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Many studies have examined the impact of factors affecting accident severity in rural areas; however, little attention has been paid to different lighting conditions (LCs), and less to the detailed categories and precise determining of twilight. In this paper, solar altitude angle (SAA), as a basis for differentiating and categorizing LCs, is proposed to investigate explanatory variables in much greater detail. For each LC, namely, dark, twilight, dark lit (dark with street lights) and daylight, separate random parameter models are developed to investigate the impacts of some factors on crash injury severity data of 2017 and 2018 in two lane rural roads of Texas. The model estimation results indicated that different LCs have various contributing factors, indeed, to each injury severity, further stressing the significance of investigating crashes based on SAA. The key differences include crash location, marked lane, grade direction, no passing zone, shoulder width, weekday and collision type. The important findings were that developing artificial lighting at intersections and LED raised pavement markers on two lane rural roads could lead to enhanced road safety under dark LCs. Furthermore, increasing shoulder width in straight segments of two lane rural roads is important for decreasing severe injury in daylight conditions.

Air pollution, as a significant urban problem in metropolises, has harmful impacts on societies in many aspects. According to the worn-out fleet of diesel buses and fossil fuel dependencies in Tehran, alternative fuels have become more popular in sustainable public transportation. Although battery electric buses (BEBs) provide many benefits, their purchase price and required infrastructure are the main challenges for decision-makers. This paper provides a systematic approach to examining the environmental, traffic, and economic efficiency of overnight-charging electric buses (OCEBs) in Tehran, Iran. Environmental analysis shows that Carbon Oxide and Nitrogen Oxide will reduce to zero and eliminate dependence on fossil fuels. The payback period is predicted to be 7 years. Due to the better acceleration of OCEBs, the travel time, delay, and stop time reduce by about 4%, 10.67%, and 5.15% on average, respectively, which leads to a better experience for passengers and an increase in public transportation utility that cause more people attract to OCEBs. The present results indicate the feasibility of OCEBs implementation as a sustainable transportation mode and can be useful in policymakers' decision-making and planning for the future public transport system.

Increasing private car ownership and car dependency has led to a low share of walking as an active mode as well as congestion, air pollution, and health problems in developing countries. This paper aims to identify and compare the impacts of a selection of socio-economic, travel-related, and built environment variables on walking likelihood and respondents’ sensitivity to the walking distance, both for discretionary and mandatory trips. The analysis drew its origin from 14,463 responses acquired through an extensive travel survey conducted in the city of Qazvin, Iran. The estimated binary logit coefficients show people’s heterogeneity in the walking behavior for discretionary and mandatory trips. The results report a higher likelihood of walking on mandatory trips at almost all distances than the discretionary ones. Furthermore, investigating individual heterogeneity in different trip distances reveals that people aged less than 14 are more likely to choose walking on mandatory trips longer than 2400 m. Besides, those aged 25–44 years old or above 65 have less tendency to choose walking on mandatory trips with distances of 2000–2400 m and 800–1200 m, respectively. These findings are almost different on discretionary trips; compared to other age groups, people aged 15–24 years are less likely to choose walking on discretionary trips with a distance of 800–1200 m. Moreover, in trip distances of 1200–1600 m, the elderlies have a greater tendency to choose walking compared to other age groups. Some implications for more sustainable mobility in human-oriented urban environments are also presented and critically discussed.

The optimal location for establishing logistics centers is of great importance in reducing logistics costs and improving supply chain efficiency. This paper aims to provide a conceptual framework for finding the optimal location and capacity for a logistics village establishment using mixed-integer linear programming (MILP). The proposed model is applied on Qazvin province, Iran, as a developing country with a strategic location in international transport corridors. Unlike previous research, the proposed approach considers various logistics operations such as warehousing, refrigeration, sorting, and packaging, along with their capacities as distinct decision variables. The study area is divided into 6972 blocks of 1.5 × 1.5 km, of which 59% are infeasible and excluded due to environmental and natural hazard constraints. The MILP model is then applied in the GAMS for each feasible block to identify the best alternatives for the logistic village establishment with maximum total profit. Based on the results, total freight imported to Qazvin province is directly transferred to their final destinations without visiting the logistics village, while around 98% of exports of Qazvin province would first enter the logistics village to get a service before delivering to customers.