ABSTRACT
Travel choices in terms of means of transport and frequencies have changed during the recent pandemic period due to mobility restrictions, the growing fear of contagion and, especially in some months, the reduction of public transport capacity during the phases of the pandemic (especially for low demand areas). These trends must be analysed in order to optimize the implementation of possible complementary solutions to fill the deficit of local public transport (TPL) by introducing for example the Demand Responsive Transport services (DRT). A preliminary analysis is useful to identify the most efficient, effective and sustainable solutions in the various contexts, taking into account users and their motivation to travel. A growing need for "on-demand" mobility is linked to the increase in the number of elderly and disabled people. With a lack of alternative services and a reluctance to bear the burden and cost of ownership of vehicles, transport infrastructure will be particularly important to this aging population. Therefore, the improvement of transport services must consider some main characteristics of this modal choice are: being user-oriented;guarantee the accessibility of the service via the web, on specific platforms available on fixed and mobile devices and also enjoy the versatility of use with reference to the areas and users to be served. The present work, therefore, focuses on an evaluation of the literature, defining the main characteristics of DRT in Europe over the last twenty years. The results lay the foundations for a better planning of the service in the post-pandemic phase and a diffusion of bottom-up approaches for the calibration of the service itself through the dissemination of survey campaigns. © 2023 The Authors. Published by ELSEVIER B.V.
ABSTRACT
Travel choices in terms of means of transport and frequencies have changed during the recent pandemic period due to mobility restrictions, the growing fear of contagion and, especially in some months, the reduction of public transport capacity during the phases of the pandemic (especially for low demand areas). These trends must be analysed in order to optimize the implementation of possible complementary solutions to fill the deficit of local public transport (TPL) by introducing for example the Demand Responsive Transport services (DRT). A preliminary analysis is useful to identify the most efficient, effective and sustainable solutions in the various contexts, taking into account users and their motivation to travel. A growing need for "on-demand" mobility is linked to the increase in the number of elderly and disabled people. With a lack of alternative services and a reluctance to bear the burden and cost of ownership of vehicles, transport infrastructure will be particularly important to this aging population. Therefore, the improvement of transport services must consider some main characteristics of this modal choice are: being user-oriented;guarantee the accessibility of the service via the web, on specific platforms available on fixed and mobile devices and also enjoy the versatility of use with reference to the areas and users to be served. The present work, therefore, focuses on an evaluation of the literature, defining the main characteristics of DRT in Europe over the last twenty years. The results lay the foundations for a better planning of the service in the post-pandemic phase and a diffusion of bottom-up approaches for the calibration of the service itself through the dissemination of survey campaigns. © 2023 The Authors. Published by ELSEVIER B.V.
ABSTRACT
In order to explore the choice behavior of residents' travel mode in the post-COVID-19 era, a choice behavior experiment was conducted. A mixed Logit model and a latent class conditional Logit model of travel mode choice were constructed based on the data obtained from questionnaire surveys. Stata software was used to calibrate the model parameters, and the main factors influencing residents' travel mode choices were obtained. The results show that both models reflect the heterogeneity of individual travel mode choices. Compared with the mixed Logit model, the latent class conditional Logit model has an improvement of 13% in the goodness of fit and an increase of 3.03% in the prediction accuracy, which provides an effective tool for analyzing individual heterogeneity of travel behavior under public health emergencies. The latent class conditional Logit model divides residents into four and five groups according to the two scenarios of low and medium risk areas. From the perspective of travel mode attributes, the waiting time and the traveling time have become the most important influencing factors for residents to choose the travel modes. From the perspective of personal socio-economic attributes, women with higher incomes are more inclined to choose private cars to travel. The older are more sensitive to travel costs, and men are more willing to choose bus and subway travel. Copyright © 2022 by Science Press.
ABSTRACT
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.
ABSTRACT
The COVID-19 has created significant impacts on the economy and individual life around the world. Various countries and cities have adopted corresponding control measures to reduce transport activities and maintain social distance to combat the spread of COVID-19. In the circumstances, residents only maintained essential travel to ensure a normal and fundamental life. In order to explore the impacts of the epidemic and control measures on individually essential travel, we have collected 513 questionnaires between February and March 2020 in China to investigate the various characteristics of essential travel. Using a multivariate logistic regression model, we examine the major factors that potentially impact the mode choices of essential travel. Results show that various socioeconomic, transport supply, health concern and travel purpose have significantly influenced travel mode choices of essential travel. The concept of essential travel will, in the era of port-pandemic, have profound implications on transportation policy making, especially on how to improve the fundamental welfare of the disadvantaged population.