Traffic characteristics on the road network in NTU campus

• Main Author: Lim, Zhu Liang.
• Other Authors: Fan Shing Leung, Henry
• Format: Final Year Project
• Language: English
• Published: 2010
• Subjects: DRNTU::Engineering::Civil engineering::Transportation
• Online Access: http://hdl.handle.net/10356/39551
• Institution: Nanyang Technological University

This project aims to study the traffic characteristics on the road network in Nanyang Technological University (NTU) campus. The scope of study was confined within the area where North and South Academic Complex are located as this area usually experiences the heaviest traffic. The speed and volume of vehicles, the behavior of drivers, the traffic volume distribution and the effectiveness of intersections form the overall traffic characteristics in NTU campus. The traffic volume data were collected from three selected intersections in NTU, namely Hall 1 T-junction, Innovation T-Junction and School of Art, Design & Media (ADM) Roundabout. From the volume of traffic that passed through these three intersections, the traffic volume distribution of NTU campus can be calculated. The traffic volume was also used to access the performance of the three intersections. The speed data were collected for the main roads within NTU campus, namely Nanyang Ave, Nanyang Drive and Lien Ying Chow Drive. The speed data shows that most drivers do not generally follow the speed limit of 40 km/h enforced in NTU. The performance of roundabout is the function of each individual entry arms. The volume data were used to estimate the entry arms capacity which in turn used to calculate the degree of saturation to determine its level of capacity. Control delay time at each entry arms was also estimated and the level of service was determined. The results showed that two of the entry arms are in critical conditions as they have reached their maximum capacity and the control delay time was deemed unacceptable. This project provided precious traffic data like traffic volume, traffic composition, speed data, peak hour factor and traffic volume distribution which could pave the path for future studies to provide remedies that could improve the traffic conditions in NTU campus.