This study investigates various risk factors associated with pedestrian crash occurrence and injury severity based on 78,497 reported pedestrian-involved crashes across Texas from 2010 through 2019...

The distribution of public facilities and their spatial equity is an important matter to be considered while planning public facilities. However, most of the studies in the literature have taken into consideration only a single type of facility while leaving other facilities unconsidered. In this paper an integrated spatial index for public facilities has been developed integrating GIS and spatial analysis models. The index measures the spatial equity based on the accessibility of 6 different types of public facilities for 5247 unions and 476 sub-districts of Bangladesh. Spatial autocorrelation techniques have been applied to understand the spatial pattern of accessibility. In fact it helps to understand the characteristics of spatial equity both for disaggregated and aggregated levels. It has been found that variation accessibilities to the facilities across the space are significant. Distribution of some facilities are spatially clustered to some particular areas means those areas are in an advantageous position in terms of accessibility while other areas are in a backward condition. The proposed index and the spatial autocorrelation will help to identify which areas should receive more priority in allocating particular types of public facilities in the future.

An increasing number of corporations and workplaces are providing flexible working hours or flextime for employees, which is expected to reduce congestion by redistributing the temporal pattern of commuters’ departure time. This study examines the impact of flextime on departure time choice using a Bayesian continuous-time hazard duration model. The model accommodates the time-varying effect of covariates and unobserved heterogeneity. Results from the Austin Household Travel Survey collected between 2017 and 2018 show that workers who have a flextime option choose to leave later, with a predominant effect deterring morning peak departures. Other trip and individual-specific variables, such as travelers’ job type, trip duration, number of trips during the travel day, and household income, are found to have significant impacts on departure time choice. The results also show that flextime is more effective in shifting the departure time for retail and service sector employees, for those whose journeys are longer, and for those who perform more daily activities. The findings of this study support the theory that implementing such policies may ease congestion by staggering the travel demand from peak to off-peak hours.