We are pleased to announce the doctoral thesis presentation of Mr. Yu Xiao, a third-year doctoral student in our laboratory, as follows.
If you are interested in attending, please contact Prof. Fukuda (fukuda[at]plan.cv.titech.ac.jp.)
Published by: Yu Xiao
Research Title: Valuing Travel Time Reliability: Individual, System and Dynamic Perspectives
Principal Investigator: Associate Professor Daisuke Fukuda
Associate Investigators (tentative): Prof. Yasuo Asakura, Prof. Tetsuo Yagai, Prof. Taitoku Muromachi, Prof. Shinya Hanaoka, Prof. Seiichi Fumi (Graduate School of Economics, Kyoto University)
Time: January 5, 2012 (Tuesday) 10:45-12:15 a.m.
Venue: Tokyo Institute of Technology, Midorigaoka Hall 5 (Creation Project Hall) 1F Conference Room
“Valuing Travel Time Reliability: Individual, System and Dynamic Perspectives”
Yu Xiao
(Abstract)
Traffic congestion is a widespread social problem and needs to be settled by sophisticated transport management and investment. The technological advances in monitoring traffic conditions allow the stochastic features of travel time to be better captured and managed, which leads to potentially large benefits to users of transport system. The guideline of cost-benefit analysis worldwide needs to be modified into one that accounts for the benefits of emerging reliability-improving schemes.
This dissertation is dedicated to the theoretical framework in including travel time variability (unreliability) into cost-benefit analysis, with a particular focus on the monetary value attached to unit improvement of travel time reliability. This thesis can be divided into two parts: (1) understanding traveler’s decision when facing variable travel time and (2) modeling transport system with variable supply.
The first part, including Chapter 3, is particularly concerned with estimation of the cost of travel time variability. It analyzes how systematic perception errors in travel time distribution might bias the estimates and undermine the theoretical equivalence between the structural model and reduced-form model. Empirical estimation on these bias is carried out using stated preference data.
The second part, including Chapter 4 and Chapter 5, is concerned with the system (social) cost when travelers are constantly searching for lower travel cost while the transport system are constantly facing random shocks. Taking travel time variability as given, Chapter 4 uses a stylized departure-time equilibrium approach to study how system cost of a traffic bottleneck varies with travel time variability when congestion profile depends on traveler’s collective behavior. It discusses how the conventional definition of value of travel time variability can be modified and fitted in the existing framework of cost-benefit analysis for transport investment to better capture the effects of endogenized congestion. On contrary, Chapter 5 challenges the assumption of stable equilibrium by arguing that the system might not have a stable equilibrium in some case and travel time variability is also a phenomena of traveler’s day-to-day behavior adjustment. It uses simulation to investigate how much travelers’ day-to-day departure time adjustment contributes to the travel time variability and the time-average travel cost in a long run.
In summary, the two parallel parts deal with the valuation of travel time variability from different angles, contributing new insights on using reliability as an indicator for transport user’s benefit. I hope it could shed some lights for both researches and practitioners on the route to providing more reliable transport services.
