Consumer responses towards essential purchases during COVID-19 pan-India lockdown

Humanity experienced one of the worst crises in recent history due to the COVID-19 pandemic. The spread of the disease and the lockdown announced by the government of India created an emergency, disrupting the supply of essential commodities and creating panic and anxiety among the people. This paper aims at capturing the behavior of consumers purchasing essential commodities before and during the lockdown using an online questionnaire. Responses from 730 households covering 20 states in India were used. The data analysis revealed that consumers made a lesser number of trips during lockdown but purchased excess commodities considering the future uncertainties. The local family grocery stores, called kirana shops served well during the pandemic. During the lockdown, consumers made shorter trips by vehicles and walked extensively. Income was found to influence purchase behavior. The disruptions at the organized retail stores for in-store as well as online purchases were identified using factor analysis. Out of the three factors identified each for in-store and online purchases, perceived risk and vendor distrust had major influence respectively. The findings of this study give pointers to many infrastructure and policy initiatives that target tackling such emergencies in the future.

Modelling the pedestrian dilemma zone at uncontrolled midblock sections

INTRODUCTION

Pedestrians at high-speed midblock crossings with the intention to cross the road usually face safety risks due to difficulty in judging the available gaps. The risk to pedestrians is high in developing nations like India since priorities are not respected by road users. Moreover, the non-yielding vehicular traffic puts pedestrians at further risk. While crossing the road, pedestrians are clear about rejecting small gaps and accepting the large gaps, however, they experience a dilemma between the small and large gaps.

METHOD

This study attempts to model the dilemma zone for pedestrians intending to cross the high-speed roads (posted speed limit of 60 km/h). The field data were collected using high-definition video cameras at two uncontrolled midblock crossings, each in the cities of Mumbai and Kolhapur, located in the southwestern part of India. The variations in the spatial gap acceptance behavior were analyzed for 1,107 pedestrian observations using binary logit models.

RESULTS

The findings revealed that the length and the distribution of the dilemma zone were significantly affected by the speed of the approaching vehicle and the distance from it. Moreover, the influence of vehicle type (truck, car, or two-wheeler), pedestrian type (walking alone or in a group), crossing speed, and waiting time also influenced pedestrians' gap acceptance behavior. Interestingly, pedestrians' gender did not play a significant role in their road crossing decisions.

CONCLUSIONS

Overall, the study identified the dilemma zone boundaries that will help pedestrians to judge the safe gaps while crossing, and in turn, reduce the probability of pedestrian-vehicle crashes. Practical Application: The proposed dilemma zone intends to protect the pedestrians by assisting in making precise crossing decisions at high-speed midblock crossings.

Assessing safety critical driving patterns of heavy passenger vehicle drivers using instrumented vehicle data - An unsupervised approach

Assessing the individual's driving profile and identifying the at-fault behaviors contributes to road safety, riding comfort, and driver assistance systems. This study proposes a framework to identify aggressive driving patterns in longitudinal control using real-time driving profiles of heavy passenger vehicle (HPV) drivers. The main objective is to detect and quantify the instantaneous driving decisions and classify the identified maneuvers (acceleration, braking) using unsupervised machine learning techniques without any prior-ground truth. To this end, total 8295 acceleration events, and 7151 braking events, were extracted from 142 driving profiles collected using high-resolution (10 Hz) GPS instrumentation. The principal component analysis was conducted on a multi-dimensional feature set, followed by a two-stage k-means clustering on the reduced feature subspace. The results showed that 86.5% of accelerations and 65.3% of braking maneuvers were characterized as non-aggressive, indicating safe or base-line driving behavior. However, 13.5% of accelerations and 34.7% of braking maneuvers were featured to be aggressive, indicative of the actual risky behaviors. Further analysis demonstrated the heterogeneity in drivers' trip-level frequency of aggressive maneuvers and highlighted the need for a continuous driving assessment. The study also revealed that the thresholds derived from the obtained clusters featuring the aggressive accelerations (+0.3 to +0.48 g) and aggressive braking (-0.42 to -0.27 g) maneuvers were beyond the acceptable limits of passenger safety and comfort. The insights from the study aids in developing driver assistance systems for personalized feedback provision and improve driver behavior.

Modelling work- and non-work-based trip patterns during transition to lockdown period of COVID-19 pandemic in India

COVID-19 pandemic has significantly affected the transportation sector across the world. Implementation of lockdown (that includes restricted travel activities) is a prevention strategy executed by various governments to minimize the spread of COVID-19. India went into complete lockdown from 25th March 2020; however, change in commuter's travel behavior was observed from the third week of March (termed as transition to lockdown) due to pandemic fear. In total 1945 participants participated in the travel behaviour survey and their responses with respect to work-based and non-work-based trips during transition period were analysed to understand their adaptation towards COVID-19. The study also attempted to quantify the effects of influencing factors which can explain change in the commuters' travel behaviour. The findings revealed that one-year increment in traveller's age had 2% reduced probability of no travel during transition than pre-transition. For non-work-related travel, chances of lower travel frequency were significantly greater during the transition period as compared to pre-transition. Compared to the non-essential trips, the chances of reduced travel frequency for the essential trips were found to be lower by 92%. By examining these behavioural changes, the present study aims to assist the policymakers in understanding the dynamics of fluctuating travel demand with respect to trip purpose during pandemic situations like COVID-19.

Impact of lockdown associated with COVID19 on air quality and emissions from transportation sector: case study in selected Indian metropolitan cities

This study examines the impact of air quality in selected Indian metropolitan cities during the COVID19 pandemic lockdown period. Concentrations of air quality parameters such as PM_2.5, NO₂, SO₂, and CO during the transition to lockdown and the actual lockdown period were compared with business as usual periods (a period prior to COVID19 lockdown and a corresponding period in 2019) to estimate the reduction in emission in four major IT hubs in India namely Bengaluru, Chennai, Hyderabad and Pune. A 40-45% reduction in PM_2.5 concentration was observed, in these cities, during the lockdown compared to the corresponding period in 2019 and a 20-45% reduction was observed compared to business as usual period in 2020. A vehicle kilometer traveled (VKT)-related questionnaire survey-based study in Hyderabad revealed that, with 48% of population utilizing work-from-home during the transition to lockdown period, vehicular PM_2.5 emission in Hyderabad reduced by 54% compared to usual traffic emissions prior to COVID19 lockdown. Furthermore, it was estimated that emission of up to 3243, 777, 113, and 54 tons/year of CO, NOx, PM_2.5, and SO₂, respectively, could be avoided in Hyderabad alone, if work-from-home is implemented on a 2 days/week basis. The experience from this study can be used to develop policies favoring reduced use of private vehicles or implementation of work-from-home to combat air pollution and reduce carbon emissions.

Impact of lockdown associated with COVID19 on air quality and emissions from transportation sector: case study in selected Indian metropolitan cities

This study examines the impact of air quality in selected Indian metropolitan cities during the COVID19 pandemic lockdown period. Concentrations of air quality parameters such as PM_2.5, NO₂, SO₂, and CO during the transition to lockdown and the actual lockdown period were compared with business as usual periods (a period prior to COVID19 lockdown and a corresponding period in 2019) to estimate the reduction in emission in four major IT hubs in India namely Bengaluru, Chennai, Hyderabad and Pune. A 40-45% reduction in PM_2.5 concentration was observed, in these cities, during the lockdown compared to the corresponding period in 2019 and a 20-45% reduction was observed compared to business as usual period in 2020. A vehicle kilometer traveled (VKT)-related questionnaire survey-based study in Hyderabad revealed that, with 48% of population utilizing work-from-home during the transition to lockdown period, vehicular PM_2.5 emission in Hyderabad reduced by 54% compared to usual traffic emissions prior to COVID19 lockdown. Furthermore, it was estimated that emission of up to 3243, 777, 113, and 54 tons/year of CO, NOx, PM_2.5, and SO₂, respectively, could be avoided in Hyderabad alone, if work-from-home is implemented on a 2 days/week basis. The experience from this study can be used to develop policies favoring reduced use of private vehicles or implementation of work-from-home to combat air pollution and reduce carbon emissions.

Impact of physical distancing due to novel coronavirus (SARS-CoV-2) on daily travel for work during transition to lockdown

The outbreak of COVID-19 pandemic has resulted in change in both commute and personal travel patterns. Though, in India, lockdown was implemented from 25th March 2020, due to self-awareness and pandemic risk perception, change in commuter behavior was observed from the beginning of March 2020. The period from 15th to 24th March 2020 is considered as the transition phase of COVID-19 outbreak in India (i.e., between no lockdown and lockdown period). This study attempts to use a decision tree approach to investigate the modal preference of 1542 commuters in association with socio-economic and travel characteristics, and safety perceptions with respect to public and private modes during transition to lockdown due to COVID-19 in India. About 41% of commuters stopped traveling during the transition to lockdown phase, 51.3% were using the same mode of transport and 5.3% of commuters shifted from public to private mode. The study findings reported different interactions of factors influencing the decision to use public or private modes of transport for daily commuting during pandemic situations like COVID-19. Interestingly, safety perceptions (associated with personal health) of commuters did not play a significant role in their mode choice behavior during the transition phase. Though people perceived public transportation as unsafe over personal vehicle use, the actual commute patterns did not validate this due to a possible reason that commuters do not have enough alternative modes. Given the uncertainties in the decision making of the commuters regarding their travel behavior due to physical distancing, the insights from this study are important to policymakers and local transport authorities to understand the change in travel patterns.

Pedestrian temporal and spatial gap acceptance at mid-block street crossing in developing world

INTRODUCTION

Most of the midblock pedestrian crossings on urban roads in India are uncontrolled; wherein the high degree of discretion in pedestrians' behavior while crossing the traffic stream, has made the situation complex to analyze. Vehicles do not yield to pedestrians, even though the traffic laws give priority to pedestrians over motorized vehicles at unsignalized pedestrian crossings. Therefore, a pedestrian has to decide if an available gap is safe or not for crossing.

METHOD

This paper aims to investigate pedestrian temporal and spatial gap acceptance for midblock street crossings. Field data were collected using video camera at two midblock pedestrian crossings. The data extraction in laboratory resulted in 1107 pedestrian gaps. Available gaps, pedestrians' decision, traffic volume, etc. were extracted from the videos. While crossing a road with multiple lanes, rolling gap acceptance behavior was observed. Using binary logit analysis, six utility models were developed, three each for temporal and spatial gaps.

RESULTS AND CONCLUSIONS

The 50th percentile temporal and spatial gaps ranged from 4.1 to 4.8s and 67 to 79 m respectively, whereas the 85th percentile temporal and spatial gaps ranged from 5 to 5.8s and 82 to 95 m respectively. These gap values were smaller than that reported in the studies in developed countries. The speed of conflicting vehicle was found to be significant in spatial gap but not in temporal gap acceptance. The gap acceptance decision was also found to be affected by the type of conflicting vehicles.

PRACTICAL APPLICATIONS

The insights from this study can be used for the safety and performance evaluation of uncontrolled midblock street crossings in developing countries.

Is periprostatic nerve block a gold standard in case of transrectal ultrasound-guided prostate biopsy?

Introduction:

Controversy exists over the pain during prostate biopsy. Periprostatic nerve block (PNB) is a gold standard anesthetic technique during transrectal ultrasound (TRUS)-guided prostate biopsy. Recent studies showed that PNB alone is insufficient as analgesic. We compared the efficacy of tramadol and intraprostatic nerve block (INB) in addition to PNB.

Materials and Methods:

We conducted a prospective double blinded placebo controlled study at our institute in 150 consecutive patients. Patients were randomized into three groups. Group A received PNB with INB with 1% lignocaine. Group B received oral tramadol with PNB. Group C patients were administered PNB only with 1% lignocaine. Patients were asked to grade the pain level using 11 point linear visual analog scale (VAS) at the time of ultrasound probe insertion, at time of anesthesia, during biopsy, and 30 min after biopsy.

Results:

The study groups were comparable in demographic profile, prostate-specific antigen (PSA) levels, and prostate size. Group A recorded the minimum mean pain score of 2.66 during prostate biopsy which was significantly lower than group 3 (P < 0.001). Group B recorded significantly lower pain score at time of probe insertion and at anesthetic needle insertion than other two groups.

Conclusions:

PNB provides better pain control in TRUS-guided prostate biopsy but still there is need of additional analgesic in the form of tramadol or INB. Tramadol has advantage of oral intake and analgesic effect at time of probe insertion and at nerve block. Both tramadol and INB may be used in combination along with PNB.