The events will occur in the span of a week, starting on Saturday, Aug. 5, when Billy Joel and Stevie Nicks play at the stadium, followed by a Tuesday, Aug. 8, performance by Mötley Crüe and Def Leppard.

Then, on Friday, Aug. 11, and Saturday, Aug. 12, country music star Morgan Wallen heads to the Horseshoe to play two shows. 

Roadways near Ohio Stadium will be closed, limited parking will be available and CABS delays are anticipated. From Friday, Aug. 4, through Saturday, Aug. 12, the Olentangy Trail reroute will move east to Tuttle Park Place.

Motorists should allow additional time and plan for travel delays in The Ohio State University campus area, and be aware that surface lots surrounding Ohio Stadium will be limited to event parking only.

Additionally, on Sunday, Aug. 6, summer commencement will take place at the Schottenstein Center in Columbus, and a quarter- and half-marathon will take place on some campus-area roads.

For details on the events and expected impacts, visit the university's Transportation and Traffic Management website.
 

Using the cameras already installed on campus buses at The Ohio State University, researchers demonstrated that they could automatically and accurately measure counts of vehicles on urban roadways, could detect objects in the road, and could distinguish parked vehicles from those that are moving. 

In previous studies, Ohio State researchers found that using these mobile cameras provides much better spatial and temporal coverage than relying on sparsely and often temporarily placed sensors that don’t provide a view of many streets and roads in a city. 

“If we collect and process more comprehensive high-resolution spatial information about what’s happening on the roads, then planners could better understand changes in demand, effectively improving efficiency in the broader transportation system,” said Keith Redmill, lead author of the study and a research associate professor of electrical and computer engineering at Ohio State.

Whereas researchers previously used human observers to manually identify the vehicles in the videos, this study, published in the journal Sensors, automates the process using AI.  

According to co-authors of the study Mark McCord and Rabi Mishalani, both professors of civil, environmental and geodetic engineering at Ohio State, their team chose to utilize the traffic cameras on the Campus Area Bus Service partly because Ohio State’s large, interconnected campus resembles a small city and their relationship with CABS operators gave them ready access to the collected videos. 

“Sharing access to our bus cameras for traffic monitoring is a great example of how university operations can support research and learning,” said Tom Holman, Ohio State’s director of Transportation and Traffic Management. “We are happy to share existing resources that can generate helpful data for long-term traffic planning purposes on campus and beyond.”

But what sets this study apart from similar traffic-related studies is that it utilizes available resources at no extra cost: bus cameras that have already been installed for other safety and security purposes. This allows it to be easily integrated into how other cities manage their traffic monitoring, said Mishalani. 

“If we can measure traffic in a way that is as good or better than what is conventionally done with fixed sensors, then we will have created something incredibly useful extremely cheaply,” he said. “Our goal is to start building a system that could do this without much manual intervention because if you want to collect this information over lots of potential vehicles and lots of time, it’s worth fully automating that process.” 

The system works by utilizing a state-of-the-art 2D deep learning model called YOLOv4 to automatically detect and track objects. The program is also uniquely adept at recognizing multiple objects in a single image frame, said Redmill. 

While still a long way from total implementation, the study suggests the system’s results bear promise for the future of intelligent traffic surveillance. For example, besides counting vehicles, their algorithm is also able to project real-world bird’s-eye-view coordinates of the road network by taking advantage of streams of images, GNSS measurements, and regional information from 2D maps. It’s so precise, the system was also able to detect if the bus veered off from its planned route – and then report it to a map database that logs detailed information about the roadways, said Redmill, who is also a member of Ohio State’s Control and Intelligent Transportations Research Lab (CITR).

With widespread deployment and integration of their proposed approach, the vast collection and complete automation of processing of this data over time would allow for more effective planning, designing and operation of roadways to mitigate heavy traffic across the country. As for the benefits the public might see, such advancements in traffic surveillance could mean reduced travel times and greater travel choices when trying to get from point A to point B. 

“Transportation planners, engineers and operators make vital decisions about the future of our roadways, so when designing transportation systems to work over the next 30 to 50 years, it’s imperative that we give them data that allows them to improve the efficiency of the system and the level of service provided to travelers,” said Mishalani.

The research was supported by the United States Department of Transportation’s  Mobility21 University Transportation Center program. Other co-authors are Ekim Yurtsever and Benjamin Coifman, both of Ohio State.

Called the Vehicle-in-Virtual-Environment (VVE) method, it allows the testing of driverless cars in a perfectly safe environment, said Bilin Aksun-Guvenc, co-author of the study and a professor of mechanical and aerospace engineering at Ohio State.

Imagine a driverless car is placed in the middle of an empty parking lot. Although it is driving, it isn’t reacting to the real world, but to input from the software, which tells the car what the road looks like, and what cars, pedestrians and hazards it is meeting along the way.

“With our software, we’re able to make the vehicle think that it’s driving on actual roads while actually operating on a large open, safe test area,” said Aksun-Guvenc. “This ability saves time, money, and there is no risk of fatal traffic accidents.”

The study, published recently in the journal Sensors, found that by immersing self-driving machines in a virtual environment, the technique can help the car learn to avoid possible car collisions, increase pedestrian safety, and react to rare or extreme traffic events. 

Although autonomous driving technologies have become a much more common sight on the road in the last few years, due to the sheer number of accidents these systems have caused, the way these technologies are tested deserves closer scrutiny, Aksun-Guvenc said.

“Our future depends on being able to trust any and all road vehicles with our safety, so all of our research concepts pertain to working towards that goal,” said Aksun-Guvenc, who is also co-director of Ohio State’s Automated Driving Lab, a research group originally formed in 2014 to advance  autonomous vehicle technologies.

Current approaches for demonstrating autonomous vehicle functions involve testing software and technology first in simulations and then on public roads. Yet this method essentially turns other road users into involuntary participants in these driving experiments, said Aksun-Guvenc, and such risks can make the entire development process costly, inefficient, and potentially unsafe for both drivers and pedestrians alike. 

To overcome the limitations of these faulty assessments, researchers in this study replaced the output of high-resolution sensors in a real vehicle with simulated data to connect its controls to a highly realistic 3D environment, much like giving the machine a VR headset or virtual reality glasses. After feeding the data to the autonomous driving system’s computers and syncing the car’s real motions with the simulations’, researchers were able to show that it behaves as if the virtual environment were its true surroundings in real time.  

But what makes their software especially powerful, said Levent Guvenc, co-author of the study and also co-director of the Automated Driving Lab, is the strength of how flexible their virtual environment can be. “When actual senses are replaced by virtual senses, the model can be easily changed to fit any kind of scenario,” said Guvenc.

Because the VVE method can be calibrated to maintain the properties of the real world while modeling rare events in the virtual environment, it could easily simulate extreme traffic scenarios, like someone jumping in front of a vehicle, to mundane ones like pedestrians waiting at a crosswalk, he said. 

Additionally, with the help of a communication app for vehicle-to-pedestrian connectivity, the software can use Bluetooth to communicate between a pedestrian with a mobile phone and a phone in the test vehicle. The researchers had a pedestrian actually dart quickly across a simulated road a safe distance from the test vehicle. But the Bluetooth signal told the car that the person was darting right in front of it.

“The beauty of the method is that road users can share the same environment at the same time without being in the same location at all,” said Guvenc. And although generating these super-realistic environments can take time, he said the technological challenge of syncing different environments to use in real-time simulations is one challenge their team has solved. 

The team has also filed a patent for the technology. In the future, Guvenc said he’d also like to see it be integrated into traffic guidelines made by groups such as The National Highway Traffic Safety Administration. 

“We could see this technology becoming a staple in the industry in the next five or 10 years,” said Guvenc. “That’s why we’re focusing on building more applications for it.” 

Other Ohio State co-authors were Xincheng Cao, Haochong Chen and Sukru Yaren Gelbal. 

Multiple roadways will be closed, limited parking will be available and CABS transit service will be suspended for portions of the weekend of April 15 and 16.

Additionally, work related to the Cannon Drive relocation is causing traffic and bus changes in the area. Cannon between 12th Avenue and John H. Herrick Drive; the Herrick and Cannon intersection; and the Herrick bridge are all closed.

Changes because of the major events include:

• Tuttle and Northwest parking garages will be closed after the Saturday spring game and reopen after the Sunday 4 Miler event.
• Access to parking areas within the 4 Miler event route will be limited/delayed.
• All CABS routes, including CABS On-Demand and paratransit service, will be suspended during the game and race.

Motorists are encouraged to allow for additional travel time. Be prepared for heavy vehicular and pedestrian traffic before, during and after the events. 

The noon spring game exhibition at Ohio Stadium is expected to attract at least 50,000 fans to the campus area.

Visit the Transportation and Traffic Management website for more information on the events and expected impacts.

Balaji Ponnu, with Transportation and Traffic Management at Ohio State, joins a project of the National Cooperative Highway Research Program (NCHRP) titled “Pedestrian Crosswalk Spacing and Placement Guidance to Improve Safety.”

Each year, the NCHRP focuses on a set of projects that are critical to state departments of transportation across the country. This year, one of the project’s main research objectives is to determine the maximum distance pedestrians will travel to use a crosswalk and develop various crosswalk spacing recommendations to discourage them from crossing at higher-risk locations between crosswalks.

According to the U.S. Department of Transportation, pedestrian and bicyclist fatalities are about 19% of all traffic fatalities every year. In 2019, more than 6,000 pedestrians in the United States were killed due to traffic collisions, and over 80% of those accidents occurred at unmarked midblock locations, places where a traffic signal or a stop sign is nonexistent.

Ponnu, who received a doctorate in civil engineering from Ohio State in 2018, believes he was asked to participate because he serves as the traffic engineer for a large college campus in the country and due to his work investigating choice of countermeasures and pedestrian volume patterns of college crosswalks. His previous research has also helped to develop measures to discourage jaywalking on Ohio State’s Columbus campus. Earlier this year, Ponnu presented his findings on pedestrian crossing volume patterns at the 101st annual meeting of the Transportation Research Board, which was held in Washington, D.C.

“College crosswalks are very different from public road crosswalks in that they’re very unique in terms of heavy pedestrian movements and a young student population,” he said. Uncontrolled crossing locations, or places where people often choose to jaywalk, can be dangerous, but Ponnu said that penalizing people isn’t conducive to improving traffic conditions.

“The onus to prevent pedestrians from jaywalking should not be on the pedestrian. It should be on those of us who design crosswalk systems,” he said.

Case in point: During trips around campus to study local crosswalk operations, Ponnu discovered a huge variation in traffic control for crosswalks with similar characteristics across different areas around the university. “There is no consistency in how we provide crosswalk traffic control, and that’s something we need to standardize,” he said. But this issue isn't confined to college campuses; Ponnu’s previous research has shown that there is a lack of consistency in the choice of crosswalk traffic control across the country because there is no clear national guidance.

According to the NCHRP, national crosswalk spacing guidance is ambiguous as well; most agency regulations only point to where marked crosswalks should not be installed, rather than give advice on where they should be.

But how do researchers fix such a failing on a national scale?

By turning research like Ponnu’s into well-defined objectives, the project, which has received $500,000 in funding for the 2023 fiscal year, aims to be a first step in changing the way pedestrians interact with roads. It’ll be a year or two before the panel is able to share its recommendations on how to improve our current roadway system with other federal agencies, but Ponnu said he’s looking forward to serving as a “champion” for the implementation of the project’s results at Ohio State.  

“It is an absolute honor to have been invited to serve on this panel,” he said. “Being on this project will be a significant help in assisting me to design better facilities for both students and the many other people who travel to Ohio State’s campus.”