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.

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.

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Autonomous vehicles (AVs) have a number of potential advantages, although some research indicates that this technology may increase dependence on private cars. An alternative approach to bringing such technology to market is through autonomous taxis (ATs) and buses, which can assist in making transportation more sustainable. This paper aims at examining the role of attitudinal, travel-related, and individual factors in preferences for a modal shift from conventional cars toward ATs and exclusive-lane autonomous buses (ELABs), exploring the existence of heterogeneity and its possible sources. The proposed mixed logit model with a decomposition of random coefficients uses 1251 valid responses from a stated preference survey distributed in Tehran, in 2019. Results show that there is significant taste variation among individuals with respect to ATs’ travel costs, ELABs’ travel times, and walking distances to ELAB stations. Furthermore, exploring the sources of heterogeneity indicates that women are more sensitive to ATs’ travel costs and walking distances to ELAB stations while they are less sensitive to ELABs’ travel times. Moreover, travel time in discretionary activities reduces the utility of ELABs more than it does in mandatory activities. Transportation authorities can use these findings to establish more effective policies for the successful implementation of AVs.