STANDARD Project Team

Ms. Garavig Tanaksaranond
PhD Candidate

Visualization of Traffic Congestion

Traffic congestion can be defined as to when the volume of traffic is close to or exceeding the road capacity. Measured variables from monitoring devices such as speed, flow, density, or delay; then, grading the severity of traffic congestion can be used to quantify severity of traffic congestion. Among traffic flow variables that are captured from the road, travel time (and speed that can be derived from travel time) is the most popular congestion indicator since travel time (or speed) can be measured directly from the roadways and it can be easily understood by ordinary road users or by the technically inclined persons (ECMT, 2007). The purpose of this research is to develop visualization to study traffic congestion in space-time within the city from the already available vast amount traffic monitoring data. Visualization will provide spatio-temporal information and thus will facilitate decision making to traffic manager. Combining database technology, visualization system will provide swiftly generated display; and the interactive function will allow users to access the data directly. We hope that the visualization system can inform users to understand how congestion develop, move, disperse, and dissipate along the road network in the city.


Principal Investigator
Dr. Tao Cheng

Prof. Benjamin Heydecker

Research Fellows
Dr. Ioannis Tsapakis
Dr. Jiaqiu Wang

Research Students
Mr. Berk Anbaroglu
Mr. James Haworth
Mr. Ed Manley
Ms. Garavig Tanaksaranond

Industrial Partners at TfL
Mr. Andy Emmonds
Mr. Jonathan Turner
Mr. Alexandre Santacreu

alt: Research Poster
Sponsored By:     University College London   Transport For London   Engineering and Phyical Research Council