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Professor Chandra Bhat of University of Texas at Austin: Forecasting of Deadheading Trips by Ride-Hailing Vehicles

Publish Date: 2019/07/11 15:57:38    Hits:

On July 1st, from 10:30 to 12:00, Professor Chandra Bhat of the University of Texas at Austin was invited to visit our school and gave a report entitled "Forecasting of Deadheading Trips by Ride-Hailing Vehicles" in the New Main Building A949. Professor Haijun Huang, Professor Qiong Tian, Professor Tieqiao Tang, Professor Renyong Guo, Associate Professor Tianliang Liu, Dr.Chenlan Wang, and more than 100 students from the School of Economics and Management, School of Transportation, and Reliability College participated in this academic report.

At the conference, Professor Bhat vividly showed the formation of the Deadheading problem of ride-hailing vehicles, and introduced the car dataset from Ride Austin, including driver ID, passenger ID, start time, starting latitude and longitude, arrival time, arriving latitude and longitude and other information. Then, he introduced the economic model framework in detail, mainly by constructing a nonlinear multinomial Logit model. Based on the TAZ information of the previous passenger getting off, this model can predict the next pick-up location. By plotting the numberpassengers in Day-Hour distribution, it found that Friday and Saturday nights, as well as Saturday and Sunday mornings, were the peak hours of demand for ride-hailing vehicles. At the end of the report, Professor Bhat summed up his writing experience and share this to graduate students. He said that writing an academic paper is to write a story that cannot be stopped and constantly revised.

The teachers and students were touched by the academic passion of Professor Bhat and actively interacted with him. Finally, Professor Qiong Tian thanked Professor Bhat on behalf of School of Economics and Management. The report ended in the applause of teachers and students.

Introduction of the speaker:Dr. Chandra R. Bhat is a world-renowned expert in the area of transportation and urban policy design, with far reaching implications for public health, energy dependence, greenhouse gas emissions, and societal quality of life. Methodologically, he has been a pioneer in the formulation and use of statistical and econometric methods to analyze human choice behavior. His current research includes the social and environmental aspects of transportation, planning implications of connected and automated smart transportation systems (CASTS), and data science and predictive analytics. He is a recipient of many awards, including the 2017 Council of University Transportation Center (CUTC) Lifetime Achievement Award in Transportation Research and Education, the 2015 ASCE Frank Masters Award, and the 2013 German Humboldt Award. He was listed in 2017 as one of the top ten transportation thought leaders in academia by the Eno Foundation. He is also a top-cited transportation engineering researcher (web of science h-index of 51 and google scholar h-index of 83), and was listed in the most cited researchers in civil engineering by Shanghai Ranking's global ranking of academic subjects 2016 by Elsevier. He is the Editor-in-Chief of Transportation Research–Part B and a visiting professor in the Department of Civil and Environmental Engineering at Hong Kong Polytechnic University.