ABSTRACT
Many countries around the globe have imposed several response measures to suppress the rapid spread of the COVID-19 pandemic since the beginning of 2020. These measures have impacted routine daily activities, along with their impact on economy, education, social and recreational activities, and domestic and international travels. Intuitively, the different imposed policies and measures have indirect impacts on urban traffic mobility. As a result of those imposed measures and policies, urban traffic flows have changed. However, those impacts are neither measured nor quantified. Therefore, estimating the impact of these combined yet different policies and measures on urban traffic flows is a challenging task. This paper demonstrates the development of an artificial neural networks (ANN) model which correlates the impact of the imposed response measure and other factors on urban traffic flows. The results show that the adopted ANN model is capable of mapping the complex relationship between traffic flows and the response measures with a high level of accuracy and good performance. The predicted values are closed to the observed ones. They are clustered around the regression line, with a coefficient of determination ( R 2 ) of 0.9761. Furthermore, the developed model can be generalized to determine the anticipated demand levels resulted from imposing any of the response measures in the post-pandemic era. This model can be used to manage traffic during mega-events. It can be also utilized for disaster or emergency situations, where traffic flow estimates are highly required for operational and planning purposes.
ABSTRACT
Response measures to contain COVID-19 spread varied from country to country, some imposed a complete lockdown while some imposed partial restrictions. This paper compares the transport impacts of the COVID-19 pandemic for two countries having dissimilar characteristics, Germany and State of Qatar, based on the rates of infection and response measures. Secondary data, obtained from Google mobility reports, and primary data, collected from local agencies, were used for comparison purposes. The secondary data comparison from February 2020 to July 2020 indicated an overall decline in mobility for all commercial activities and an increase was noted for parks and residential locations for Saxony, Germany. For State of Qatar, the mobility was decreased to all places except residential locations. Further, the comparison for traffic volumes and the number of crashes during the first wave of the pandemic indicated that the reduction in traffic volumes, major, and minor crashes was coupled with restrictive measures rather than COVID-19 incidences for both countries. Further, the traffic volumes showed a statistically significant inverse linear relationship with the stringency index for both countries during weekdays as well as weekends. These results suggest that the policy measures are key in governing movement restrictions and containing the spread of pandemic rather than the number of COVID-19 incidences. Further, the authorities should monitor the traffic trends during the pandemic and enforce the traffic rules and regulations as soon as the movement restrictions are lifted.
ABSTRACT
Coronavirus drastically changes people’s travel behavior all over the world. This study aims to investigate the effect of people’s adaptive travel behavior on greenhouse gas (GHG) emission in south Asian countries. We estimate the changes in GHG emission due to the COVID-19 global restrictions during the period of March–May 2020. An online questionnaire survey was conducted to explore the travel distance, the number of trips, and travel modes in pre-pandemic and during the pandemic in Bangladesh, India, Pakistan, and Sri Lanka. The travel distances were converted to GHG emission using IPCC and UNEPA emission factors for different modes of travel. COVID-19 suddenly declined the choice of public transport, taxi, and office transport by 55.80 percent, 33.33 percent, and 55.81 percent, respectively. The choice of walking, car, and motorcycle was increased by 42.85 percent, 16.21 percent, and 9.28 percent, respectively. Avoidance of travel was increased by 229 percent. These sharp changes in the choice of travel modes are attributable to the control measures, risk perception, and adaptive behavior, e.g., remote working, online shopping, virtual teaching-learning and meetings, and stay at home. Travel length for all modes was declined including walking, rickshaw, tuktuk, taxi, private car, office/campus transport, and public transport, while the bicycling length was increased by 40.75 percent. Pandemic reduced emission by 52.34 percent, 22.84 percent, 57.28 percent, 46.05 percent, and 30.16 percent for public transport, private car, office/campus transport, taxi, and motorcycle, respectively. COVID-19 caused a notable 32.81 percent reduction in emission in the month of May 2020 in the study area. The control measures and risk perception of COVID-19 made some sustainable impressions on travel behavior expected to be continued apart from COVID-19 that would contribute to the reduction of 35 percent GHG emission by 2050 that is assigned to the transport sectors in the Paris Climate Agreement. The findings are useful in sustainable transport planning, decision, and the policymaking process to capture travel behavior in pandemics.
ABSTRACT
Ever since the beginning of 2020, the mobility of people and goods all over the world has been extremely limited as a result of movement restrictions imposed by local authorities as part of several other efforts to stop the wide spread of COVID-19 pandemic. The Supreme Committee for Crisis Management in the State of Qatar adopted the policy of incremental preventive measures that were adjusted based on the pandemic status. These actions involved several restrictions, aiming a balance between reducing the pandemic spread and the typical daily activities disturbance. This paper assesses the impact of pandemic response measures on traffic mobility by quantifying the holistic impact of the incremental measures at different stages on traffic volumes and traffic safety. Daily traffic counts from 24 intersections were collected every 15-min for several days, representing the traffic before and after implementing each preventive measure. Besides, a screenline was used to represent the traffic entering and leaving the Central Business District (CBD) in the City of Doha. The results show that the daily traffic demand distribution over the course of day was not affected by those preventive measures. However, an overall demand reduction of 30% in baseline traffic was observed for all studied intersections and the screenline when all preventive measures were active. Moreover, the analysis of traffic violations and the total crashes indicated a drop of 73% and 37% respectively. The results from this assessment will assist decision and policy makers, and planners to prioritize traffic management actions for future needs. Further, the findings can also be utilized for mega-event traffic management in the post-COVID era, such as FIFA World Cup 2022 and 2030 Asian Games.
ABSTRACT
Various measures were recommended or imposed by the governments to control the spread of COVID-19. Travel behaviors are significantly influenced due to such measures. However, people have various travel needs ranging from grocery shopping to work. This study examines the changes that occurred in travel behavior due to the COVID-19 pandemic. Data were collected through an online questionnaire survey that included questions on trip purpose, mode choice, distance traveled, and frequency of trips before and during COVID-19. 1203 responses were collected from various countries around the world. Results explained that trip purpose, mode choice, distance traveled, and frequency of trips for the primary travel were significantly different before and during the pandemic. Further, the majority of trips were made for shopping during the pandemic. There was a significant shift from public transport to private transport and non-motorized modes. People placed a higher priority on the pandemic related concerns while choosing a mode during the pandemic as compared to the general concerns. Gender, car ownership, employment status, travel distance, the primary purpose of traveling, and pandemic-related underlying factors during COVID-19 were found to be significant predictors of mode choice during the pandemic. Outcomes of this study could be useful in transport planning and policymaking during pandemics based on the travel needs of people. In particular, government authorities could utilize such knowledge for planning smart and partial lockdowns. Service providers, e.g., taxi companies and retailers, could use such information to better plan their services and operations.
ABSTRACT
The outbreak of infectious diseases affects people"s lifestyles significantly, as they undertake fewer outdoor activities as a protective measure and to follow government orders of restricted movements. This paper reviewed the scientific literature related to transport and infectious diseases to gain insights into managing such circumstances. The outcomes indicate that the transport sector has a two-fold role during the outbreak of infectious diseases: controlling the spread of infection and assessing the impact of reduced outdoor activities on the transport sector. It was found that local and international travel restrictions, if applied at the initial stages, are effective in controlling the spread of infectious disease;at a later stage, behavioral changes become prominent in limiting the spread. Further, the outbreaks resulted in a significant reduction in mobility, altering traffic patterns with lower peaks and improving traffic safety. The public transport mode share reduced considerably and people preferred cars and active modes. These changes also showed positive impacts on air pollution and water pollution. Further, the air transport and tourism sector were noted to be the hardest hit and will recover slowly. The outcomes from the review will be useful for planners and administrators in managing future emergency conditions better.