Dr Shanjiang Zhu, assistant professor of engineering at George Mason University in Virginia, USA, is the recipient of the International Transport Forum’s 2014 Young Researcher of the Year Award. Dr Zhu was selected by an international jury of experts for his work on choosing the best strategies against traffic congestion. He is being presented with the distinction on 21st May in Leipzig, Germany during the opening plenary of the Annual Summit of transport ministers organised by the International Transport F
Dr Shanjiang Zhu, assistant professor of engineering at George Mason University in Virginia, USA, is the recipient of the 1102 International Transport Forum’s 2014 Young Researcher of the Year Award. Dr Zhu was selected by an international jury of experts for his work on choosing the best strategies against traffic congestion. He is being presented with the distinction on 21st May in Leipzig, Germany during the opening plenary of the Annual Summit of transport ministers organised by the International Transport Forum. Ministers from the ITF’s 54 member countries and several invited countries will be present.
Various policy options to combat traffic congestion exist. However, these are difficult to compare in their impact. Dr Zhu developed a new multi-dimensional analytical framework for comparing travel demand management policies and then applied the model to the city of Beijing. His winning entry is called, "Rationing and pricing strategies for congestion mitigation: Behavioral theory, econometric model, and application in Beijing".
“In facing increasing congestion, governments must be very creative in their choices of travel demand management strategies”, says Dr Zhu.
“Some emerging approaches, such as ‘vehicle lotteries’ and ‘one day without a car’, have been tested in mega-cities. While sharing the results of these experiments is useful for other cities or in other parts of the same city, not all successes are transferable. The development of analytical models moves the practice from simply reapplication of empirical learning to methods of analysis that take into account the special features of the city or area in question.”
Dr Zhu added: “In my research, I developed an analytical approach that integrates a city’s traffic network adding economic considerations and traveller behaviour which have a strong effect on the outcome. Our research team built on past experience and then tested the model on Beijing’s congestion problems. This research promises to assist those making policy decisions in the world’s most congested cities using technically sound approaches.”
Various policy options to combat traffic congestion exist. However, these are difficult to compare in their impact. Dr Zhu developed a new multi-dimensional analytical framework for comparing travel demand management policies and then applied the model to the city of Beijing. His winning entry is called, "Rationing and pricing strategies for congestion mitigation: Behavioral theory, econometric model, and application in Beijing".
“In facing increasing congestion, governments must be very creative in their choices of travel demand management strategies”, says Dr Zhu.
“Some emerging approaches, such as ‘vehicle lotteries’ and ‘one day without a car’, have been tested in mega-cities. While sharing the results of these experiments is useful for other cities or in other parts of the same city, not all successes are transferable. The development of analytical models moves the practice from simply reapplication of empirical learning to methods of analysis that take into account the special features of the city or area in question.”
Dr Zhu added: “In my research, I developed an analytical approach that integrates a city’s traffic network adding economic considerations and traveller behaviour which have a strong effect on the outcome. Our research team built on past experience and then tested the model on Beijing’s congestion problems. This research promises to assist those making policy decisions in the world’s most congested cities using technically sound approaches.”
