Image Processing Based Vehicle Driving Behavior Calibration

Self-driving cars have become more and more popular in academia and industry. An increasing number of self-driving cars are tested on public roads across the US. However, there does not exist sufficient datasets about how self-driving cars drive in the traffic environment. In this project, we will use several open datasets to understand such question. The student involved in this project will assist Ph.D students to analyze both human-driven vehicles and autonomous vehicles driving datasets. Students with good computer and coding skills are preferred. Skill requirements are: 1. using Python to extract data in required format, process and analyze data; 2. using Python to plot driving patterns of both human-driven and self-driving vehicles; 3. generating figures, graphs, tables, or statistical models to present results.

Lab: DiTecT

Direct Supervisor: Sharon Di

Position Dates: 5/20/2019 - 8/31/2019

Hours per Week: 20

Paid Position: No

Credit: Yes

Positions Available: 1

Qualifications: Computer programming and coding

Eligibility: Freshman, Sophomore, Junior, Senior; SEAS only

Professor Sharon Di, xd2187@columbia.edu, Mudd 630, 2128530435