Mostafa Amin-Naseri

StaticsTutor: Free Body Diagram Tutor for Problem Framing

While intelligent tutoring systems have been designed to teach free-body diagrams, existing software often forces students to define variables and equations that may not be necessary for conceptual understanding during the problem framing stage. StaticsTutor was developed to analyze solutions from a student-drawn diagram and recognize misconceptions at the earliest stages of problem framing, without requiring numerical force values or the need to provide equilibrium equations. Preliminary results with 81 undergraduates showed that it detects several frequent misconceptions in statics and that students are interested in using it, though they have suggestions for improvement. This research offers insights in the development of a diagram-based tutor to help problem framing, which can be generalized to tutors for other forms of diagrams.

Quantitative analysis of probe data characteristics: Coverage, speed bias and congestion detection precision

Abstract In recent years, there has been a growing desire for the use of probe vehicle technology for congestion detection and general infrastructure performance assessment. Unlike costly traditional data collection by loop detectors, wide area detection using probe-based traffic data is significantly different in terms of the nature of data collection, measurement technique, coverage, pricing, and so on. Although many researches have studied probe-based data, there remains critical questions such as data coverage and penetration over time, or the influential factors in the accuracy of probe data. This research studied probe-sourced data from INRIX, to profoundly explore some of these questions. First, to explore coverage and penetration, INRIX real-time data was illustrated temporally over the entire state of Iowa, demonstrating the growth in real-time data over a 4-year timespan. Furthermore, the availability of INRIX real-time and historical data based on type of road and time of day, were explored. Second, a comparison was made with Wavetronix smart sensors, commonly used sensors in traffic management, to explore INRIX’s speed data quality. A statistical analysis on the behavior of INRIX speed bias, identified some of the influential factors in defining the magnitude of speed bias. Finally, the accuracy and reliability of INRIX for congestion detection purposes was investigated based on the road segment characteristics and the congestion type. Overall, this work sheds light onto some of the less explored aspects of INRIX probe-based data to help traffic managers and decision makers in better understanding this source of data and any resultant analyses.

Investigating the relationship between traffic incidents and public events: A case study

Large social events can influence traffic conditions and possibly lead to jams and incidents. This study leverages crowdsourced data to analytically evaluate the relationship between social events and traffic incidents in the city of Chicago. In particular, we collected data on social events from scraping online webpages, as well as traffic data from a twitter account that posted irregular traffic incidents based on a crowdsourced navigation application (Waze). Using these two sources the relationship between social events and the occurrence of traffic incidents was investigated. The total number social events and their categories for each region and its neighboring regions were used to build models that predicted the chance of a traffic incident occurrence.