffic flows, and collisions. The research question was whether shorter visibilities supported policy intentions by reducing bicycle collisions in low-speed limit areas, as MfS suggested. The results show that greater visibility 9 m back to left and right positively correlates with higher road traffic collisions. In comparison, greater left-hand visibility at 2.4 m back from minor arms has a counter-effect that improves safety. This supports the notion that shorter visibility in residential areas aid cyclist safety. This study contributes significantly to the literature by shedding light on the impact of shorter visibility on road safety. The findings have important implications for transportation policy and practice, highlighting the importance of the MfS approach for improving cyclist safety in the design of priority intersections. • The pSEM model reveals complex relationship between intersection geometries, and collisions in low-speed limit areas. • The shorter visibility distance in built-up areas correlates with fewer bicycle collisions. • The longer visibilities at 9 m back to the left and right are associated with higher bicycle collisions. • Better left-hand visibility at 2.4 m improves cyclists safety. • The policy implication of 20 mph (30 km/h) speed limits improves the safety of cyclists at intersections. [ABSTRACT FROM AUTHOR]

This article makes the case that electric micromobilities (EMMs) are the site of a moral panic and employs the lens of mobility justice to explain it. Through analysis of scholarly and media discourse, interviews with, and social media content produced by, EMM riders (eriders), and the auto ethnographic experiences of the lead author as an electric unicycle rider in daily life, as a participant in online and offline "erider" communities, and as a food delivery worker, we reinforce the conclusion that alternate mobilities face an uphill battle in gaining legitimacy and inclusion in transportation policy and infrastructure. While this is not a new finding—alternate mobilities have a long history of being demonized and excluded—this article offers insight into how individuals who find themselves unwitting scapegoats in conflicts over public space consciously engage in deliberate actions to resist EMM panic and achieve greater mobility justice. [ABSTRACT FROM AUTHOR]

High-speed rail (HSR) services are experiencing rapid global expansion, posing competition not only in the traditional passenger sector but also challenging air cargo with their attributes of speed and punctuality. In this study, we establish a straightforward model for air-HSR competition in both passenger and cargo markets, taking into account the vertical structure of transportation supply chain. We explore various market equilibria based on the combination of three factors: 1) HSR's provision of cargo services, 2) the integration or separation of HSR's ownership and operation, and 3) uniform or differentiated airport administrative fees for passenger and cargo airlines. The analytical results of our model indicate that the entry of HSR into the cargo market consistently enhances social welfare and may even improve the profit of cargo airlines. However, if airports adopt uniform pricing or there is vertical separation in HSR sector, this could potentially weaken the positive impact on welfare enhancement. These findings have important implications for transportation policy, highlighting how strategic management of infrastructure can significantly influence the effectiveness and societal benefits of HSR's expansion into cargo services. • We develop a model to explore air-HSR competition in passenger and cargo sectors, focusing on their vertical structure. • We evaluate: 1) HSR cargo service, 2) split HSR ownership/operation, 3) airport's distinct fees for passenger/cargo airlines. • Introducing HSR to the cargo market always improves social welfare, without necessarily diminishing cargo airline profits. • A uniform pricing strategy at the airport could potentially harm the profits of most involved entities. • HSR's vertical separation decreases traffic and profits, worsening social welfare, especially in larger markets. [ABSTRACT FROM AUTHOR]

On-demand app-based shared mobility services have created new opportunities for complementing traditional fixed-route transit through transit agencies' efforts to incorporate them into their service provision. This paper presents one of the first studies that rigorously examine riders' responses to a pilot aimed at providing such a transit-supplementing service. The study conducts latent class analysis on riders of the Via to Transit program, a mobility pilot in the Seattle region where on-demand service was offered to connect transit riders to light rail stations. The analysis identifies three distinct rider groups with heterogenous responses to the on-demand service: (1) riders who previously used private cars or ride-hailing; (2) riders who were pedestrians and bikers but switched likely because of safety concern; (3) mostly socio-economically disadvantaged riders who previously relied on the bus, but switched to the new service for the convenience and speed. These results point to rich transportation policy implications, which can inform decision-making by public transit agencies as they are exploring alternative ways to deliver the mobility services. [ABSTRACT FROM AUTHOR]

Public health and climate change mitigation are strongly related to the efficiency of a unified vehicle-health system. To date, however, the existing DEA studies have not incorporated a robust set of transportation and public health indicators to evaluate the performance of the vehicle-health system. Our approach maps the relationship between transportation and health indicators in a network DEA framework. In addition, this study develops a new methodological framework for identifying stage priorities for decision-makers, peer evaluation and an understanding of the effects of policy in a comprehensive vehicle-health production system. This study empirically evaluates indicators of vehicle use and their effects on public health for each US state. The main conclusions are summarized: First, the network DEA and cross-efficiency network DEA models have significant methodological differences, highlighting the importance of model selection for empirical analysis. Second, US states exhibit enormous disparities in their prior strategies. The relative weights of the vehicle use stage and health outcomes stage confirm differing levels of importance attached to either stage. Third, group heterogeneity and technology inequality are observed among US states. Both intra-group and inter-group inequalities drive technology inequality. Moreover, considerable heterogeneity exists in the intra-group decomposition of the overall efficiency Theil index among the three network DEA models. Finally, promoting a safe and integrated transportation network improves vehicle-health performance, implying that strategic transportation policies hold significant potential for improving public health. [ABSTRACT FROM AUTHOR]

Like all branches of our economy, also railway transport is based on long-term strategic plans whose aim is to create a transportation policy in order to achieve the most appropriate and equal conditions for all carriers. Coping with safety and hazard prevention must be based mainly on the capabilities of each business entity. The paper points out the issue of employees' work safety in the Slovak Railways company in connection with the European legislation in the field of safety and health protection at work and its implementation into the laws of the Slovak Republic. It also discusses the issues of employees' safety at workplaces and summarizes the duties of employees and employers in the field of health and safety protection in railway transport and deals with the implementation of European legislation into the laws of the Slovak Republic. The paper also analyses the safety of employees in railway transport in the form of a survey, whose aim is to determine the state of employees' safety at workplaces and aims to confirm or refute hypotheses regarding the impact of the quality and effectiveness of internal safety regulations of the Slovak Railways on the safety of employees and also whether the employer implements sufficient measures in order to minimize possible accidents at workplaces. [ABSTRACT FROM AUTHOR]

The transportation landscape is witnessing profound changes due to technological advancements, necessitating proactive policy responses to harness innovation and avert urban mobility disruption. The sharing economy has already transformed ridesharing, bicycle-sharing, and electric scooters, with shared autonomous vehicles (SAVs) poised to reshape car ownership. This study pursues two objectives: firstly, to establish a market segmentation for shared ride services and secondly, to evaluate the environmental impact of ridesharing in different contexts. To mitigate potential biases linked to stated preference data, we analysed the navette service, utilized by a research institute in Europe, closely resembling future SAVs. The market segmentation relied on hierarchical cluster analysis using employee survey responses, while the environmental analysis was grounded in the 2019 navette service data. Our analysis revealed four unique employee clusters: Cluster 1, emphasizing active transportation and environmental awareness; Cluster 2, showing openness towards SAVs given reliable alternatives are available; Cluster 3, the largest segment, highlighting a demand for policy support and superior service quality; and Cluster 4, which places a premium on time, suggesting a potential need for strategies to make the service more efficient and, consequently, discourage private car use. These findings highlight a general willingness to adopt shared transport modes, signalling a promising transition to shared vehicle ownership with significant environmental benefits achievable through service design and policy measures.

Abstract Background Transportation policies can impact health outcomes while simultaneously promoting social equity and environmental sustainability. We developed an agent-based model (ABM) to simulate the impacts of fare subsidies and congestion taxes on commuter decision-making and travel patterns. We report effects on mode share, travel time and transport-related physical activity (PA), including the variability of effects by socioeconomic strata (SES), and the trade-offs that may need to be considered in the implementation of these policies in a context with high levels of necessity-based physical activity. Methods The ABM design was informed by local stakeholder engagement. The demographic and spatial characteristics of the in-silico city, and its residents, were informed by local surveys and empirical studies. We used ridership and travel time data from the 2019 Bogotá Household Travel Survey to calibrate and validate the model by SES. We then explored the impacts of fare subsidy and congestion tax policy scenarios. Results Our model reproduced commuting patterns observed in Bogotá, including substantial necessity-based walking for transportation. At the city-level, congestion taxes fractionally reduced car use, including among mid-to-high SES groups but not among low SES commuters. Neither travel times nor physical activity levels were impacted at the city level or by SES. Comparatively, fare subsidies promoted city-level public transportation (PT) ridership, particularly under a ‘free-fare’ scenario, largely through reductions in walking trips. ‘Free fare’ policies also led to a large reduction in very long walking times and an overall reduction in the commuting-based attainment of physical activity guidelines. Differential effects were observed by SES, with free fares promoting PT ridership primarily among low-and-middle SES groups. These shifts to PT reduced median walking times among all SES groups, particularly low-SES groups. Moreover, the proportion of low-to-mid SES commuters meeting weekly physical activity recommendations decreased under the 'freefare' policy, with no change observed among high-SES groups. Conclusions Transport policies can differentially impact SES-level disparities in necessity-based walking and travel times. Understanding these impacts is critical in shaping transportation policies that balance the dual aims of reducing SES-level disparities in travel time (and time poverty) and the promotion of choice-based physical activity.

Background: Transportation policies can impact health outcomes while simultaneously promoting social equity and environmental sustainability. We developed an agent-based model (ABM) to simulate the impacts of fare subsidies and congestion taxes on commuter decision-making and travel patterns. We report effects on mode share, travel time and transport-related physical activity (PA), including the variability of effects by socioeconomic strata (SES), and the trade-offs that may need to be considered in the implementation of these policies in a context with high levels of necessity-based physical activity. Methods: The ABM design was informed by local stakeholder engagement. The demographic and spatial characteristics of the in-silico city, and its residents, were informed by local surveys and empirical studies. We used ridership and travel time data from the 2019 Bogotá Household Travel Survey to calibrate and validate the model by SES. We then explored the impacts of fare subsidy and congestion tax policy scenarios. Results: Our model reproduced commuting patterns observed in Bogotá, including substantial necessity-based walking for transportation. At the city-level, congestion taxes fractionally reduced car use, including among mid-to-high SES groups but not among low SES commuters. Neither travel times nor physical activity levels were impacted at the city level or by SES. Comparatively, fare subsidies promoted city-level public transportation (PT) ridership, particularly under a 'free-fare' scenario, largely through reductions in walking trips. 'Free fare' policies also led to a large reduction in very long walking times and an overall reduction in the commuting-based attainment of physical activity guidelines. Differential effects were observed by SES, with free fares promoting PT ridership primarily among low-and-middle SES groups. These shifts to PT reduced median walking times among all SES groups, particularly low-SES groups. Moreover, the proportion of low-to-mid SES commuters meeting weekly physical activity recommendations decreased under the 'freefare' policy, with no change observed among high-SES groups. Conclusions: Transport policies can differentially impact SES-level disparities in necessity-based walking and travel times. Understanding these impacts is critical in shaping transportation policies that balance the dual aims of reducing SES-level disparities in travel time (and time poverty) and the promotion of choice-based physical activity. [ABSTRACT FROM AUTHOR]

This paper uses machine learning approaches to predict the association between traffic volume, air pollution, and meteorological conditions. A key focus is on the interaction between these factors. The paper does this using hourly traffic volume, N O x , P M 2.5 , and weather data for Oslo, Norway. I considered a total of six datasets of the 2019 whole-year data to verify the prediction accuracy of the models. I find that the autoregressive integrated moving average model with exogenous input variables, and the autoregressive moving average dynamic linear model outperform the machine learning models in predicting air pollution. At the same time, I also explored the effect of sampling weather subsets on prediction accuracy. Finally, my study makes optimal policy recommendations for reducing air pollution from traffic volume, after considering the interaction and lagged effects of meteorology, time variables, traffic, and air pollution. [ABSTRACT FROM AUTHOR]

This paper asks how legislative elites—lawmakers serving on statehouse committees with jurisdiction over transportation and energy—set transportation policy and funding agendas and what factors matter for compelling lawmaker policy action or explaining inaction. The role of legislatures in federalist systems has broader implications for the setting of transportation policy agendas, but in this study, we focus on U.S. state legislatures. We report on five focus group discussions conducted with 23 legislative representatives from 19 different states to reveal untapped insights into committee members' perceptions and the factors that drive their attention to certain issues in contemporary U.S. transportation policy. We find that these state-level political elites almost universally see funding as the most important issue and recognize the sector's broad fiscal reliance on motor fuel taxes as structurally unsound, given growing vehicle fuel efficiency and electric vehicle adoption. We find further that, with respect to their own policymaking activities, state lawmakers understand transportation policy and energy transition as distinct issues and appear unable to meet these known challenges by crossing committees to redesign policy. We also see implications of these results more broadly for subnational and provincial governments that, regardless of country setting, must often work across multiple layers of government to set policy agendas in the context of an evolving energy and transportation landscape and that warrant greater attention from policy scholars. [ABSTRACT FROM AUTHOR]

The development of scenic roads is implemented as an integrative tourism and transportation policy in China. As an essential component of scenic road systems, rest areas provide spaces for people to interact with roadside landscapes, enhancing the quality of experiences of recreational motorists. However, the understanding of scenic road rest area usage still lacks empirical evidence. This study developed an empirical approach to explore the affordance actualisation mechanism focused on the context of motorist-rest area interaction. The results outlined a behavioural profile about the usage of rest areas on scenic roads and further revealed that: (1) inspired affordances and anticipated affordances, respectively, acted on people's experiences and satisfaction; (2) the perceptual dimension is more proactive in actualising affordances compared with the physical dimension. These findings contribute to the literature on affordance and the evidence-based planning and design for scenic roads. [ABSTRACT FROM AUTHOR]

This paper analyses the impact of highways on the distribution of economic activities between urban agglomerations and peripheral regions in the European Union. In doing so, I use an empirical strategy based on the land use theory employing disaggregated economic and infrastructure data. To address endogeneity, I apply an IV strategy exploiting non-local highway construction as a source of exogenous variation. I find that highways contribute to the diffusion of urban economic activities into surrounding areas, reducing the income gap between European agglomerations and peripheries. Reduced-form estimations suggest that the gap would have been nearly 3% higher in 2020 if the highway networks of European countries had remained at the level of 1990. The study concludes that transportation infrastructure policies can alleviate regional income disparities, increasing economic convergence between urbanised and less urbanised areas. [ABSTRACT FROM AUTHOR]

Urban railways have become a prominent mode of public transportation within cities owing to their connectivity with other modes of transport and environmental friendliness. Various policies, such as the expansion of metropolitan areas and the development of megacities, have further emphasized the pivotal role of urban railways. Consequently, more railway stations are expected to be constructed in developed cities. However, the temporal variation in boarding and alighting patterns at each railway station is often overlooked. Failing to account for this variation, specifically the differences in peak-hour concentration rates, in railway station design may cause increased conflicts among users owing to concentrated demands during specific time periods, exacerbating congestion and diminishing the appeal of the urban railway systems. Therefore, this study investigated the correlation between the temporal variation in boarding and alighting patterns and the attributes (location) of railway stations in Seoul, South Korea, and analyzed the spatial heterogeneity of this correlation. Initially, the factors influencing the peak-hour concentration rates in railway stations were identified using a linear regression model. Peak hours were defined as morning and afternoon peaks and boarding and alighting were differentiated to account for the directional aspects of temporal variations in boarding and alighting patterns. The correlation between boarding and alighting patterns and the attributes of railway station influence zones was determined, and a geographically weighted regression model was estimated to analyze the spatial heterogeneity of this correlation based on railway station location. The analysis results revealed that railway stations in the southeastern and downtown areas of Seoul exhibited varying impacts of station attributes on boarding and alighting patterns even when the station attribute influence zones were identical. The contribution of this study is to evaluate the priorities of railway projects and its corresponding transportation policies. Regarding the policy goal recently announced by the Korean government, "Achieving Commute Times in 30-min range," our finding will provide a good measure of accessibility whether it succeeds or not. [ABSTRACT FROM AUTHOR]

AbstractProblem, research strategy, and findingsTakeaway for practiceThe transportation sector is the largest contributor of greenhouse gas emissions in the United States. To articulate how cities may combat rising emissions, municipalities throughout the country have produced climate action and sustainability plans that outline strategies to reduce their carbon footprints from transportation. At the same time, last-mile delivery—also known as urban freight—is becoming an increasingly important component of urban transport emissions due to the rise of e-commerce. However, few cities are overtly pursuing policies to reduce emissions from this subsector. In this research we used content analysis to determine the extent to which major cities (based on population and growth) were considering or actively developing sustainable urban freight practices. We developed a simple contextual scale to compare the comprehensiveness of planning trends between cities. This content analysis also identified the strategies those cities are considering. Our findings show that fewer than half (45%) of the studied cities have considered last-mile freight in sustainability planning at all. Of those, only 17 (29%) have articulated an intent to dedicate resources toward achieving that goal.We found that urban freight planning is still in its infancy in terms of actions taken by municipal agencies. Though some cities have comparatively comprehensive plans dedicated to the industry, most are just now scratching the surface. Those cities lacking dedicated last-mile freight plans can learn from those other cities initiating pilots and collecting data from the industry. We point out also, though, that urban freight planning requires an understanding of the stakeholders, namely, delivery companies, and the first step for many cities is to initiate communication and collaboration with the private sector to better understand the environmental impact of urban freight in their city. [ABSTRACT FROM AUTHOR]

Bicycles and other forms of micromobility have been anecdotally used in past disasters to help save lives and improve community recovery. However, research and practice are scarce on this resilient transportation strategy, which limits its usefulness and possible benefits. To fill this gap, our paper investigates the potential role bicycles and micromobility in facilitating (or limiting) disaster response and recovery. Given the lack of exploration on the topic, we convened an online workshop where we conducted brainstorming and focus group discussions with disaster experts from various government agencies, not-for-profit organizations, academia, and policy groups. We present a synthesis of that discussion, along with a review of the existing literature. We conclude there is strong potential for bicycles and micromobility for different disaster phases, hazard types, and groups of people. However, multiple barriers exist related to implementation and safety, suggesting a need for future research and policy in the transportation and emergency management fields and practices. • Feasibility of micromobility to aid evacuation is determined by disaster type, disaster phase, vehicle type, and geography. • Micromobility has the potential to aid both the short-term response and longer-term recovery from natural disasters. • Micromobility is flexible and cheap for resource movement and can navigate roads that are impassable for cars and trucks. • Availability of bikes and micro-modes is both a barrier and a facilitator for use during disaster response. • Many political and coordination barriers remain to make micromobility a part of disaster planning. [ABSTRACT FROM AUTHOR]

Congestion pricing and License Plate Rationing (LPR) are classical transportation policies targeting travel demand. Travelers are constrained to reduce their cars' usage to improve traffic conditions or decrease exhaust gases emissions. They have already been proven effective in the field but have also received some criticism for being unfair or badly perceived by users. On the other side, Tradable Credit and Permit Schemes (TCS/TPS) have been investigated in the literature for more than a decade but have never been implemented in practice. In this paper, we present a large-scale dynamic simulation study, corresponding to the morning peak hour for the Lyon city (France) to benchmark pricing, LPR, TCS, and TPS in terms of modal shift from personal cars to Public Transportation (PT), over a horizon of several days and with different charging schemes. Congestion dynamic in the transportation system is reproduced using a trip-based Macroscopic Fundamental Diagram (MFD) framework. We compute the modal assignment at equilibrium by iteratively solving a Quadratic Problem (QP). The initial formulation, presented in previous work for a single day and a uniform TCS, is extended to account for different days, validity cycles, charging schemes, and TPS. The benchmarking shows that the TCS outperforms LPR in terms of both social cost and carbon emissions. Making credit valid over multiple days reduces the price variability while keeping the same system performances and gain distributions. [ABSTRACT FROM AUTHOR]