Modeling the COVID-19 Travel Choices in Colombia and India: A Hybrid Multiple Discrete-Continuous Nested Extreme Value Approach.

The COVID-19 pandemic has affected many daily activities, primarily as a result of the perceived contagion risk and government restrictions to mitigate the spread of the virus. To this end, drastic changes in the trip choices for commuting to work have been reported and studied, mostly through descriptive analysis. On the other hand, modeling-based research that can simultaneously understand both changes in mode choice and its frequency at an individual level has not been much used in existing studies. As such, this study aims to understand the changes in mode-choice preference and the frequency of trips, comparing pre-COVID with during-COVID scenarios, in two different countries of the Global South: Colombia and India. A hybrid multiple discrete-continuous nested extreme value model was implemented using the data obtained from online surveys in Colombia and India during the early COVID-19 period of March and April 2020. This study found that, in both countries, utility related to active modes (more used) and public transportation (less used) changed during the pandemic. In addition, this study highlights potential risks in likely unsustainable futures where there may be increased use of private vehicles such as cars and motorcycles, in both countries. It was also identified that perceptions toward government responses had a significant impact on the choices in Colombia, though this was not the case in India. These results may help decision makers focus on public policies to encourage sustainable transportation by avoiding the detrimental long-term behavioral changes resulting from the COVID-19 pandemic.

Willingness to pay for COVID-19 mitigation measures in public transport and paratransit in low-income countries.

In order to combat the spread of COVID-19, various measures were taken in most countries to make public transit and paratransit safer. These additional measures, which include restrictions on number of passengers, provision of hand sanitisers and face coverings, and more frequent cleaning, add to the costs of operations or reduce profitability. The resulting financial pressure on the transport operators raises an important question on who pays for these additional measures. In most countries, this has been covered by one-time government bailouts to operators or strategies to increase fare, the latter of which directly affects the users. However, even without these interventions, there could be a demand and as such willingness to pay (WTP) for some of these intervention measures from the consumers concerned about safety. Knowing such WTP will not only help operators set their fare, but also help the governments decide the appropriate bailout needed. This paper addresses the issue by estimating the user's willingness to pay for selected COVID-19 mitigation measures in public transport and paratransit (motorcycle taxis) using survey data collected from two cities in low-income countries as case studies - Kampala, Uganda and Dhaka, Bangladesh. For public transport, these measures are - (1) social distancing (passenger loading at half capacity), and (2) mandatory hand sanitisation and increased cleaning of surfaces, while for paratransit, they are - (1) provision of a transparent shield between the rider and the passenger, and (2) provision of cleaned helmets at the start of each trip. The study analyses stated preference data using the utility maximisation framework and finds that the implementation or provision of COVID-19 mitigation measures improves the attractiveness of the associated public transport or paratransit alternatives, and transport users make trade-offs between safety and cost when making travel decisions. We find positive willingness to pay for all four mitigation measures, suggesting potential existence of a market for these measures. We also find that the typical mode choice factors such as costs, travel time and convenience became less important during the pandemic and the safety measures became more important considerations.

Impacts of COVID-19-Related Non-Pharmaceutical Interventions on Mobility and Accidents in Bangladesh.

Transport plays a major role in spreading contagious diseases such as COVID-19 by facilitating social contacts. The standard response to fighting COVID-19 in most countries has been imposing a lockdown-including on the transport sector-to slow down the spread. Though the Government of Bangladesh also imposed a lockdown quite early, it was forced to relax the lockdown for economic reasons. This motivates this study to assess the interaction between various non-pharmaceutical intervention (NPI) policies and transport sector outcomes, such as mobility and accidents, in Bangladesh. The study explores the effect of NPIs on both intra- and inter-regional mobility. Intra-regional mobility is captured using Google mobility reports which provide information about the number of visitors at different activity locations. Inter-regional, or long-distance, mobility is captured using vehicle count information from toll booths on a major bridge. Modeling shows that, in most cases, the policy interventions had the desired impact on people's mobility patterns. Closure of education institutes, offices, public transport, and shopping malls reduced mobility at most locations. The closure of garment factories reduced mobility for work and at transit stations only. Mobility was increased at all places except at residential locations, after the wearing of masks was made mandatory. Reduced traffic because of policy interventions resulted in a lower number of accidents (crashes) and related fatalities. However, mobility-normalized crashes and fatalities increased nationally. The outcomes of the study are especially useful in understanding the differential impacts of various policy measures on transport, and thus would help future evidence-based decision-making.

Meeting sustainable development goals via robotics and autonomous systems.

Robotics and autonomous systems are reshaping the world, changing healthcare, food production and biodiversity management. While they will play a fundamental role in delivering the UN Sustainable Development Goals, associated opportunities and threats are yet to be considered systematically. We report on a horizon scan evaluating robotics and autonomous systems impact on all Sustainable Development Goals, involving 102 experts from around the world. Robotics and autonomous systems are likely to transform how the Sustainable Development Goals are achieved, through replacing and supporting human activities, fostering innovation, enhancing remote access and improving monitoring. Emerging threats relate to reinforcing inequalities, exacerbating environmental change, diverting resources from tried-and-tested solutions and reducing freedom and privacy through inadequate governance. Although predicting future impacts of robotics and autonomous systems on the Sustainable Development Goals is difficult, thoroughly examining technological developments early is essential to prevent unintended detrimental consequences. Additionally, robotics and autonomous systems should be considered explicitly when developing future iterations of the Sustainable Development Goals to avoid reversing progress or exacerbating inequalities.

Face mask mandates and risk compensation: an analysis of mobility data during the COVID-19 pandemic in Bangladesh.

INTRODUCTION: Concerns have been raised about the potential for risk compensation in the context of mask mandates for mitigating the spread of COVID-19. However, the debate about the presence or absence of risk compensation for universal mandatory mask-wearing rules-especially in the context of COVID-19-is not settled yet. METHODS: Mobility is used as a proxy for risky behaviour before and after the mask mandates. Two sets of regressions are estimated to decipher (any) risk-compensating effect of mask mandate in Bangladesh. These include: (1) intervention regression analysis of daily activities at six types of locations, using pre-mask-mandate and post-mandate data; and (2) multiple regression analysis of daily new COVID-19 cases on daily mobility (lagged) to establish mobility as a valid proxy. RESULTS: (1) Statistically, mobility increased at all five non-residential locations, while home stays decreased after the mask mandate was issued; (2) daily mobility had a statistically significant association on daily new cases (with around 10 days of lag). Both significances were calculated at 95% confidence level. CONCLUSION: Community mobility had increased (and stay at home decreased) after the mandatory mask-wearing rule, and given mobility is associated with increases in new COVID-19 cases, there is evidence of risk compensation effect of the mask mandate-at least partially-in Bangladesh.

A comparative total cost of ownership analysis of heavy duty on-road and off-road vehicles powered by hydrogen, electricity, and diesel.

This study investigated the cost competitiveness, using total cost of ownership (TCO) analysis, of hydrogen fuel cell electric vehicles (FCEVs) in heavy duty on and off-road fleet applications as a key enabler in the decarbonisation of the transport sector and compares results to battery electric vehicles (BEVs) and diesel internal combustion engine vehicles (ICEVs). Assessments were carried out for a present day (2021) scenario, and a sensitivity analysis assesses the impact of changing input parameters on FCEV TCO. This identified conditions under which FCEVs become competitive. A future outlook is also carried out examining the impact of time-sensitive parameters on TCO, when net zero targets are to be reached in the UK and EU. Several FCEVs are cost competitive with ICEVs in 2021, but not BEVs, under base case conditions. However, FCEVs do have potential to become competitive with BEVs under specific conditions favouring hydrogen, including the application of purchase grants and a reduced hydrogen price. By 2050, a number of FCEVs running on several hydrogen scenarios show a TCO lower than ICEVs and BEVs using rapid chargers, but for the majority of vehicles considered, BEVs remain the lowest in cost, unless specific FCEV incentives are implemented. This paper has identified key factors hindering the deployment of hydrogen and conducted comprehensive TCO analysis in heavy duty on and off-road fleet applications. The output has direct contribution to the decarbonisation of the transport sector.

The effects of e-ridehailing on motorcycle ownership in an emerging-country megacity.

The impact of app-based e-hailing or ridesourcing services on various transport metrics is an area of active research, and research so far have focused on the car-based (or four-wheeled vehicle based) services only. In many cities in the developing and emerging countries, motorcycle-based passenger e-hailing services have become very popular in the last few years, but the implications of these have not been studied before. This study investigates the effects of motorcycle-hailing apps in Dhaka - a megacity in Bangladesh - on the size of its motorcycle fleet. We employ segmented multiple regression on timeseries data to show that there was a statistically significant increase in motorcycle ownership in Dhaka as a result of the motorcycle-hailing services. The findings were also supported by a visual intervention analysis. By the end of 2018, there were 7.45% more motorcycles in Dhaka than there would have been if these app-based e-hailing services were not available. We conclude with potential implications of these increases in motorcycle numbers and future research directions.

Air quality and climate impacts due to CNG conversion of motor vehicles in Dhaka, Bangladesh.

Dhaka had recently experienced rapid conversion of its motor vehicle fleet to run on compressed natural gas (CNG). This paper quantifies ex-post the air quality and climate benefits of the CNG conversion policy, including monetary valuations, through an impact pathway approach. Around 2045 (1665) avoided premature deaths in greater Dhaka (City Corporation) can be attributed to air quality improvements from the CNG conversion policy in 2010, resulting in a saving of around USD 400 million. Majority of these health benefits resulted from the conversion of high-emitting diesel vehicles. CNG conversion was clearly detrimental from climate change perspective using the changes in CO2 and CH4 only (CH4 emissions increased); however, after considering other global pollutants (especially black carbon), the climate impact was ambiguous. Uncertainty assessment using input distributions and Monte Carlo simulation along with a sensitivity analysis show that large uncertainties remain for climate impacts. For our most likely estimate, there were some climate costs, valued at USD 17.7 million, which is an order of magnitude smaller than the air quality benefits. This indicates that such policies can and should be undertaken on the grounds of improving local air pollution alone and that precautions should be taken to reduce the potentially unintended increases in GHG emissions or other unintended effects.