Determining the speed limit of road transport systems has a significant role in the speed management of vehicles. In most cases, setting a speed limit is considered as a trade-off between reducing travel time on one hand and reducing road accidents on the other, and the two factors of vehicle fuel consumption and emission rate of air pollutants have been neglected. This paper aims to evaluate optimal speed limits in traffic networks in a way that economized societal costs are incurred. In this study, experimental and field data as well as data from simulations are used to determine how speed is related to the emission of pollutants, fuel consumption, travel time, and the number of accidents. This paper also proposes a simple model to calculate the societal costs of travel and relate them to speed. As a case study, using emission test results on cars manufactured domestically and by simulating the suburban traffic flow by Aimsun software, the total societal costs of the Shiraz-Marvdasht motorway, which is one of the most traversed routes in Iran, have been estimated. The results of the study show that from a societal perspective, the optimal speed would be 73km/h, and from a road user perspective, it would be 82km/h (in 2011, the average speed of the passing vehicles on that motorway was 82km/h). The experiments in this paper were run on three different vehicles with different types of fuel. In a comparative study, the results show that the calculated speed limit is lower than the optimal speed limits in Sweden, Norway, and Australia

Fossil-fuel consumption in land freight is over 19%. Alternative fuel trucks (AFTs) help decrease greenhouse gas emissions. However, AFT preferences in international land transit have received little attention due to passing through various countries with different financial and regulation plans. This variety affects AFTs’ market share. This study analyzes factors influencing AFT preferences in international land transit. A questionnaire (designed in four sections) was distributed among international transport companies in Iran and Europe. A principal component analysis helped extract principal components composed of cognitive, environmental, policy, practical, and economic variables. The multinomial logit models include 26 meaningful variables. The marginal effect analysis shows that the service quality of the manufacturer, importance of greenhouse gas mitigation, and social responsibility do not significantly elevate AFT preferences. In addition, cargo type influences AFT choice. The results of this study help to identify the barriers affecting AFTs’ market share, which can positively impact air pollution.

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.

Greenhouse gas emissions from fossil fuel engines in land freight transportation are considerable. Alternative fuel trucks help decrease emissions. Previous studies have generally focused on the alternative fuel truck preferences in domestic land freight. External land transit has received little attention due to passing through various countries with different financial, policy, regulation, and incentive plans. This variety can affect international transport companies’ alternative fuel truck preferences and, consequently, the market share. To make external land transit more sustainable, factors (cognitive, economic, environmental, policy, and practical) influencing alternative fuel truck preferences of the international transport companies are analyzed in this study. A questionnaire was distributed among 684 international transport companies in 20 countries to gather data on their background information; their alternative-fuel choice; their level of agreement with Cognitive, Environmental, and Policy factors; and importance degree of practical, economic, and some other policy factors in adopting alternative fuel trucks. Principal components analysis helped extract 11 principal components composed of cognitive, environmental, policy, practical, and economic variables. The two multinomial logit models include 26 influential variables. The importance of greenhouse gas mitigation, low noise pollution, and social responsibility do not significantly elevate emission-free trucks preferences. The marginal effect of the service quality of the manufacturer (with a twelve percent decrease in choice probability) shows manufacturers should improve the quality of their services. It is also noteworthy that cargo type influences alternative fuel truck choice. Results of this study can help to identify the factors, policies, and regulations which may affect and increase the market share of alternative fuel trucks.