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Prior research on COVID-19 focused primarily on travel behavior changes before, during, and after the pandemic, with the aim of analyzing the significant variables. However, this research aims to study and compare the effects of traffic and transportation measures, specific events, and vaccination rates on the COVID-19 infection rate in Tehran, Iran. A correlation analysis is employed to investigate the degree of relationship between the number of infected individuals on each day and the implementation time of measures, events, and the vaccination rate. Over a 14-day period, the majority (67%) of measures and events had a significant impact on either decreasing or increasing the number of infections at a significant level of 1%. Results indicate that congestion pricing suspension has the most effect on decreasing the virus spread (correlation coefficient between -0.75 and -0.94). As another traffic-related measure, intercity travel bans also contributed to a decrease in infections. Additionally, certain holidays/events and their related movements and gatherings are linked to an increase in cases (correlation coefficient between 0.71 and 0.96). The ongoing decrease in infection rate could be attributed to the increasing vaccination rate, showing a negative correlation with a coefficient of -0.771. [ABSTRACT FROM AUTHOR]

Walking has been recognized as an important mode of transportation in recent years, and recent research has improved travel demand models for walk trips. One important added stage is the distribution of walk trips, which can be evaluated using destination choice models. Previous studies have overlooked the importance of origin trip attributes in the destination choice of walk trips. With the aim of improving destination choice models for discretionary home-based walk trips, a questionnaire based on the previous day's walk trips was used, and 422 trips were collected from individuals. A discrete choice logit model is used for discretionary trips by utilizing policy-related variables, such as origin-sensitive variables, land-use-related variables, and socio-economic conditions of individuals. Additionally, a solution is proposed to address the issue of data scarcity in considering the choice set. The results demonstrate that origin land-use (LU) variables, such as LU diversity index and access to green spaces, as well as socio-economic variables, like age and homeownership status, are statistically significant in the destination choice of discretionary home-based walk trips. One prominent result is that reducing the diversity of unattractive LU compared to increasing the diversity of attractive LU has a greater impact on the destination choice of such trips. Specifically, a 1% increase in the diversity of attractive LU in the origin area leads to a 0.031% increase in the probability of choosing a destination within that area, while a 1% decrease in the diversity of unattractive LU results in a 0.124% increase in the probability of choosing a destination within the area. The findings can be utilized in urban LU distribution and assessing their impact on destination choice for walk trips, ultimately informing future urban planning efforts in the context of pedestrian mobility. [ABSTRACT FROM AUTHOR]

Due to the potential of automated vehicles (AVs) to change the transportation system radically, it is essential to investigate the factors affecting users' intention to use them. Although previous studies have mostly focused on the latent variables of the internal schema of beliefs, this paper aims to examine the impact of internal and external factors by integrating the variables of the unified theory of acceptance and use of technology along with environmental concerns and perceived risk. Moreover, the effects of latent variables are also compared for different trip purposes (mandatory and optional), which have received less attention in previous studies. Using a stated-preference survey, 641 valid responses from citizens of Tehran, Iran have been collected. The estimation results of structural equation modelling show a significant difference between the determinants of AV acceptance across mandatory and optional trips. The estimated coefficients indicate that social influence and performance expectancy are the strongest explanatory factors in the intention to use AVs in optional and mandatory trips, respectively. However, no significant difference is observed for the impact of environmental concerns on the intention to use AVs across both trip types. [ABSTRACT FROM AUTHOR]

Pricing and traffic rationing have emerged as effective and economically feasible strategies for mitigating traffic congestion in the central business districts of large cities. In Tehran, Iran's capital city, two separate surveys were conducted to evaluate the effects of time- and duration-based pricing strategies. The surveys included 1,388 participants from the congestion pricing zone (CBD) and 983 participants from the odd-even traffic rationing zone. The error component logit model was calibrated using stated preference (SP) scenarios for both the congestion pricing zone and the odd-even traffic zone; These models aimed to analyze modal shift, route choice, and time of travel in a day. Additionally, the mode choice behavior in the CBD was examined using the generalized mixed logit (GMXL) model, which was calibrated using both SPs and RPs. The findings indicate that implementing a duration-based scenario would result in a modal shift, changes in trip patterns, and even trip cancellations. On the other hand, the time-based scenario would primarily lead to changes in travel timing or destination choices. GMXL results show that duration-based pricing is more effective in shifting private vehicle trips to other modes. Furthermore, on-demand ride-hailing is less significant as a competitor mode within these zones. [ABSTRACT FROM AUTHOR]

Sustainable and livable cities and non-motorized transportation modes are being increasingly promoted around the world. A considerable number of studies have investigated various factors associated with the severity of pedestrian crashes. However, little attention has been paid to the particular impacts of lighting conditions. This paper aims to differentiate between different lighting conditions based on solar altitude by developing separate Generalized Ordered Probit (GOP) models for the four distinct lighting conditions (i.e. daylight, twilight, dark, and lighted) analysing pedestrian injury severity at urban intersections. The models are tested using a set of log-likelihood ratio tests, which show there are key differences in the significance of the estimates, magnitude, and even the direction of the effects of explanatory variables, in which such differences may not be revealed by calibrating one aggregate model. Notably, built environments, age, gender of both pedestrian and driver, and speed limits were found to have different impacts on the severity of the crash. [ABSTRACT FROM AUTHOR]

This research integrates Unified Theory of Acceptance and Use of Technology (UTAUT) (Performance Expectancy [PE], Effort Expectancy [EE], and Social Influence) with Diffusion of Innovation Theory (TRialability [TR] and OBservability [OB]) as well as Perceived Risk (PR) to identify a wider set of latent factors affecting acceptance of fully automated AVs. Although research on AVs acceptance has been conducted in developed countries, it is a rather new topic in developing countries, where it has only been introduced as a promising technology to come. Structural equation modeling on stated preference surveys data of 641 Tehran residents in 2019 justifies the proposed integration of two theories and PR. Only PR shows an expected negative sign (−0.2); Among UTAUT variables, PE (0.33) and EE (0.25) were the most and least influential factors, respectively. Regression weights o DOI-related variables show that TR (0.17) and OB (0.16) have almost equal effect. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Improving the service quality of public transport is necessary to maintain the loyalty of current users and attract new travelers. Past studies show that users' preferences for transit service quality are heterogeneous, but recognizing the factors describing this heterogeneity has not been investigated in depth. This paper aims to evaluate the sources of heterogeneity in passengers' preferences for service attributes of bus transit regarding the regular bus system in the city of Tehran. Four attributes of bus travel, including in-vehicle travel time, fare, vehicle crowding, and headway, were considered. Stated preference (SP) data of 360 commuters with work purpose was collected through face-to-face interviews. The random parameter logit (RPL) model, considering the heterogeneity around the mean of random coefficients, shows that heterogeneity can be explained to some extent by observed characteristics. It can be helpful for transit operators to adopt more efficient measures to improve service aspects. [ABSTRACT FROM AUTHOR]