Educational games proved to be effective tools to support transportation engineering education. Our group has been actively developing educational games for teaching transportation engineering classes. This work identifies the key concepts in transportation engineering that can be gamified. Five games were developed targeting five areas in transportation. The developed games are Transporters for planning, Time-space Invaders for signal control, DZ-Man for safety, Angry Curves for highway design, and Road Crush for pavement design. All the games can be played online after users’ registration and logging-in. The users’ gameplay data are uploaded to a server. A record of gameplay data include the user name, the game played, the level number in the game, the game parameters (e.g., the game scores), and the time that record was generated. We evaluated the effectiveness of the games with before and after studies. The students were asked to do quizzes after learning a certain concepts during the class. The quizzes were targeting the concepts taught in the class. Students were asked to play a game targeting the same concepts and to answer the same quizzes again. We compared the quizzes scores before and after the gameplay to tell the effectiveness of the games. The games were evaluated in 2014 and 2015 during a transportation introductory class. The results showed that for all the tested games, the overall students’ quizzes scores increased. T-Tests were conducted for each evaluation and the results showed the increases were statistically significant. The results indicate that the games can improve students’ learning outcomes significantly. This paper can be used to guide developers to build new games for transportation engineering education. The paper can also be useful for transportation educators who want to implement games in their teaching practice.
Qichao Wang is a Ph.D. student in the Transportation Infrastructure and Systems Engineering program at Virginia Tech. He holds a Bachelor of Engineering in Traffic Engineering from Nanjing Tech University, P.R.China (2014). His research interests include 3D visualization, traffic control, multi-agent system, and optimization.
Dr. Montasir Abbas is an Associate Professor in the Transportation Infrastructure and Systems Engineering at Virginia Tech. He holds a Bachelor of Science in Civil Engineering from University of Khartoum, Sudan (1993), a Master of Science in Civil Engineering from University of Nebraska-Lincoln (1997), and a Doctor of Philosophy in Civil Engineering from Purdue University (2001).
Dr. Abbas has wide experience as a practicing transportation engineer and a researcher. He was an Assistant Research Engineer and the Corridor Management Team Leader at Texas Transportation Institute (TTI), where he has worked for four years before joining Virginia Tech. Dr. Abbas conducted sponsored research of more than $720,000 as a principal investigator and more than $750,000 as a key researcher at TTI. After joining Virginia Tech, he has conducted over $2,400,000 worth of funded research, with a credit share of more than $1,750,000.
Dr. Abbas is an award recipient of $600,000 of the Federal Highway Administration Exploratory and Advanced Research (FHWA EAR). The objective of the FHWA EAR is to “research and develop projects that could lead to transformational changes and truly revolutionary advances in highway engineering and intermodal surface transportation in the United States.” The award funded multidisciplinary research that utilizes traffic simulation and advanced artificial intelligence techniques. He has also conducted research for the National Cooperative Highway Research Program on developing “Traffic Control Strategies for Oversaturated conditions” and for the Virginia Transportation Research Council on “evaluation and recommendations for next generation control in Northern Virginia.”
Dr. Abbas developed Purdue Real-Time Offset Transitioning Algorithm for Coordinating Traffic Signals (PRO-TRACTS) during his Ph.D. studies at Purdue University, bridging the gap between adaptive control systems and closed-loop systems. He has since developed and implemented several algorithms and systems in his areas of interest, including the Platoon Identification and Accommodation system (PIA), the Pattern Identification Logic for Offset Tuning (PILOT 05), the Supervisory Control Intelligent Adaptive Module (SCIAM), the Cabinet-in-the-loop (CabITL) simulation platform, the Intelligent Multi Objective Control Algorithms (I-MOCA), the Traffic Responsive Iterative Urban-Control Model for Pattern-matching and Hypercube Optimal Parameters Setup (TRIUMPH OPS), the Multi Attribute Decision-making Optimizer for Next-generation Network-upgrade and Assessment (MADONNA), and the Safety and Mobility Agent-based Reinforcement-learning Traffic Simulation Add-on Module (SMART SAM). He was also one of the key developers of the dilemma zone protection Detection Control System (D-CS) that was selected as one of the seven top research innovations and findings in the state of Texas for the year 2002.
Dr. Abbas served as the chair of the Institute of Transportation Engineers (ITE) traffic engineering council committee on “survey of the state of the practice on traffic responsive plan selection control.” He is also a member of the Transportation Research Board (TRB) Traffic Signal Systems committee, Artificial Intelligence and Advanced Computing Applications committee, and the joint subcommittee on Intersection. In addition, he is currently a chair on a task group on Agent-based modeling and simulation as part of the TRB SimSub committee. He also serves as a CEE faculty senator at Virginia Tech.
Dr. Abbas is a recipient of the Oak Ridge National Lab Associated Universities (ORAU) Ralf E. Powe Junior Faculty Enhancement Award and the G. V. Loganathan Faculty Achievement Award for Excellence in Civil Engineering Education. He is also a recipient of the TTI/Trinity New Researcher Award for his significant contributions to the field of Intelligent Transportation Systems and Traffic Operations.
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