Mobility and Recovery in Europe: Impact of the Covid-19 Crisis A European Comparative Analysis

Further to a first benchmark study covering new mobility behaviours and their impact on the road infrastructure, carried out by the European Union Road Federation (ERF), the Confederation of International Contractor's Associations (CICA), the French Federation of Public Works (FNTP), the European Construction Industry federation (FIEC) and Routes de France in 2019-2020, the same group published a second study in September 2021. The objective of that second study was to give a picture of the impact of the crisis caused by the pandemic on the mobility and transport sectors in 11 European countries (Belgium, Croatia, Czech Republic, France, Germany, Italy, Netherlands, Poland, Spain, Sweden, United Kingdom) The approach was to compare the evolution of mobility before and after the emergence of the health crisis. In addition, it would analyse the way in which European countries have adapted their support for transport infrastructures, further to an analysis of National Recovery and Resilience Plans, based on the European Recovery Plan ("Next Generation EU"). Beyond the main trends observed and their impact on mobility patterns and habits, the group also made recommendations on the role of road in the global mobility framework and the necessary adaptation of the road transport infrastructure. © 2023 The Authors. Published by ELSEVIER B.V.

Impacts of COVID-19 on Bike-Share Usage: The case of Daejeon, Korea.

After COVID-19 began spreading through fecal-oral routes, crowded cities introduced social distancing policies. Mobility patterns in urban also changed because of the pandemic and the policies to reduce the infection of it. This study investigates the impact of COVID-19 and related policies such as social-distancing by comparing bike-share demand in Daejeon, Korea. By using big data analytics and data visualization, the study measures differences in bike-sharing demand between 2018-19, before the pandemic, and 2020-21, during the pandemic. According to results, (1) bike-share users tend to travel long distances and cycle more than before the pandemic, (2) bike users choose cycling not for commuting but for transportation during the pandemic, and (3) the pandemic has broadened the spatial borders bike-usages. These results provide meaningful implications for urban planners and policymakers by identifying differences in the ways people use public bikes during the pandemic era.

Car Ownership and Post-COVID Urban Mobility across European Cities

The COVID-19 pandemic has greatly affected households' mobility habits and choices in the past two years. Scarce evidence is available concerning medium term decisions such as the purchase or sale of a private vehicle. This work aims to explore the factors that have influenced households' decisions to buy or sell a private car due to the pandemic and foresee how these decisions might influence their travel behaviour in the next few years. To achieve this goal, an EU-wide survey gathering information from 21 European cities was carried out during the second term of 2021, when lockdowns were no longer in place, but some mobility and sanitary restrictions were still maintained. The survey focuses on the impact of the pandemic and the consequent mobility restrictions on the transport habits and preferences of the respondents. The questionnaire collected socio-economic characteristics and mobility habits of 10,152 individuals. Interestingly, the analysis of the survey does not provide any evidence of a reduction of motorization rates for teleworkers. On the contrary, both partial and full-time teleworkers have bought significantly more cars than the rest of the groups. These findings greatly contrast with the fact that changes in daily habits resulting from the adoption of teleworking regimes are the main cause of reductions in car use among car buyers. This result suggests that further incentives for car ownership reduction are needed to harness the full potential of teleworking for decreasing car dependency. A positive relation between number of cars owned before COVID and car purchases has been found, pointing out that these purchases are probably not solving accessibility limitations for car-less households. Finally, a positive relation is also observed between car purchases and increased use of shared mobility services. © 2023 The Authors. Published by ELSEVIER B.V.

Mobility and Recovery in Europe: Impact of the Covid-19 Crisis A European Comparative Analysis

Further to a first benchmark study covering new mobility behaviours and their impact on the road infrastructure, carried out by the European Union Road Federation (ERF), the Confederation of International Contractor's Associations (CICA), the French Federation of Public Works (FNTP), the European Construction Industry federation (FIEC) and Routes de France in 2019-2020, the same group published a second study in September 2021. The objective of that second study was to give a picture of the impact of the crisis caused by the pandemic on the mobility and transport sectors in 11 European countries (Belgium, Croatia, Czech Republic, France, Germany, Italy, Netherlands, Poland, Spain, Sweden, United Kingdom) The approach was to compare the evolution of mobility before and after the emergence of the health crisis. In addition, it would analyse the way in which European countries have adapted their support for transport infrastructures, further to an analysis of National Recovery and Resilience Plans, based on the European Recovery Plan ("Next Generation EU"). Beyond the main trends observed and their impact on mobility patterns and habits, the group also made recommendations on the role of road in the global mobility framework and the necessary adaptation of the road transport infrastructure. © 2023 The Authors. Published by ELSEVIER B.V.

Equity Implications of Ride-Hail Travel during COVID-19 in California.

COVID-19 has shocked every system in the U.S., including transportation. In the first months of the pandemic, driving and transit use fell far below normal levels. Yet people still need to travel for essential purposes like medical appointments, buying groceries, and-for those who cannot work from home-to work. For some, the pandemic may exacerbate extant travel challenges as transit agencies reduce service hours and frequency. As travelers reevaluate modal options, it remains unclear how one mode-ride-hailing-fits into the transportation landscape during COVID-19. In particular, how does the number of ride-hail trips vary across neighborhood characteristics before versus during the pandemic? And how do patterns of essential trips pre-pandemic compare with those during COVID-19? To answer these questions, we analyzed aggregated Uber trip data before and during the first two months of the COVID-19 pandemic across four regions in California. We find that during these first months, ride-hail trips fell at levels commensurate with transit (82%), while trips serving identified essential destinations fell by less (62%). Changes in ride-hail use were unevenly distributed across neighborhoods, with higher-income areas and those with more transit commuters and higher shares of zero-car households showing steeper declines in the number of trips made during the pandemic. Conversely, neighborhoods with more older (aged 45+) residents, and a greater proportion of Black, Hispanic/Latinx, and Asian residents still appear to rely more on ride-hail during the pandemic compared with other neighborhoods. These findings further underscore the need for cities to invest in robust and redundant transportation systems to create a resilient mobility network.

Mobility Dynamics amid COVID-19 with a Case Study in Tennessee.

The year 2020 has marked the spread of a global pandemic, COVID-19, challenging many aspects of our daily lives. Different organizations have been involved in controlling this outbreak. The social distancing intervention is deemed to be the most effective policy in reducing face-to-face contact and slowing down the rate of infections. Stay-at-home and shelter-in-place orders have been implemented in different states and cities, affecting daily traffic patterns. Social distancing interventions and fear of the disease resulted in a traffic decline in cities and counties. However, after stay-at-home orders ended and some public places reopened, traffic gradually started to revert to pre-pandemic levels. It can be shown that counties have diverse patterns in the decline and recovery phases. This study analyzes county-level mobility change after the pandemic, explores the contributing factors, and identifies possible spatial heterogeneity. To this end, 95 counties in Tennessee have been selected as the study area to perform geographically weighted regressions (GWR) models. The results show that density on non-freeway roads, median household income, percent of unemployment, population density, percent of people over age 65, percent of people under age 18, percent of work from home, and mean time to work are significantly correlated with vehicle miles traveled change magnitude in both decline and recovery phases. Also, the GWR estimation captures the spatial heterogeneity and local variation in coefficients among counties. Finally, the results imply that the recovery phase could be estimated depending on the identified spatial attributes. The proposed model can help agencies and researchers estimate and manage decline and recovery based on spatial factors in similar events in the future.

Strangers On This Road We Are On: A Literature Review of Pooling in On-Demand Mobility Services

Ridepooling service options introduced by transportation network companies (TNCs) and microtransit companies provide opportunities to increase shared-ride trips in vehicles, thereby improving congestion and environmental factors. This paper reviews the existing literature available on ridepooling and related services, specifically focusing on pooling options available from on-demand transportation companies. The paper summarizes the existing knowledge on the use of pooled-ride services, factors in travel mode service options for customers, available policy and planning strategies to incentivize sharing vehicles, and effects of the COVID-19 pandemic on shared-ride travel. Overall, research shows that ridepooling options are more likely to be considered by public transit users who have lower household incomes, while ridesourcing users of upperclass backgrounds are less likely to consider moving to a shared-ride service. Travel time and trip cost are the most important factors for travelers determining whether to use a ridesplitting or microtransit service rather than a ride-alone ridesourced trip. Existing policy and planning tools targeting pooled travel or TNCs can be expanded on and specified for on-demand ridepooling services, such as offering better incentives to use shared vehicles and increased access to curb areas or travel lanes, but the most effective strategies will include increasing the user costs for parking or riding alone. © National Academy of Sciences.

Shared Mobility Opportunities and Their Computational Challenges for Improving Health-Related Quality of Life

Shared mobility has emerged in urban spaces as an alternative to owning and maintaining a vehicle, by allowing flexible and short-term mobility services at low costs. These mobility options act as promising sources of trips benefiting people in vulnerable groups and enabling them to access essential services such as healthcare and providing transport during emergency evacuations. Shared mobility services can also make the cities more sustainable and healthy for all inhabitants by reducing the number of circulating vehicles. Fewer vehicles in the urban traffic makes the air cleaner and the environment less noisy, reducing risks of respiratory, and cardiovascular diseases and improving the people's health-related quality of life. However, managing shared mobility services intensifies transport challenges. Amid these challenges are reducing operational costs and diminishing health hazards such as the ones posed by COVID-19. © 2021 Elsevier Ltd. All rights reserved

Sharing: Attitudes and Perceptions

Emerging shared mobility services refer to the shared used of travel modes such as a car or a micromobility vehicle that grant users short term, on-demand access to these travel options. Particularly in the last decade, shared mobility services, largely enabled by smartphone technology, have considerably changed the landscape of the transportation system. As the public is learning and adapting to these new mobility options, urban transportation systems are bending toward a service-oriented framework. Public attitudes and perceptions of these novel travel modes play a determining role in adoption of transportation services are constantly evolving with changes in the vehicle technology and service models of shared mobility services. This, however, presents the interesting opportunity to examine how the public understands transportation and shared mobility, a lens through which lessons can be learned to inspire better transportation planning and policymaking. This chapter reviews four main shared mobility services: carsharing, ridesourcing, bikesharing, and scooter sharing to highlight the evolution of public attitudes and perceptions towards the shared mobility services. © 2021 Elsevier Ltd. All rights reserved

Post-pandemic shared mobility and active travel in Alabama: A machine learning analysis of COVID-19 survey data.

The COVID-19 pandemic has had unprecedented impacts on the way we get around, which has increased the need for physical and social distancing while traveling. Shared mobility, as an emerging travel mode that allows travelers to share vehicles or rides has been confronted with social distancing measures during the pandemic. On the contrary, the interest in active travel (e.g., walking and cycling) has been renewed in the context of pandemic-driven social distancing. Although extensive efforts have been made to show the changes in travel behavior during the pandemic, people's post-pandemic attitudes toward shared mobility and active travel are under-explored. This study examined Alabamians' post-pandemic travel preferences regarding shared mobility and active travel. An online survey was conducted among residents in the State of Alabama to collect Alabamians' perspectives on post-pandemic travel behavior changes, e.g., whether they will avoid ride-hailing services and walk or cycle more after the pandemic. Machine learning algorithms were used to model the survey data (N = 481) to identify the contributing factors of post-pandemic travel preferences. To reduce the bias of any single model, this study explored multiple machine learning methods, including Random Forest, Adaptive Boosting, Support Vector Machine, K-Nearest Neighbors, and Artificial Neural Network. Marginal effects of variables from multiple models were combined to show the quantified relationships between contributing factors and future travel intentions due to the pandemic. Modeling results showed that the interest in shared mobility would decrease among people whose one-way commuting time by driving is 30-45 min. The interest in shared mobility would increase for households with an annual income of $100,000 or more and people who reduced their commuting trips by over 50% during the pandemic. In terms of active travel, people who want to work from home more seemed to be interested in increasing active travel. This study provides an understanding of future travel preferences among Alabamians due to COVID-19. The information can be incorporated into local transportation plans that consider the impacts of the pandemic on future travel intentions.

Definition of the e-Scooter Sharing Stations Number and Location Under a Lack of Data: A Case Study of the City District in Dnipro

In Ukrainian cities, the number of users of bicycles, usual and electric scooters, and e-unicycles increased in recent years. All these vehicles are a direct alternative to walking trips or short-distance transport trips. During the COVID-19 pandemic, the micromobility has become a safe option to travel in the open air which ensured the possibility to keep social distance and reduce the number of contacts in comparison with public transport. This paper presents the approach to defining the rational number and location of e-scooter sharing stations under limited data. To estimate the number of the sharing stations, the station capacity, potential daily demand for e-scooter trips and the locations of available e-scooters were used. The locations of sharing stations were defined concerning walking accessibility, demand coverage and remoteness from the shortest path of the vehicle commissioned to collect the scooters for recharging or replace the scooter batteries on-site. The research was conducted by the example of Sobornyi district in Dnipro, Ukraine. Apart from the number and location of sharing stations, the potential flows of e-scooter riders were modeled. These findings are relevant because they can provide local authorities and sharing operators with the information for well-grounded decisions on public space and street design, micromobility infrastructure extension as well as planning of the sharing system performance indicators. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Micromobility services before and after a global pandemic: impact on spatio-temporal travel patterns

Sudden changes in urban mobility were caused due to the COVID-19 pandemic. The impacts are yet to be furtherly measured and analyzed. Our article uses GPS records provided by three different micromobility operators in Madrid to study how the pandemic affected their service usage and its relationships with land use. Thus, spatio-temporal travel patterns are compared between pre-COVID 19 (from January 2019 to February 2020) and COVID times (from March to December 2020). Additionally, multiple regression analyses are conducted to assess how the two scenarios differentiate in relation to micromobility trips, generated or attracted, to or from different land uses, and during morning or afternoon peak hours. Results show that the most pandemic-resilient shared mode is bike-sharing, and that COVID-19 has caused a downfall in micromobility trips of approximately 10%, which is relatively lower compared to the 80% ridership drop reported by the public transport system. Our models reveal that residential and commercial areas gained importance after the pandemic, while workplace locations (office and industrial), educational and transport facilities lost relevance with teleworking and online studying. These findings could help authorities to plan future policies and improve the infrastructure needed to promote micromobility services. © 2022 Taylor & Francis Group, LLC.

Strangers On This Road We Are On: A Literature Review of Pooling in On-Demand Mobility Services

Ridepooling service options introduced by transportation network companies (TNCs) and microtransit companies provide opportunities to increase shared-ride trips in vehicles, thereby improving congestion and environmental factors. This paper reviews the existing literature available on ridepooling and related services, specifically focusing on pooling options available from on-demand transportation companies. The paper summarizes the existing knowledge on the use of pooled-ride services, factors in travel mode service options for customers, available policy and planning strategies to incentivize sharing vehicles, and effects of the COVID-19 pandemic on shared-ride travel. Overall, research shows that ridepooling options are more likely to be considered by public transit users who have lower household incomes, while ridesourcing users of upper-class backgrounds are less likely to consider moving to a shared-ride service. Travel time and trip cost are the most important factors for travelers determining whether to use a ridesplitting or microtransit service rather than a ride-alone ridesourced trip. Existing policy and planning tools targeting pooled travel or TNCs can be expanded on and specified for on-demand ridepooling services, such as offering better incentives to use shared vehicles and increased access to curb areas or travel lanes, but the most effective strategies will include increasing the user costs for parking or riding alone.

Carsharing Vehicle Fleet Selection from the Frequent User’s Point of View

Short-term car rental services, i.e., carsharing, is a solution that has been developing better and better in urban transport systems in recent years. Along with intensive expansion, service providers have to face an increasing number of challenges to compete with each other. One of them is meeting the expectations of customers about the fleet of vehicles offered in the system. While this aspect is noticed in the literature review mainly in terms of fleet optimization and management, there is a research gap regarding the appropriate selection of vehicle models. In response, the article was dedicated to identifying the vehicles that were best suited to carsharing systems from the point of view of frequent customers. The selection of appropriate vehicles was treated as a multi-criteria decision issue, therefore the study used one of the multi-criteria decision support methods—ELECTRE III. The work focuses on researching the opinions of users (experts) who often use carsharing services in Poland. The study included a list of the most popular vehicles in Europe in 2021, including classic, electric, and hybrid cars, and a list of 11 evaluation criteria. The research results indicate for frequent users the advantage of conventional drive vehicles over electric and hydrogen vehicles. Moreover, they indicate that the best vehicles are relatively large cars (European car segments C and D) with the greatest possible length, boot capacity, engine power, number of safety systems, and quality. On the other hand, the least important issues are the number of seats in the vehicle and the number of doors. Interestingly, the vehicles selected by frequent users questioned the concept of small city cars, which occupied a small public space on which carsharing was supposed to focus. The results obtained support the operators of carsharing services in making fleet decisions.

Exploring the Role of Shared Mobility in Alleviating Private Car Dependence and On-Road Carbon Emissions in the Context of COVID-19

Shared mobility is becoming increasingly popular worldwide, and travelers show more complex choice preferences during the post-pandemic era. This study explored the role of shared mobility in the context of coronavirus disease (COVID-19) by comparing the travel mode choice behavior with and without shared mobility. Considering the shared mobility services of ride-hailing, ride-sharing, car-sharing, and bike-sharing, the stated preference survey was designed, and the mixed logit model with panel data was applied. The results show that if shared mobility is absent, approximately 50% of motorized mobility users and 84.62% of bike-sharing adopters will switch to using private car and public transport, respectively. The perceived pandemic severity positively affects the usage of car-sharing and bike-sharing, while it negatively affects the ride-sharing usage. Under different pandemic severity levels, the average probabilities of private car choice with and without shared mobility are 38.70 and 57.77%, respectively;thus, shared mobility would alleviate the dependence on private car in post-pandemic future. It also helps to decrease the on-road carbon emissions when the pandemic severity is lower than 53. These findings suggest policymakers to maintain the shared mobility ridership and simultaneously contain the pandemic. Additionally, pricing discount and safety enhancement are more effective than reducing detour time to protect ride-sharing against COVID-19. Copyright © 2022 Zhang, Shao, Wang, Huang, Mi and Zhuang.

Roadmap for Future Mobility Development Supporting Bangkok Urban Living in 2030

This study demonstrates how to develop a roadmap guiding a company’s technology and innovation for future mobility by integrating the results from foresight and scenario analysis. The key drivers and trends influencing the urban development of Bangkok in the next 10 years were determined through the environmental scanning approach. The participatory approach was then applied to get stakeholders involved to enrich scenario thinking. The participants were invited from many social networks involved in city development in Bangkok. The scenario development was framed according to livability and city infrastructure development. As mobility is always the key issue for big cities, future development for mobility can be addressed in terms of different aspects such as filling stations, clean fuel, public transportation, shared mobility platforms, or last-mile traveling. A roadmap to guide future development of shared mobility was developed based on the analysis of the particular company in the case study.

Willingness-to-pay for shared automated mobility using an adaptive choice-based conjoint analysis during the COVID-19 period

Due to recent technological developments, both academia and the market have become interested in utilizing shared autonomous vehicles (SAVs). Gaining insight into preferences and priorities for using the next generation of shared mobility was the primary motivation for this study. The goal is to explore the willingness-to-pay (WTP) for a shared mobility service using a detailed user preference analysis for alternative automation types and incentive and policy options. The data was collected between March to May 2020 during the COVID-19 lockdown period in the United States via an online survey and analyzed by the Adaptive Choice-Based Conjoint Analysis (ACBC) method. The results of this study show that respondents distinctly preferred fully automated vehicles (SAVs) over shared human-driven vehicles (SHVs), tended to use a door-to-door service rather than a pooled service with a short walking distance, and were more interested in using advanced built-in amenities in the vehicle, not inclined to share their travel with others, and likely to pay less money to avoid potential delays. Comparing the results before and during the COVID-19 period showed that respondents afterward have markedly less willingness-to-share their trips with other riders compared to the survey analysis done before the COVID-19 period.

Ride acceptance behaviour of ride-sourcing drivers

The performance of ride-sourcing services such as Uber and Lyft is determined by the collective choices of individual drivers who are not only chauffeurs but private fleet providers. In such a context, ride-sourcing drivers are free to decide whether to accept or decline ride requests assigned by the ride-hailing platform. Drivers’ ride acceptance behaviour can significantly influence system performance in terms of riders’ waiting time (associated with the level of service), drivers’ occupation rate and idle time (related to drivers’ income), and platform revenue and reputation. Hence, it is of great importance to identify the underlying determinants of the ride acceptance behaviour of drivers. To this end, we collected a unique dataset from ride-sourcing drivers working in the United States and the Netherlands through a cross-sectional stated preference experiment designed based upon disparate information conveyed to the respondents. Using a choice modelling approach, we estimated the effects of various existing and hypothetical attributes influencing the ride acceptance choice. Employment status, experience level with the platform, and working shift are found to be the key individual-specific determinants. Part-time and beginning drivers who work on midweek days (Monday-Thursday) have a higher tendency to accept ride offers. Results also reveal that pickup time, which is the travel time between the driver’s location and the rider’s waiting spot, has a negative impact on ride acceptance. Moreover, the findings suggest that a guaranteed tip (i.e., the minimum amount of tip that is indicated upfront by the prospective rider, a feature that is currently not available) and an additional income due to surge pricing are valued noticeably higher than trip fare. The provided insights can be used to develop customised matching and pricing strategies to improve system efficiency. Since the study has been conducted during the COVID-19 crisis, the potential implications of the pandemic on ride acceptance behaviour have been examined using an Integrated Choice and Latent Variable (ICLV) model. The results show that drivers with a higher sensitivity to the COVID-19 effects tend to have a lower acceptance rate.

The Impact of COVID-19 on Travel Mode Choice Behavior in Terms of Shared Mobility: A Case Study in Beijing, China.

Shared mobility is growing rapidly and changing the mobility landscape. The COVID-19 pandemic has complicated travel mode choice behavior in terms of shared mobility, but the evidence on this impact is limited. To fill this gap, this paper first designs a stated preference survey to collect mode choice data before and during the pandemic. Different shared mobility services are considered, including ride hailing, ride sharing, car sharing, and bike sharing. Then, latent class analysis is used to divide the population in terms of their attitudes toward shared mobility. Nested logit models are applied to compare travel mode choice behavior during the two periods. The results suggest that shared mobility has the potential to avoid the high transmission risk of public transport and alleviate the intensity of private car use in the COVID-19 context, but this is limited by anxiety about shared spaces. As the perceived severity of the pandemic increases, preference for ride hailing and ride sharing decreases, and a price discount for ride hailing is more effective than that for ride sharing at maintaining the ridership despite the impact of COVID-19. These findings contribute to understanding the change in travel demand and developing appropriate strategies for shared mobility services to adapt to the pandemic.

Travel Mode Choice Analysis with Shared Mobility in Context of COVID-19

To analyze the impact of COVID-19 on the travel mode choice behavior with diverse shared mobility services, this study designed the stated preference (SP) questionnaire for the multi-modal transportation system which include conventional travel modes, ride hailing, ride sharing, car sharing, and bike sharing. The mixed Logit models with panel data were proposed to investigate the travel mode choices before and during COVID-19. The influence differences of explanatory variables are compared, and the joint effects of perceived pandemic severity and mode choice inertia are examined. Based on the elasticity analysis, the mode choice preferences are predicted corresponding to different management policies under COVID-19 pandemic. The results indicate that the perception to pandemic severity has significant impacts on the ridership of ride sharing and car sharing, and the mode choice inertia obviously affects the usage of ride hailing, car sharing, and bike sharing. When the perceived pandemic severity reduces to 30%~50%, the strategy of increasing parking charge to 1.6~3.0 times would reduce the usage of private car to pre-pandemic condition, and the car sharing with lower close contact risk could become a main substitute. When the perceived pandemic severity is higher than 60%, the strategy of increasing the travel safety of ride sharing to 1.4~3.6 times would improve the ridership. Copyright © 2022 by Science Press.