ABSTRACT
The dataset consists of survey data on pedestrian crosswalk usage behavior in high-density urban areas of a developing country, specifically collected from Dhaka, the capital city of Bangladesh. Data were gathered through a questionnaire survey conducted at twelve key locations, covering eight attributes related to crosswalk behavior and the demographic details of respondents. The survey yielded 682 valid responses, focusing on factors such as the suitability of crosswalk locations, guard rails, and lighting. The dataset is structured to support analyses using supervised machine learning techniques, facilitating reproducibility, secondary analysis, and policy development for pedestrian safety improvements. Furthermore, the dataset can be reused for cross-validation of future studies, comparison with pedestrian behavior in similar urban settings, and the development of predictive models to enhance pedestrian infrastructure in other developing regions.
ABSTRACT
To ensure safety against the COVID-19, along with all other countries, Bangladesh as a least-developed country needs to deal with the changes in travel behavior, particularly changes in mode choice behavior. As Dhaka has been marked as a hotspot for the virus contagion, this paper has focused on the changes in mode choice behavior of Dhaka people due to the COVID-19 pandemic while they are on the road. A web-based questionnaire survey was conducted to capture the information on mode preferences and perspectives on travel characteristics for commute and discretionary trips before and during COVID-19. Multinomial Logit (MNL) model based on a utility function has been used to investigate the significance of the socio-demographic attributes and travel characteristics of the trips on the mode choice behavior and to calculate the maximum utility of the mode choice. This study highlighted some noticeable changes in perspective towards mode choice. People prefer walking, private cars, and rickshaw more during the pandemic as they feel these modes are more reliable, available, and cost-effective in this crucial time. Usage of public transportation dropped drastically for discretionary purposes. Additionally, usage of the on-demand vehicle increased during the pandemic as a large portion of commuters shifted to on-demand vehicles from public transportation. Furthermore, this paper suggested some viable policy-making implications to cope with the current pandemic and relatable future national and global crises. Finally, the paper concludes by suggesting some future research insights.
ABSTRACT
In response to Coronavirus 2019 (COVID-19) pandemic, Bangladesh enforced social distancing measures to mitigate the virus transmission rate through lockdowns. However, it is challenging for people to follow through and stay home in developing nations where socio-economic conditions are divergent from developed countries. This research aims to investigate COVID-19 induced travel pattern changes of residents and significant demographic factors affecting the trip generation in Dhaka City, the most densely populated Bangladeshi city. A questionnaire survey was used to extract information on demographic characteristics of respondents in Dhaka City and their travel patterns in the pre-pandemic era and during the pandemic. Analyses reveal striking differences in work trips except for workers and craftsmen. The use of telemedicine facilities is noticeable. Preference for public transport has decreased yet a decent percentage (9%) of people use buses during the pandemic. However, non-motorized modes are also very popular (19.93%) in the pandemic. The findings offer major implications for transportation planners and policymakers on how to dynamically plan for such crisis by combining a range of strategies so that safe and sustainable urban mobility and reduction of unnecessary travel demand can be ensured.