3/3/2025 McCall Macomber
Written by McCall Macomber
Infrastructure is key to effectively rolling out next-generation transportation technologies that could increase roadway safety as well as improve freight efficiency.
Two Illinois Center for Transportation researchers are designing roadway infrastructure to meet future needs in projects sponsored by the Center for Connected and Automated Transportation.
Building Smart Roads: Vehicle-to-Infrastructure Communication
Jeff Roesler, University of Illinois Ernest Barenberg Professor in CEE and ICT rigid pavements lead, is working to improve communication between infrastructure and vehicles with advanced driver-assistance systems — particularly in work zones.
In 2023, there were approximately 1,000 fatalities in U.S. construction work zones, according to the U.S. Bureau of Labor Statistics, many of which were due to inadequate communication or driver errors such as speeding, distractions or unsafe lane changes.
Roesler’s CCAT project studies a way to better detect and warn drivers of ADAS vehicles about upcoming work zones and provide sufficient in-vehicle directives such as slow down or a merge or exit maneuver.
His method uses invisible electromagnetic markings in or on pavement to communicate passively to vehicles through on-board magnetometer sensors. The magnetometers, sensors that detect changes in the local magnetic field, then convey audiovisual warnings to drivers inside the vehicle.
The passive markings, which require no external power source, may be embedded in the pavement or coated on the road surface “like an invisible lane marking,” according to Roesler.
Roesler and Illinois doctoral student Apidej Sakulneya measured the spacing and orientation of the “invisible” electromagnetic lane markings with the strength of the produced magnetic field in the lab.
They can use the information to provide lane-keeping assistance as well as communicate in-vehicle warnings related to speed and upcoming lane-merge maneuvers.
They pilot tested the markings in a parking lot using three-axis magnetometers (vertical, lateral and forward-backward) mounted on a cart to study sensor signals from various offsets and orientation angles or markings.
Using three-axis magnetometers reliably captured the markings’ magnetic signatures, reducing the risk of inaccurate signal interpretation and, ultimately, vehicle maneuvers, which may occur with single-axis sensors.
Roesler, in an ongoing CCAT project with CEE professor Alireza Talebpour, is currently integrating the sensor suite into a vehicle to validate it on roadway trials under various environmental and roadway geometric conditions.
Autonomous Truck Platoons: Predicting Pavement Damage
As connected and autonomous technology advances, truck platoons are closer to becoming reality. Truck platoons, or groups of trucks closely following each other, reduce aerodynamic drag, bringing fuel savings and lowering emissions.
Imad Al-Qadi, Grainger Distinguished Chair in Engineering and ICT director, is using modeling to predict pavement damage from truck platoons in his CCAT project.
“Trucks usually drive behind each other 200 to 250 feet apart, and platoons will allow trucks to drive approximately 50 feet apart,” Al-Qadi said. “That may impose damage to the pavement, because the trucks are driving at the same spot, with relatively short distances between trucks, and without any wandering.”
To enhance the benefits of truck platoons, it is critical to accurately predict damage from a platoon as well as to optimize the location of a platoon’s trucks with respect to the road, a task Al-Qadi studied in a previous CCAT project.
Al-Qadi, joined by Aravind Ramakrishnan, Fangyu Liu and Angeli Jayme, used finite-element analysis to simulate real-world behavior of truck platoons on pavement.
The analysis method breaks objects into smaller elements and predicts how each element will behave, allowing researchers to predict how the overall object will behave.
Key to the analysis is the team’s simulation of tandem axles — which is the first time researchers have simulated tandem axles to predict pavement damage.
They developed a model that predicts damage from axles that was validated utilizing experimental work completed at Arizona State University, a former partner in the study.
“Platoons are coming very soon,” Al-Qadi said. “Our role was to turn this challenge from platoons into an opportunity by having the proper planning to enhance the roadway service life, while reducing the energy used by trucks.”
“We feel that agencies and the trucking industry will benefit from this research as optimized platoons could reduce damage to flexible pavements,” he said. “In addition, strategically, we’ll be able to plan the appropriate rehabilitation as well as the appropriate design for the pavement.”