The currently available transport modeling tools are used to evaluate the effects of behavior change. The aim of this study is to analyze the interaction between the transport mode choice and travel behavior of an individual—more specifically, to identify which of the variables has the greatest effect on mode choice. This is realized by using a multinomial logit model (MNL) and a nested logit model (NL) based on a utility function. The utility function contains activity characteristics, trip characteristics including travel cost, travel time, the distance between activity place, and the individual characteristics to calculate the maximum utility of the mode choice. The variables in the proposed model are tested by using real observations in Budapest, Hungary as a case study. When analyzing the results, it was found that “Trip distance” variable was the most significant, followed by “Travel time” and “Activity purpose”. These parameters have to be mainly considered when elaborating urban traffic models and travel plans. The advantage of using the proposed logit models and utility function is the ability to identify the relationship among the travel behavior of an individual and the mode choice. With the results, it is possible to estimate the influence of the various variables on mode choice and identify the best mode based on the utility function.

Transportation planning plays an essential role in improving the transportation system. Therefore, planners should have the ability to forecast the response of transportation demand to changes in the characteristics of the travellers. This has led researchers to work on more effective behavioural models by updating conventional models and replacing them with activity-based modelling to describe the daily activity chains performed by travellers. So, this study uses the activity model to model and analyse daily activity to identify the factors affecting the activity chain. This study aims to use logit models based on the utility function for modelling the activity chains of travellers in Budapest city. At the same time, we identify the effects of various characteristics related to the traveller, trip and location in the activity chains. This paper presents the relationships between the two aspects of travel behaviour and activity chains by providing two different causal structures. The results showed that the location attribute, activity duration and activity purpose were most influential on the activity chains. This study provides good insights into activity chains behaviour of travellers. It also extends the need to incorporate activity model behaviour within these complicated processes and household and individual decision making of daily activity.

Tires that are simply thrown away are a serious environmental problem and safe disposal is a difficult problem. Using the crumb rubber (CR) obtained from shredding of those scrap tires in roads is an alternative solution to their safe disposal. On the other side, excessive rutting in the bituminous layer is a structural defect associated with functional implications. Wheel loads and high pavement temperatures are environmental factors which the main cause of premature rutting. Modified binders and rut resistant mixes especially gradations can reduce premature rutting. The object of the paper to solve two main problems: firstly, the solution to the problem of the tires waste to safe disposal and; secondly, to study the rutting behaviour in bituminous mixes modified by tires waste in CR form. In this paper, two types of bituminous mixes, stone matrix asphalt and bituminous concrete those are used to carry wheel tracking test. The results are shown by using Marshall Test that 6% of CR content by weight if normal binder 60/70 content and optimum binder content for the binder in bituminous mixes is 5.1% & 5.5% by weight of mix is have improved the bituminous mixes. In addition, results indicated that the mixes prepared with a modified binder by CR are good in forming rut resisting mixes. The benefit of this study is the tires waste disposal in an environment-friendly way and better road to withstand rutting.

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An effective way to optimize decision-making regarding the transport mode choice in the transportation system is improving or changing the travel cost, the travel time, or some other travel characteristics by using sensitivity analysis. This method encourages travelers to switch from private transportation to public transport, thus reducing pollution and emission. Furthermore, by searching for the most sensitive factors in travel behavior, the sensitivity analysis might highlight the directions of the improvement. However, according to previous studies, travelers will transfer from one transport mode to another only if the utility of the new choice is higher than the original transport mode. In the current paper, sensitivity analysis is applied to provide a comparison between the impacts of the physical and sensory parameters on the travel behavior and transport mode choice based on a utility function. The multinomial logit (MNL) model is used to estimate and perform the sensitivity analysis of the main variables. The sensitivity analysis demonstrates the degree of the travelers’ sensitivity to changes in the travel characteristics including both physical and sensory parameters. The models are calibrated with the NLOGIT software and validated through statistical indicators; thus, the essential factors influencing the choices are obtained. The input variables selected for the models are based on the data collected in Budapest, Hungary. The sensitivity analysis is determined by the outputs of the variables based on the changes of the input variables. As the results show, the travelers have more sensitivity to the changes in the physical parameters. Furthermore, the outcomes indicate that the travel cost is an essential variable, which greatly affects the decisions related to the transport mode choice. From the sensory parameters, the comfort factor has more influence than other factors. The results of the analysis present that the travelers’ sensitivity to changes in the travel utilities of the travel characteristics impacts the decisions regarding the mode choice behavior significantly.