About Us

The Control and Intelligent Transportations Research Lab is housed in the OSU Center for Automotive Research and the Department of Electrical and Computer Engineering.

Our research and development interests include theoretical and applied research on autonomous or semi-autonomous cooperative mobile systems. Topics include planning, control, reinforcement learning, multi-agent interaction, computer vision, sensor fusion, behavior prediction, and decision making.

CITR has developed several hardware testbeds and simulation platforms.

News

[2023-05-25] Our paper “Automated Traffic Surveillance Using Existing Cameras on Transit Buses” has been published in the journal Sensors. Link

[2023-05-07] Congratulations! Our master students have graduated!:

[2023-03-20] Our book chapter “Risk Analysis for Vehicle–Pedestrian Interaction with Extended Sensing” has been published in the book Towards Human-Vehicle Harmonization . Link

[2023-03-13] Our paper “Using Collision Momentum in Deep Reinforcement Learning Based Adversarial Pedestrian Modeling” has been accepted for presentation at the 2023 IEEE Intelligent Vehicles Symposium.

[2023-01-22 ] Our paper “Lyapunov Stability Regulation of Deep Reinforcement Learning Control with Application to Automated Driving” has been accepted for presentation at the 2023 American Control Conference.

[2022-11-14] As part of our collaboration in the Center for Automated Vehicles Research with Multimodal Assured Navigation (CARMEN), our laboratory participated in organizing the semi-annual project symposium. The agenda from the symposium can be found here. The website from the project is here.

[2022] Our paper “A finite-sampling, operational domain specific, and provably unbiased connected and automated vehicle safety metric” has been published in the journal IEEE Transactions on Intelligent Transportation Systems . Link

[2022 ] Our paper “Data-Driven Risk-Sensitive Control for Personalized Lane Change Maneuvers.” has been published in the journal IEEE Access. Link

[2022] Congratulations! The following papers were accepted to the 10th IFAC Symposium on Advances in Automotive Control AAC 2022:
1. " A formal safety characterization of advanced driver assist systems in the car-following regime with scenario-sampling. " Link
2. " Dynamic and Interpretable State Representation for Deep Reinforcement Learning in Automated Driving "  Link
3. " Entropy Based Metric to Assess the Accuracy of PNT Information" Link

[2022] Our paper “Predicting pedestrian crossing intention with feature fusion and spatio-temporal attention” has been published in the journal IEEE Transactions on Intelligent Vehicles. Link

[2022] Our paper “Photorealism in Driving Simulations: Blending Generative Adversarial Image Synthesis With Rendering” has been published in the journal IEEE Transactions on Intelligent Transportation Systems. Link

[2022] Our paper “On the generalizability of motion models for road users in heterogeneous shared traffic spaces” has been published in the journal IEEE Transactions on Intelligent Transportation Systems. Link

[2021-11-14] Our paper “ An Online Evolving Method for a Safe and Fast Automated Vehicle Control System” has been accepted to the journal IEEE Transactions on Systems, Man and Cybernetics Systems.

[2021-11-12] Our paper “ Model-based Decomposition and Backtracking Framework for Probabilistic Risk Assessment in Automated Vehicle Systems” was presented at the 2021 International Topical Meeting on Probabilistic Safety Assessment and Analysis

[2021-11-12] Our paper “A Formal Characterization of Black-Box System Safety Performance With Scenario Sampling” has been published in the journal IEEE Robotics and Automation Letters. Link

[2021-10-30] Our paper “ Towards Guaranteed Safety Assurance of Automated Driving Systems with Scenario Sampling: An Invariant Set Perspective” has been published in Early Access for the journal IEEE Transactions on Intelligent Vehicles. Link

[2021-06-20] Congratulations! The following papers were presented in the 2021 Intelligent Transportation Systems Conference (ITSC) :
1. "Methodology for Hazard Identification and Mitigation Strategies Applied to an Overtaking Assistant ADAS" Link
2. "Pedestrian Emergence Estimation and Occlusion-Aware Risk Assessment for Urban Autonomous Driving" Link
3. "Faraway-Frustum: Dealing with Lidar Sparsity for 3D Object Detection using Fusion" Link

[2021-10-14] Congratulations! Professor Ümit Özgüner was recognized with the prestigious IEEE Lifetime Achievement Award for Intelligent Transportation Systems Research for a lifetime of pioneering contributions in research on intelligent vehicles and the founding of the IEEE ITS Society. You can find the press note here.

[2021-10-14] As part of our collaboration in the Center for Automated Vehicles Research with Multimodal Assured Navigation (CARMEN), our laboratory participated in organizing the semi-annual project symposium. The agenda from the symposium can be found here. The website from the project is here.

[2021-07-05] Our paper “ A Vision-Based Social Distancing and Critical Density Detection System for Covid-19” has been published in the journal Sensors. Link

[2021-05-15] Our master students Mert Koç and Zhitong He graduated and accepted positions at the company Oztech Inc. Our master student Haolin Zhang graduated and accepted a position at Zhejiang Huaruijie Technology Co., Ltd. Congratulations!

[2021-05-12] Congratulations! Professor Keith Redmill was recognized with the prestigious Lumley Research Award for his work focusing on intelligent transportation systems, autonomous vehicles and mobile robots, advanced safety and driver assistance systems, and the control, sensing, and communication technologies that make those systems possible. You can find the press note here.

[2021-01-31] Our paper “A Modeled Approach for Online Adversarial Test of Operational Vehicle Safety” was accepted to 2021 American Control Conference (ACC). PDF

[2020-12-15] Our doctoral students Teawon Han and Dongfang Yang graduated. Teawon has accepted a position at Ford Greenfields Lab and Dongfang has accepted a position at Chongqing Changan Automobile Software Tech Corp. Congratulations!

[2020-11-30] Our laboratory organized the event Pedestrians on the Roadway: A Workshop on Autonomous Vehicles Encountering Pedestrians. Slides from the workshop can be found here. Video playlist on Youtube.

[2020-07-11] Teawon Han presented his work "An Online Evolving Framework for Advancing Reinforcement-Learning based Automated Vehicle Control" at IFAC World Congress 2020. Check the recording at YouTube.

[2020-07-08] To help stopping COVID-19, CITR has developed a vision-based system for social distancing. Please check our new work: "A Vision-based Social Distancing and Critical Density Detection System for COVID-19". PDF GitHub

[2020-04-02] Congratulations! 3 papers from us were accepted into 2020 Intelligent Vehicles Symposium:
1. "A Multi-State Social Force Based Framework for Vehicle-Pedestrian Interaction in Uncontrolled Pedestrian Crossing Scenarios". PDF GitHub
2. "Integrating Deep Reinforcement Learning with Model-based Path Planners for Automated Driving".PDF
3. "Optical Flow Based Visual Potential Field for Autonomous Driving". PDF

[2020-03-12] Congratulations! Our following work was accepted into IFAC World Congress 2020: "An Online Evolving Framework for Advancing Reinforcement-Learning based Automated Vehicle Control". PDF

[2019-11-03] Welcome Dr. Ekim Yurtsever to join us as a postdoctoral researcher from Nagoya University!

[2019-03-08] The Ohio State University is to host "Explainable Artificial Intelligence for Driving Safety" review and workshop. CITR lab is honored to help to organize the event.