Spatial Seemingly Unrelated Regression Models for Freight Trip Generation by Vehicle Type: Application to the Chennai Metropolitan Area in India

During the last two decades, there has been substantial interest in developing freight trip generation (FTG) models. Most studies consider only truck trips or convert all freight trips into equivalent truck trips. Freight in several large cities is increasingly being moved by smaller vehicles. This calls for modeling FTG by vehicle type. The present research identifies and compares establishment characteristics affecting FTG by different vehicle types. In this context, spatial correlations among nearby establishments and the error-term correlations between independent models by vehicle type become relevant. Based on the Lagrange-Multiplier (LM) tests, we develop non-spatial seemingly unrelated regression (SUR) models for freight trip production (FTP) and spatial SUR models with a spatial lag in the dependent variable to account for both spatial and error-term correlations for freight trip attraction (FTA). The results show that establishment type and size affect FTG by different vehicle types.

Review of the Land Use Variables Affecting the Transportation Behaviour, Review paper

The aim of this paper is to review research conducting the impact of land use variables on the travel behaviour. It is focused on the density as an important measure of land use that reflects the interaction with the transportation system. The effect of density has been addressed years ago; therefore, papers have been published since 1960s were reviewed in this paper. These papers are classified into two groups according to the most common measure of the density and the most common variables of the travel behaviour considered in these researches. The first group contains about 26 papers published before 2000 while the second group contains about 45 papers published after 2000. It has been noticed that the population density is the main term of density used in the first group while the employment density and the configuration of densities are integrated as measures in the papers published after 2000. The direct relationship with mode choice and travel length has been approved. However, there are some gaps are identified in the discussion and conclusion sections, such as the effect on the trip production rate, the type of trips according to its purposes, internal and external, and weekdays and weekend.

MODELING PUBLIC TRANSPORT USERS’ TRIP PRODUCTION IN HAWASSA CITY, ETHIOPIA

Today, overcrowded public transport demand, resulting in huge costs in an urban area. Similarly, there are a lot of people who use public transport in Hawassa city. This study aimed to develop public transport users' trip production models at the household level. Some socio-economic characteristics and trip detail of the public transport users were collected randomly from the different households through a questionnaire survey. The data gathered was fed into IBM SPSS package version 20 to develop linear regression models. The developed models are associated with trips for purpose and time intervals of trips made. The developed linear regression models, general trips, work trips, educational trips, and trips made before 8:00 AM and after 4:00 PM had good explanatory power. The value of explanatory power comprised of 0.656, 0.722, 0.549, 0.610 and 0.510. These values indicated the explanation power of the socio-economic characteristics on the trips made. It means the daily trips production was significantly affected by the number of working individuals, the different age brackets, cars and motorcycles, and the monthly income per household. The most frequent public transport users’ trips production regarding the trip purpose and time are work trips and occurred after 4:00 PM. This scenario represented a good model developed in this study. Hence, it is suggested that Hawassa city’s traffic management office use the developed models to predict the future trips demand to provide a proper scheme to avoid congestion during the peak hour of the day.

Modeling Public Transport Users’ Trip Production in Hawassa City, Ethiopia

Today, overcrowded public transport demand, resulting in huge costs in an urban area. Similarly, there are a lot of people who use public transport in Hawassa city. This study aimed to develop public transport users' trip production models at the household level. Some socio-economic characteristics and trip detail of the public transport users were collected randomly from the different households through a questionnaire survey. The data gathered was fed into IBM SPSS package version 20 to develop linear regression models. The developed models are associated with trips for purpose and time intervals of trips made. The developed linear regression models, general trips, work trips, educational trips, and trips made before 8:00 AM and after 4:00 PM had good explanatory power. The value of explanatory power comprised of 0.656, 0.722, 0.549, 0.610 and 0.510. These values indicated the explanation power of the socio-economic characteristics on the trips made. It means the daily trips production was significantly affected by the number of working individuals, the different age brackets, cars and motorcycles, and the monthly income per household. The most frequent public transport users’ trips production regarding the trip purpose and time are work trips and occurred after 4:00 PM. This scenario represented a good model developed in this study. Hence, it is suggested that Hawassa city’s traffic management office use the developed models to predict the future trips demand to provide a proper scheme to avoid congestion during the peak hour of the day.