International Journal of Transportation Engineering
Volume:9 Issue: 2, Autumn 2021

Understanding the effective variables on mode choice of grocery shopping trips is very important, considering the high frequency of these trips. Although previous studies show that attitudes (personal preference) play an essential role in mode choice, few studies investigate the effect of heterogeneity of these factors in mode choice of grocery shopping. This research investigates the role of socioeconomic, built-environment, lifestyle, attitude, and behavioral variables on taste variation of individuals in mode choice of grocery shopping trips. 398 individuals are surveyed in chain grocery stores of Tehran in May 2016 and factor analysis is used to identify latent variable such as safety, pedestrian-oriented, mode flexibility. Furthermore, a mixed logit (MXL) model is employed to test heterogeneity among individuals. Results of MXL model show that several socioeconomic, mode attributes and attitude variables have significant effects on mode choice for grocery shopping activities. Besides, male variable in bus mode and travel time in walking mode is heterogeneous variables among parameters with random normal distribution coefficient for grocery shopping destinations. Moreover, the results of the random coefficient analysis show that the existence of a shopping center in the CBD without parking spaces for bus mode and household car ownership (two or more) for walking mode are the primary sources of heterogeneity of grocery shopping trips. Findings suggest that considering policies like parking management, especially in CBD and development of public transit stations, based consistent with the development of pedestrian facilities, increase the likelihood of using transit. Also, policies like optimal grocery shopping malls sitting in all areas of the city increase the likelihood of using walking mode.

Millions of people die in road accidents every year. This issue is more important for professional drivers as they are more likely to involve in a car accident due to the longer driving hours. The purpose of this study was to identify the most important manner or factors affecting traffic accidents as well as the taxi driver’s characters based on the Drivers' Behavior Questionnaire (DBQ) and Emotionality Activity Sociability (EAS) temperament survey, a total number of 420 taxi drivers in Tehran province were asked to participate in this study and the results indicated that there is a remarkable relationship between driving history and anger management. The results also shows that the more driving experience the drivers have, the better they can manage their anger along with long-term plans and psychological classes. Finally, the correlation between the main variables of the research were measured and the findings revealed that the highest correlation pertains to that between temperament (anger, activity, helplessness, anxiety, sociability) and errors (0.995), and temperament driving offences of taxi drivers (0.474).

Risk analysis of the rail vehicles collision as one of the most important accidents with the rate of nearly 4 percent of the total accidents has always been of great interest especially for the railway safety decision makers. The reason might be revealed while considering the chain of causes and the scenarios of consequences. The superiority of modeling by Bayesian networks method for analyzing the risk of such accidents is that not only the conditional probability of each cause (hazard) as a variable is assessed but also with having any new evidence, the model can be updated subsequently and the consequences can be monitored. The methodology consists of two major categories of qualitative and quantitative parts while the concluded model is a mixture of the two methods. Main causes of a collision are grouped as environmental, signaling and human factors. Resulted model gives the highest probability to the shunting limit signal as a subdivision of the human errors. Evaluating the consequences resulted in the severity of “second degree” based on the Iranian railway accidents severity categorization guideline.

Organizations that provide intercity online taxi services are interested in clustering the community based on the car request rate to increase their service quality and examine all factors affecting this quality. Managers of online taxi systems are concerned about intercity service quality. Hence, they permanently update their knowledge of online taxi requests and their service quality. Managers became aware of service quality rates in different city districts based on their experiences, especially in Tehran, so that they decided to examine this issue. Accordingly, the purpose of this study is to examine the intercity transportation service quality of an online taxi company in 22 districts of Tehran, Iran. Using semi-structured and unstructured interviews with senior managers, the main variables were identified. The community clustering was also done using the K-means method and IBM[1] Software. Results showed that the classification of senior managers of this company regarding their service qualities, as well as the experiences and platforms of similar foreign companies, could not be used as an appropriate reference to examine intercity service quality in different districts. Therefore, driver rating, driver performance, and accepted request volume were the most important issues in district clustering followed by passenger rating. However, the variables mentioned were previously ignored.

Transit Routes Design (TRD) problem deals with optimizing the configuration of transit routes to satisfy a given objective, such as maximizing network coverage, while holding the budget constraint. In its discrete form, TRD is recognized as a computationally interactive problem. A review of the literature reveals that, despite extensive research on this problem, the number of studies on specific urban network configurations has remained limited. Among these studies, many have applied simplifying assumptions such as continuous design variables which may not be applicable to real-world settings. The present study focuses on a discrete version of the TRD problem for an urban “grid” network and aims to maximize the service coverage through the network. To this end, a local search Hill-Climbing (HC) heuristic algorithm is proposed and evaluated. The proposed HC algorithm performs several replications in which it starts with a combination of randomly selected routes and iteratively improves them by moving to the “best neighbour” until it reaches a local optimum solution. Our results for a 6×10 grid network for three budget levels (i.e. low, medium, and high budget levels) indicate that, in much shorter run-times than the exact algorithm, the proposed HC algorithm can produce high-quality solutions with 0.12%, 4.16%, and 2.22% difference from global optimums.

One way to change the allocation of road resources to traffic demand is to convert two-way roads into one-way streets. This conversion can be done for a variety of reasons such as insufficient street width for two-way traffic, reducing delay at intersections, increasing safety and reducing congestion. In the city of Yazd, the urban road network has very few one-way thoroughfares and its traffic flow directions have not been optimally configured to solve the traffic problems of this city. Converting two-way streets into one-way routes may therefore serve as a means of better traffic management in the central district of this city. In this research, after a review of the literature, the physical and traffic characteristics of main roads in the central district of Yazd were investigated through a field study in order to identify the two-way roads that are technically and practically eligible for conversion into one-way. The results of the field study, which were obtained from 78 data collection stations, were then used to build a simulation model in the Aimsun software. The network was then calibrated and prepared for the execution of the scenarios. The results indicated that as long as the number of trips ending in or passing through the area remains the same, these streets cannot be made one-way and All scenarios have worse results than the current situation.Finally, the proposed scenarios were re-simulated with the assumption of a 30% decrease in travel demand in the area.It was found that scenario 6 offers better outcomes than other options and it is practically impossible to make the streets one-way without reducing the demand for private transport.