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The rollout of driverless cars (DC) may reshape human mobility drastically. Urban roads may face a surge of car traffic if DC technologies continue to enhance the use of private cars. Shared DC use can remedy this by reducing the number of urban trips that non-shared-use DC could otherwise make. While recent research has proven the importance of socioeconomic factors on shared DC use, the influence of present sharing behaviour, personality traits, and social norms on shared DC use has not been extensively explored to date. To address this gap in this study, we employed a panel of 500 Edinburgh-based respondents through an online survey to examine the likelihood of accepting the non-shared-use and shared-use DC options for regular urban trips. We have collected data on respondents’ present carsharing and ridesharing behaviour, personality traits, social norms, and sociodemographic characteristics. To elicit the impact of these factors on the likelihood of accepting non-shared-use and shared-used DC options, ordered probit models were estimated. The model findings imply that frequent household car users and those influenced by social expectations to preserve the environment are willing to use non-shared-use DC. In contrast, city centre dwellers, cooperative and younger adults with sharing attitudes show a higher tendency towards shared DC. High-earning, working-aged and young respondents are more inclined to use a driverless taxi, whereas city-centre dwellers and those influenced by social expectations to share personal resources are more favourable towards ridesharing with a stranger in DC. These results can assist the policymakers and transport planners shape policies for promoting shared DC use and transport service providers to deliver and operate shared DC fleets efficiently.

Recently a comprehensive traffic safety study for the two main corridors was conducted in Eastern Province of Saudi Arabia. The main aim of the study was to analyze the causes of various traffic safety related issues in the Eastern Province. This was done with regards to traffic crashes with fatalities in-particular; some of the methods employed included collecting data on traffic volumes, highway speeds, travel times, traffic crashes, and conducting the road safety audit. These methods helped develop several countermeasures which targeted to reduce crashes and the severity levels associated with them, and hence improve the overall traffic safety situation in the area. This paper explains a sketch planning approach for the application of Highway Safety Manual (HSM) based crash prediction methods using road safety audit data, to help estimate reduction in crashes due to proposed improvements. The selection of the two corridors was to best represent the transportation network in the Eastern Province which consists of several different types of facilities including urban, suburban, and rural roads. Comprehensive road safety audit was performed on two corridors and the data collected thereof was archived into reporting templates. After thorough evaluation of the data collected in the safety audit process, improvements to root causes of traffic safety concerns were recommended; the HSM based crash prediction methods were applied to see the effectiveness of the improvements suggested. Reports were prepared for each of the data collection items. While the results show reduction in traffic crashes based on improvements to the corridors, this approach could contribute in its true essence when applied in combination with several other traffic safety improvement strategies.

Safety experts and transportation departments are focused on reducing road accidents and their societal and economic effects. The most crucial step in establishing a successful road safety practice is identifying dangerous highway zones through the study of crashes and looking at how the location of accidents relates to surrounding geography and other factors. Using the latest cutting-edge GIS analytical methods, this study aims to map the locations of accident hot spots and evaluate the severity and spatial extent of crash occurrences in Ohio. Road traffic crash (RTC) data has been analyzed using sophisticated GIS-based hot spot analysis for decades by safety researchers. Using four years’ worth of crash data from the state of Ohio and spatial autocorrelation analysis, this study aims to show how a GIS technique can be used to find places where accidents are likely to happen (2017–2020). The study analyzed and ranked crash hotspot areas using the matching severity levels of RTCs. Cluster zones of high and low crash severity were discovered using the spatial autocorrelation tool and the Getis Ord Gi* statistics tool to evaluate the distribution of RTCs. The analysis used Getis Ord Gi*, the crash severity index, and Moran’s I spatial autocorrelation of accident events. The findings indicated that these techniques were useful for identifying and rating crash hotspot locations. Since the sites of the identified accident hotspots are located in significant cities in the state of Ohio, such as Cleveland, Cincinnati, Toledo, and Columbus, the organizations in charge of traffic management should make it their top priority to minimize the negative socioeconomic impact that RTCs have and should also conduct a thorough investigation. This study’s contribution is the incorporation of crash severity into hot spot analysis using GIS, which could lead to better-informed decision-making in the realm of highway safety

Predominant water scarcity and environmental degradation in Bangladesh's coastal communities arise due to extreme meteorological conditions, unrestrained water usage, and extensive saline intrusion into both surface and groundwater. This study leverages both quantitative data from a household survey and qualitative data from a Participatory Rural Appraisal to explore the perspectives of 150 official experts and 240 coastal public respondents regarding the implementation of a "Community-Based Rainwater Harvesting System" (CBRWHS) as a sustainable water supply technology in six major coastal districts of Bangladesh. Though CBRWHS surpasses the benefits of an individual harvesting system (IHS) due to its collective approach, high storage capacity, social cohesiveness, environmental benefits, and potential for scalability, findings suggest that the experts identify financial insolvency, lack of technical skills, and insufficient education as principal barriers against adopting CBRWHS. They propose that providing technical instructions, education, and establishing a CBRWHS pilot could serve as effective incentives. While expressing a sufficient understanding of IHS, respondents are willing to adopt CBRWHS only if financial support is provided. Given the residents' experience with IHS, they are cognizant of the financial and technical challenges intrinsic to such systems. CBRWHS, unlike IHS, operates as a shared system with collective property rights and regulations. Majority of respondents perceive CBRWHS as a potential significant mitigation tool against the water shortage situation since the challenges associated with harvesting, maintaining, and using rainwater could be addressed collectively by the user community. Similar to the official experts, public respondents identify a lack of technical expertise, financial constraints, and regulations as the most significant obstacles to IHS adoption. The findings of this study hold substantial implications not only for the local region but also for similar coastal regions worldwide, suggesting a crucial need for the prioritization of community-based solutions to water scarcity within the wider global discourse on sustainable water management.

The very fast economic and population growth of Bangladesh, along with its high urbanization rate, have been seen since its independence in 1971. Sylhet City Corporation (SCC) has also experienced high population growth as well as rapid urbanization since 2002. The solid waste generation rate is also increasing along with the high economic and population growth in SCC. SCC and its extended areas are now producing more solid waste than ever before because of accelerated unplanned urbanization, ever-growing tourist pressure, and an overgrowing urban population. Sooner than later, resource recovery and capacity development in existing solid waste management systems are required to allow the sustainable and resilient growth of SCC. This study aimed to explore the total amount of solid waste generation per day as well as the waste composition and potentiality for resource recovery from the generated solid waste in SCC and its extended areas. This study has found that SCC is now generating a total of 375.68 tons of solid waste daily from households, daily kitchen markets, medical institutes, resident hotels, commercial shops, and restaurants. This study has also found that about 90% of daily-generated solid waste is perishable and has a high moisture content. This study has found that the generated waste in SCC has the potential to produce compost fertilizer, solid recovered fuel (SRF), and electricity. On the other hand, this study can directly help the conservancy department of SCC to have a brief idea about the existing solid waste generation rate, composition, categories, and potentialities of resource recovery from the generated solid waste. It can also succor other conservancy departments of other city corporations or urban areas of Bangladesh as well as other researchers in a similar way.

The multi-scale assessment of surface-groundwater interactions in hard rock (granite), water limited environments was carried out first in the ~80 km2 Sardon catchment and finally in a small, 7.6 ha Trabadillo study area (Western Spain). Three different thematic studies (Chapters 2-4) had been carried out applying various techniques including: field data acquisition, automated monitoring, remote sensing and integrated hydrological modelling using GSFLOW code. Chapter 2 addresses the assessment of dynamics of surface-groundwater interactions at the Sardon catchment scale; the main findings were: (1) intense groundwater exfiltration; (2) groundwater flow characterized by short groundwater flow-path and short residence time; (3) declining trend of catchment groundwater outflow; and (4) large variability of infiltration influenced by land cover type. That impact of land cover upon dynamics of surface-groundwater interactions triggered expansion of further research in Chapters 3 and 4, but also underpinned some hardcoded deficiencies of GSFLOW, related to formulation of driving forces. That initiated the study in Chapter 3, addressing spatiotemporal tree rainfall interception loss (EI). Experimental measurements of EI on selected evergreen Quercus ilex and deciduous Quercus pyrenaica oaks were carried out during two years and spatiotemporally upscaled into two homogeneous (1 ha) plots and into the entire Sardon catchment; the main findings were: (1) yearly EI was larger in wet than in dry hydrological years but if reflected as percent of rainfall, then it was opposite; (2) EI of Quercus ilex trees were larger than of Quercus pyrenaica but for the catchment scale EI, it was opposite, because of much larger catchment population of the latter; (3) catchment EI was primarily dependent on tree density and species type. The Chapter 4 focusses on simulating surface-groundwater interactions at very fine grid (5x5 m) and at temporal daily resolution, using 20-year time-series observation to assess the net recharge dependence upon land cover type expressed through hydrological terrain units (hydrotopes). The findings of this study confirmed all findings of the Chapter 2, adding the following: (1) hydrotope-dependent variability of water fluxes; (2) non-negligible grass interception; and (3) much lower net recharge under tree than grass hydrotopes, meaning more trees, less water resources.