Document Details
|
Document Type |
: |
Thesis |
|
Document Title |
: |
EFFECT OF HEAVY VEHICLES ON TRAFFIC FLOW PARAMETERS: CASE STUDY OF AL-HARAMAIN FREEWAY, JEDDAH, SAUDI ARABIA تأثير المركبات الثقيلة على متغيرات التدفق المروري: حالة دراسية ، طريق الحرمين السريع ، جدة ، المملكة العربية السعودية |
|
Subject |
: |
Faculty of Engineering - Department of Civil Engineering |
|
Document Language |
: |
Arabic |
|
Abstract |
: |
Roadway networks, particularly urban freeways, and number of vehicles have increased very rapidly in Kingdom of Saudi Arabia during the last three decades. In order to optimize freeway traffic flow, understanding of interrelation among basic characteristics of vehicular traffic flow, speed, and density is important to traffic engineers. In addition, knowledge of speed-flow-density characteristics is required for estimation of highway capacity. Freeways are generally designed to serve mixed traffic flow consisting of passenger cars and heavy vehicles. However, operating characteristics of heavy vehicles differ significantly from those of passenger cars as they travel relatively slowly and occupy larger space. Passenger-car Equivalent (PCE) is used to account for heavy vehicles in traffic stream for obtaining aggregate speed-flow-density relationships.
This study is aimed to model relationship among average headway, proportion of heavy vehicles in traffic stream, and traffic density in order to estimate PCE for heavy vehicles in urban freeways in Saudi Arabia. The study also aims to develop speed-flow-density relationship for urban freeways in Saudi Arabia by using logistic framework and stochastic approach.
A typical basic section within Al-Haramain Freeway, located in Jeddah, was selected as case study section. Traffic parameters including volume counts, vehicle classification, and speed were collected for each lane of the freeway during uncongested and congested traffic conditions. Samplings data were collected and analyzed using video image recorders with subsequent machine vision processing programs.
The PCE estimation model developed in this research includes proportion of heavy vehicles and traffic density to estimate PCE for heavy vehicles. While Highway Capacity Manual (HCM) of 2000 considers average value of 1.5 for PCE for all levels of service for the freeway, proposed model produces different PCE values during uncongested and congested traffic conditions covering all levels of service. Average of these PCE values during uncongestion and congestion was 1.48 and 3.05 respectively.
The PCE estimation model may be utilized as tool to help traffic engineers in assessing impact of heavy vehicles in traffic stream during uncongested and congested traffic conditions. The model will also facilitate estimation of effect of heavy vehicles on traffic flow under local condition.
Logistic speed-flow-density model, developed in this study using estimated PCE values, suggests that capacities of the right-most (shoulder) lane and the left-most (median) lane are 2089 pc/h and 3102 pc/h respectively. These values are greater than those found out based on PCE value suggested in the Highway Capacity Manual. In addition, capacity of 2400 pc/h/ln estimated by the curves of HCM 2000 is low compared to the values obtained from the logistic model for all lanes, except for the right-most lane. Stochastic behavior was incorporated by extending the logistic model to include randomly distributed parameters in order to grasp aggregate traffic stream patterns more precisely.
The stochastic logistic speed-flow-density model can be used to evaluate operational efficiency and estimate capacity of urban freeways in Saudi Arabia. In addition, it may be utilized to forecast traffic volumes projections that assist in preparation for future traffic demand. Moreover, stochastic logistic model may be used to support freeway management strategies and Intelligent Transportation System (ITS) applications by forecasting future traffic conditions under variable traffic circumstances. |
|
Supervisor |
: |
Prof. Dr. Mohammad Jobair Bin Alam |
|
Thesis Type |
: |
Doctorate Thesis |
|
Publishing Year |
: |
1433 AH
2011 AD |
|
Co-Supervisor |
: |
Dr. Hamed Omar Albar |
|
Added Date |
: |
Tuesday, December 13, 2011 |
|
Researchers
| علي عثمان مليباري | Melibari, Ali Othman | Researcher | Doctorate | |
|
Back To Researches Page
|