Modeling metro users' travel behavior in Tehran: Frequency of Use

Transit-oriented development (TOD), as a sustainable supporting strategy, emphasizes the improvement of public transportation coverage and quality, land use density and diversity around public transportation stations and priority of walking and cycling at station areas. Traffic, environmental and economic problems arising from high growth of private cars, inappropriate distribution of land use, and car-orientation of the metropolitan area, necessitate adoption of TOD. In recent years, extensive research into urban development and transportation has focused on this strategy. This research in which metro stations are considered as a base for development, aims to model metro users' travel behavior and decision-making procedures. In this regard, the research question is: what are the parameters or factors affecting the frequency of travel by metro in a half-mile radius from stations. The radius was determined based on TOD definitions and five-minute walking time to metro stations. A questionnaire was designed in three sections that include travel features by metro, attitudes toward metro, and economic and social characteristics of respondents. Ten stations were selected based on their geographic dispersion in Tehran and a sample of 450 respondents was determined. The questionnaires were surveyed face to face in (half-mile) vicinity of metro stations. Based on a refined sample on 400 questionnaires ordered discrete choice models were considered. Results of descriptive statistics show that 38.5 percent of the sample used metro more than 4 times per week. Trip purpose for 45.7 percent of metro users is work. Access mode to the metro stations for nearly half of the users (47.6 percent) is bus. The results of ordered logit models show a number of significant variables including: habit of using the metro, waiting time in stations, trip purpose (working, shopping and recreation), personal car access mode to the metro station, walking access mode to the metro station and being a housewife

TRAFFIC INFORMATION USE MODELING IN THE CONTEXT OF A DEVELOPING COUNTRY

The use of traffic information in the form of radio reports, as a solution to the problem of congestion, is one of the issues, which is of particular importance for large cities like Tehran. In this study, factors affecting the use of traffic information in the context of a developing country are examined for commuters in the city of Tehran using ordered logit models. Results based on the particular survey designed for this purpose are compared to those of a developed country. Regarding the use of information in the form of listening to the radio traffic reports, the models show that older commuters, commuters who adjust their departure time according to traffic conditions (those who are sensitive to traffic congestion), commuters with longer preferred arrival time at work, and those with longer total travel time, have a greater propensity to listen to traffic reports and use to them

A Direct Demand Model of Departure Time and Mode for Intercity Passenger Trips

Travel demand is well announced as a crucial component of transportation planning. This paper aims to develop a direct demand model, denoting a more acceptable abstraction of reality, for intercity passengers in daily work and leisure trips in Tehran province. The model utilizes combined estimation across the data source, collected in 2011, of travelers originating from the city of Tehran and heading toward two destination clusters: intra-province and inter-province. The paper sketches a way to predict simultaneous choice of departure time and travel mode under the influence of zonal (origin, destination, and residence), individual and household socio-demographic, and trip-related variables. The time frame for analysis of departure time is [5-19] and available modes are auto, taxi, bus, and metro. Multinomial Logit (MNL) and Nested Logit (NL) models as behavioral models are selected from discrete choice family to provide appropriate direct demand structure. Besides, the paper discusses Independent Irrelative Alternative (IIA) assumption of the models and demonstrates choice order of NL; Travelers choose departure time prior to mode at first level and then decide on mode at second level. Finally, travel demand elasticity and marginal effect with respect to travel time, age, and auto cost are also highlighted

Role of Children in Parents’ Car Use Behavior

This paper demonstrated how related variables of children’s school trips and the principle factors of the theory of planned behavior(TPB) influence parents’ car use behavior along with socio demographic factors. An urban Iranian sample from Tehran, consisting of parents (men and women) with primary-school children was asked to fill in physical questionnaires. Sample characteristics next revealed by descriptive statistics. A block regression analysis was utilized to explore first; how TPB’s factors and second; how children’s transportation’s related-variables increase the explained variance of parents’ car use behavior beyond socio- demographic factors. Results show both TPB’s factors and children’s transportation block increased the explained variance of parents’ car use behavior beyond socio demographic variables. Finally results are discussed due to the hierarchy pattern in the models

Fuzzy random utility choice models: the case of telecommuting suitability

ABSTRACT: Random utility models have been widely used in many diverse fields. Considering utility as a random variable opened many new analytical doors to researchers in explaining behavioral phenomena. Introducing and incorporating the random error term into the utility function had several reasons, including accounting for unobserved variables. This paper incorporates fuzziness into random utility models to account for the imprecision of data intrinsic in human perception and statement. Fuzzy variables are contrasted with random variables, and a model is presented of relationships among real, perceived, and stated/reported conditions. The proposed fuzzy approach is applied to modeling telecommuting suitability, using data gathered from 242 employees in Tehran, Iran to construct fuzzy membership functions of job-tasks to the fuzzy set of telecommuting suitability. The resulting utility function can be viewed as representing the global wisdom of respondents. The enhancement in the fuzzy random utility model results, although modest, is promising and sets the stage for further research in the field of fuzzy logit models

Comparative Analysis of Safety Performance Indicators Based on Inductive Loop Detector Data

Conflicts in traffic stream have been detected by different safety performance indicators. This study aims to empirically investigate the differences between different indicators in detecting rear-end conflicts and assessing the risk in an uninterrupted flow. Micro-level data of a 24-hr traffic stream (including 6,657 vehicles) were captured using inductive loop detectors installed on a rural freeway section. Different indicators (Time Headway (H), Time to Collision (TTC), Proportion of Stopping Distance (PSD), Deceleration Rate to Avoid Collision (DRAC) and Stopping Distance Index (SDI)) were used to measure each car following event in a bivalent state (safe/unsafe). Unsafe events associated with each indicator were detected and common unsafe events characterized by different indicators were identified. Temporal distributions of rear-end collision risks associated with each indicator at 15-min intervals were also compared. Finally, the 15-min risk values based on different indicators were categorized and compared across three levels (Low, Medium and High). Data mining and statistical techniques showed that while SDI is the single most conservative indicator, DRAC and TTC detect a few risky events but very equal ones. In almost all conflicts associated with TTC, headway is still lower than the critical threshold. However, there exist considerable risky events based on headway which are still safe according to TTC. Comparison of PSD and TTC also declares that almost all conflicts associated with TTC are also risky according to PSD

Final analytical comparison of aggregate and disaggregate mode choice models transferability

ABSTRACT: Transportation models as tools for transportation planning are critical to such related decisions. Considering the high cost of calibrating and validating such models, effective alternatives are highly sought for; one such alternative being the use of models calibrated for other cities. This calls for transferability analysis which has not been the subject of many researches. Due to criticality of aggregate and disaggregate data in transportation models, this paper tries to compare transferability of models calibrated with data of both groups. Mode choice models for daily work trips in two real-sized cities of Qazvin and Shiraz are analyzed. Models are calibrated employing multinomial logit structure with four modes of private car, taxi, bus, and 2-wheelers. In order to increase reliability of results, the top five best models are selected for each city-data category to be transferred. Based on transferability test statistics, transfer index, and goodness-of-fit of transfer models, aggregate models are not transferable and their results are deceptive. Transferability measures of these models are not in acceptable range; whereas transferability of disaggregate models have relative proper response. According to transfer index and goodness-of-fit of origin models operate similar to destination models. However transferability test statistics rejects the assumption of equality coefficients in both cities models. Using personal variables helps to effectively transfer origin models in addition to improve them

Prediction of Pervious Concrete Permeability and Compressive

Abstract: admixtures. The hydrological property of pervious concrete is the primary reason for its reappearance in construction. Much research has been conducted on plain concrete, but little attention has been paid to porous concrete, particularly to the analytical prediction modeling of its permeability. In this paper, two important aspects of pervious concrete due data. The proposed network is intended to represent a reliable functional relationship between the input independent variables accounting for the variability of permeability and compressive strength of a porous concrete. Results of the higher values were observed for the permeability as compared with compressive strength and for the train data set concrete when there are no laboratorial data available

Prediction of pervious concrete permeability and compressive strength using artificial neural networks

ABSTRACT: Pervious concrete is a concrete mixture prepared from cement, aggregates, water, little or no fines, and in some cases admixtures. The hydrological property of pervious concrete is the primary reason for its reappearance in construction. Much research has been conducted on plain concrete, but little attention has been paid to porous concrete, particularly to the analytical prediction modeling of its permeability. In this paper, two important aspects of pervious concrete due to permeability and compressive strength are investigated using artificial neural networks (ANN) based on laboratory data. The proposed network is intended to represent a reliable functional relationship between the input independent variables accounting for the variability of permeability and compressive strength of a porous concrete. Results of the Back Propagation model indicate that the general fit and replication of the data regarding the data points are quite fine. The R-square goodness of fit of predicted versus observed values range between 0.879 and 0.918 for the final model; higher values were observed for the permeability as compared with compressive strength and for the train data set rather than the test data set. The findings can be employed to predict these two important characteristics of pervious concrete when there are no laboratorial data available

Capacity drop estimation based on stochastic approach applied to Tehran-Karaj freeway

ABSTRACT: Existence of capacity drop phenomenon, as the difference between pre-queue and queue discharge flow rates, has been one of the controversial concepts of traffic engineering. Several researches have focused on capacity drop existence and also its estimation issues. This paper aims to estimate capacity drop based not only on a comparison between breakdown and queue discharge flow rates, but also on the estimation of the capacity distribution function before and after breakdown. In the empirical case, speed and flow rate data are collected in a section of Iran’s most crowded freeway for four months, based on which the threshold speed as the boundary between congested and non-congested flow is determined, and breakdown flow rates and their subsequent queue discharge flows are detected. Paired t-test between pre-queue and queue discharge flow rates is conducted to find the mean difference. Also, the distribution function of capacity under non-congested and congested flow is estimated using maximum likelihood and product limit methods. Based on the 11,600-record data set, it was observed that end results of both methods are consistent, revealing roughly five percent drop in capacity for the section under investigation