Passenger's perception about city buses in the aftermath of COVID 19: Experience from Guwahati city, India.

The COVID-19 epidemic has affected public transport in various cities worldwide, including Guwahati city in India, where a 59.09% decline in the ridership of city bus services occurred in autumn 2021. The present work aims to investigate the impact of COVID-19 on travelers' perception and identify the parameters associated with the user's dissatisfaction for improving bus service in Guwahati city. In addition, the study also estimated the revenue loss of bus services due to this pandemic. This was carried out based on survey data from travelers in pre-covid (January 2019) situation, unlocked with 50% seating capacity (November 2020), and unlocked with 100% seat capacity plus some limited amount of standee (January 2021) situation. Results showed an increase in the number of users' priorities in post covid compared to pre covid conditions. Factors such as comfort, fairness, reliability & convenience, and safety are the priority areas of users' pre covid. Whereas bus service attribute such as vehicle condition & hygiene emerged as an additional priority of users post covid. Unfortunately, the bus service in the city performed poorly in terms of hygiene, leading to the shifting of the user to other modes of transport. The poor condition of the vehicles is another major factor that made the users to discard the bus service. This led to huge financial losses of the public transit authorities. The cost analysis result showed that the city bus operators faced a financial loss due to the COVID19 outbreak. The average wage of the drivers reduced from 780 Rs./day to 339 Rs./day in the first unlock phase and 476 Rs./day in the second unlock phase. The present study discusses the introduction of the new route in the city, regular cleaning, regular servicing of the buses, and other recommendations to improve the bus service in Guwahati city.

Optimization and public transport tendering: a case study in Southern Italy.

This article presents a multi-start heuristic approach to a design problem motivated by a real-world application in the Italian transport system. Specifically, it focuses on the problem of designing optimal lots in the public transport organization. In defining lots (in terms of number, size, and boundaries) both cost and service level have to be considered. Under certain assumptions, we model the problem as a graph partitioning problem and consider the same performance measure indicated by the relevant decree-law enacted by the Italian Ministry of Transport. The multi-start algorithm proposed for individuating high-quality solutions for the problem uses adaptive large neighbourhood search. The results of a computational study based on real data from a region in Southern Italy are reported.

Investigating the impact of COVID-19 on user perception for deriving policies and intervention areas for urban bus service in India.

The paper aims to investigate the impact of COVID-19 pandemic on the perception of travelers and identify new policies and intervention areas for improving urban bus service. This was carried out based on the perception data collected from travelers in the years 2018 (before pandemic) and 2020(in post lockdown scenario). Data was collected from the state of Kerala, India, and Importance-Satisfaction Analysis (ISA) with fuzzy c-means clustering was carried out to identify improvement areas for both scenarios. Results show a substantial increase in the number of priority areas as compared to the pre-pandemic scenario. Bus service attributes such as cleanliness, crowding level, and pedestrian environment emerged as new intervention areas of bus service during the pandemic. This is a clear reflection of the increased awareness of travelers about the prevailing pandemic scenario and the need for improvement in attributes related to social distancing and hygiene. The higher priority to information related attributes of bus service clearly shows the need for improvement in such attributes for the safe planning of trips during the pandemic. The work also estimated desired service levels of quantitative attributes to enhance the satisfaction levels of users. An evaluation of five bus routes in Kochi based on the desired levels shows the underperformance of attributes such as headway, punctuality, and crowding level. While the findings are city-specific, the methodology and experience may be adopted to enhance the service quality of buses and other public transport.

Modeling the service-route-based crash frequency by a spatiotemporal-random-effect zero-inflated negative binomial model: An empirical analysis for bus-involved crashes.

Previous studies related to bus crash frequencies modeling are limited and the statistical models are usually developed at the road segment or zonal level. This study focuses on modeling crash frequencies specifically at the bus-service-route level, which is useful and important to policymakers and bus operation companies toward the improvement of the safety level of bus networks, especially for developing countries where buses are still a major mode of urban travels. Using the observed data adopted from one of the bus operating companies in Beijing, China, we proposed a spatiotemporal-random-effect zero-inflated negative binomial (spatiotemporal ZINB) model to investigate bus crash occurrence and identity key influential factors at the bus-service-route level. The model was motivated to accommodate the special statistical characteristics of the excessive zeros and, more importantly, the potential spatiotemporal correlations of the data. Three degenerated versions of this model were also developed for comparison purposes. Results indicate that the proposed spatiotemporal ZINB model is statistically superior to the others according to a comprehensive judgment based on the EAIC, EBIC, and RMSE criteria. The estimated coefficients reveal the impacts of related factors on the likelihood of bus-involved crashes from bus operation factors including total passengers, number of drivers, and proportion of male drivers as well as planning factors including route length and stop density. On the other hand, the standard deviations of the introduced structured and unstructured spatiotemporal random-effects are statistically significant indicating that the observations are correlated within each route, between neighbor routes and across years. Corresponding policy and practical implications are provided for bus operating companies and planning departments toward the improvement of bus safety.