Researchers at University of Nebraska-Lincoln are working on safeguarding US military base entry points against EV threats, focusing on high-speed ramming and zero-to-60 acceleration. The team will employ digital simulations and physical crash tests to refine barriers designed to withstand such impacts.
Researchers developed a new anode material that increases lithium-ion battery storage capacity by 1.5 times, allowing for fast charging in as little as six minutes. The innovation uses electron spin to enhance storage capacity and ferromagnetic properties.
The new model maximizes coverage area and minimizes response time, accounting for hot spots. It outperformed existing techniques in computational testing, improving response times regardless of traffic size.
Researchers have developed a novel photoelectrochemical ultraviolet photodetector that can detect two types of ultraviolet light using a multilayered nanostructure. The detector's performance can be regulated through light intensity and external bias, enabling easy adaptation to environmental changes.
The new manufacturing process produces lightweight aluminum vehicle parts that lower costs and are more environmentally friendly. Researchers have shown that the Shear Assisted Processing and Extrusion (ShAPE) process can break up metal impurities in scrap without requiring an energy-intensive heat treatment step.
A research group from Tohoku University successfully develops a dealloying bonding technology that forms a strong mechanical bond between iron and magnesium. This breakthrough enables the creation of new lightweight materials with reduced environmental impact, potentially transforming the transportation industry.
Researchers at Cranfield University are developing a new generation of lithium-sulfur batteries that offer improved performance and reduced weight compared to traditional lithium-ion batteries. The technology has the potential to support electrification of short-haul aircraft, light goods vehicles, and passenger vehicles.
University of Arizona engineers create a communication network allowing robots to explore subsurface environments independently, deploying miniaturized sensors as they traverse caves. The 'breadcrumb-style' system enables swarms of individual robots to navigate convoluted environments without losing contact.
Researchers at Chalmers University of Technology have developed a propeller design optimisation method that paves the way for quiet, efficient electric aviation. The new design can reduce noise emissions by up to 5-8 dBA, comparable to going from a normal conversation voice to a quiet room.
A new LiDAR system pinpoints pedestrian behavior to improve safety and efficiency at intersections. The system tracks pedestrians' true intent to cross, reducing conflicts between pedestrians and vehicles.
A new machine learning model can predict city traffic activity in different zones of cities, enabling targeted responses from policymakers. Understanding people's mobility patterns is crucial for improving urban traffic flow, and the model provides insights into urban interactions.
Researchers at HKU Engineering have developed a new type of continuous Marangoni transport system that generates highly ordered Fermat's spiral patterns. The system utilizes an aqueous two-phase system, inspiring potential biological applications and novel methods for fibre fabrication.
A new approach, called the white phase concept, uses autonomous vehicles to control traffic flow at intersections, reducing fuel consumption and travel time. The system informs human drivers through a clearly identifiable signal, improving safety and efficiency.
A new method has been developed to calibrate the activity-based travel demand model, taking into account bounded rationality and interdependencies between activities. The study uses a simultaneous perturbation stochastic approximation method to solve the calibration problem.
Researchers have identified the need for standardization of performance indices and a single frame for normalization methods to address concerns with bioelectrochemical systems. The study proposes strategies for up-scaling BES technologies, enabling resource recovery through on-site treatment of wastewater at an efficiency comparable t...
Researchers at Incheon National University have developed an IoT-enabled, real-time object detection system for autonomous vehicles. The YOLOv3-based model achieved high accuracy (>96%) in detecting 2D and 3D objects, outperforming other state-of-the-art detection models.
Researchers develop an algorithm to automate feature extraction from HD maps and point cloud data. The model achieved high precision in detecting road signs and traffic lights, with zero false detections.
University of Missouri engineers are working on a collaborative human-robot order picking system to speed up the online delivery process. The proposed model aims to optimize key decisions in warehouse operations, allowing robots to navigate efficiently and collaborate with humans to increase efficiency.
Researchers from NC State University have developed a dynamic computational tool to help improve user access to electric vehicle (EV) charging stations. The technique accounts for factors such as charging time, cost, and wait times to provide users with the most convenient options.
The study introduces a new day-to-day traffic assignment model that incorporates bounded rationality, suggesting users consider topological similarity when making travel choices. This leads to the concept of Boundedly Rational User Equilibrium (BRUE), where routes with low cost variations are used.
A team of researchers has created an online dashboard to track equity requirements in 239 shared micromobility programs across the US. The dashboard provides city officials with valuable insights on best practices for expanding access to these programs, including technology access, reduced fare options, and adaptive vehicles.
The Active Transportation Return on Investment Study found positive effects on business activity in retail and food sectors, benefiting areas outside of downtown Portland. The research team evaluated 12 projects constructed between 2001 and 2016 and recommended investments for Metro's Regional Flexible Funding Allocations.
The study found substantial variability in total cost of ownership (TCO) across different car segments and user profiles. TCOs are lower for battery electric vehicles (BEVs) without subsidies, making them more attractive to consumers and policymakers.
A study analyzing over 3 million EV-related Reddit posts reveals a wide spectrum of viewpoints on electric vehicles. The research found high similarities between political and fringe communities, indicating controversial opinions on environmental impacts.
A new optimization tool can quickly improve performance of various autonomous systems, including walking robots and self-driving vehicles. The tool uses automatic differentiation to identify tweaks that achieve desired outcomes, reducing trial-and-error simulations.
Researchers at Portland State University created a two-stage stochastic programming model to optimize e-scooter placement, charging, and rebalancing in Tucson. The model uses data from the City of Tucson to answer questions on demand uncertainty, idle periods, and customer satisfaction.
Researchers developed a computational model to determine optimal places for electric vehicle charging facilities and powerful stations without straining the local power grid. The model considers travel flow, user demand, and regional power infrastructure needs.
Researchers at Chalmers University of Technology have developed a method to make shipping industry significantly greener by using hydrofoils to reduce water resistance. The new technology can increase the range of electric vessels and reduce fuel consumption by up to 80%.
Researchers at MIT City Science explore the impact of autonomy on shared micro-mobility systems, proposing it as a solution to mitigate challenges such as rebalancing and vehicle oversupply. An agent-based simulation tool assesses fleet performance and user experience, providing insights for informed decisions.
A new white paper from Portland State University explores how purchase incentive programs can expand the current e-bike market, identifying effective program structures and administration methods. The study examines impacts and statistics from around 75 e-bike incentive programs in North America.
Researchers at Tokyo University of Science propose two new search strategies to reduce the computational cost of rebalancing in bicycle-sharing systems. The approaches focus on finding feasible solutions more efficiently and redefine the problem to minimize solving time.
A new method reduces computational complexity of traffic models, making them operate more efficiently. The modified algorithm breaks down complex forecasting questions into smaller problems that can be solved in parallel, significantly reducing run time. This approach also allows for a good enough solution within an error bar, rather t...
A simulator is built to test eight widely used matching functions under various market scenarios, with the best-fit models summarized. The study aims to address the applicability and performance of these functions in different ride-sourcing markets.
The University of the Basque Country is taking steps to cut its environmental and social footprint by analyzing its impact through life-cycle assessment and modeling. By identifying areas for improvement, such as reducing transportation emissions and extending computer lifespan, the university aims to reduce its impact by up to 30%.
A new study from the University of Utah examines the impacts of decentralizing homeless service locations in Salt Lake County, Utah. The research found that people using the relocated resource centers tended to travel less, with visits to community services declining by as much as 40%.
Researchers from Tokyo University of Science analyzed usage patterns of bicycles in four major US cities to improve bicycle sharing system efficiency. They found temporal patterns and similarities between weekdays and weekends, contradicting previous studies.
The new NCHRP Guide updates pedestrian analysis methodologies to support safe and sustainable communities. The research team developed new products published in 2022, free to download from the National Academies Press.
Communications in Transportation Research enforces Data and Code Disclosure and Sharing Policy to ensure replicability and research resource sharing. Authors must provide necessary materials for reproducing published works, contributing to the community's rigor and transparency.
MIT engineers mapped airplane contrails over the US in 2020 and found a 20% drop in coverage compared to prepandemic years. The team's computer-vision technique can help predict where contrails form, allowing airlines to reroute planes and reduce aviation's climate impact.
Researchers analyzed user survey data and on-the-ground observations to understand e-scooter use and safety. The study found that older riders were less likely to experience crashes, while helmet use was lower in observed data compared to surveyed users.
Researchers from Shibaura Institute of Technology analyzed 18 Tokyo Metropolitan Area railway lines to understand the impact of in-vehicle congestion on efficiency. They found that incorporating congestion rates into efficiency analysis can help develop better public transit strategies, leading to higher service levels and sustainability.
A study by Texas A&M researchers found that navigation systems frequently guide drivers to take paths with a greater risk of crashes, despite reducing travel time. The study analyzed road and traffic characteristics in five metropolitan areas and proposed a new system architecture for finding the safest route using navigation systems.
This article reviews bi-level optimization models applied to ship air emission management, highlighting the challenges of implementing regulations and policies. The study finds that the maritime industry's reaction to policies can have negative effects on emission reduction.
Researchers from UOC-led OptimalSharing@SmartCities project will analyze inhabitants' mobility patterns and demands to design more efficient shared transport practices. The project aims to develop agile optimization algorithms capable of processing large volumes of data in real-time for dynamic system coordination.
A new online tool tracks e-bike purchase incentive programs in the US and Canada, providing a point of reference for future policy development. The tracker reveals that most programs set incentive levels fairly arbitrarily, with little thought given to their potential impact on specific groups or income brackets.
Researchers have developed a high-resolution radar sensor that can reliably distinguish between cars and pedestrians, providing counts, speed, and direction of each moving target. The sensor outperforms cameras in low-visibility conditions and beats conventional radar by providing a richer picture.
A study by Penn State University and Virginia Tech Transportation Institute found that electric vehicle sounds can improve pedestrian safety, but with some cases of false negatives at close ranges. Adding sound to electric vehicles increases detection distances beyond minimum safe detection ranges.
A new fluid has been created that can be molded and patterned using light, with potential applications in adaptive optics, mass transport, and microfluidics manufacturing. The fluid's surface tension is dependent on temperature, making it susceptible to laser manipulation.
Researchers identified 33 studies that integrated smart device technology, including Bluetooth low-energy beacons and LIDAR scanning. However, limited information was found on participant's visual acuities or etiologies, limiting the usability of the findings for this heterogeneous population.
Researchers from Tokyo University of Science developed a computationally quick approach to predict molten droplet solidification on a solid surface. The model simulates the solidification process by considering the droplet behavior and heat transfer between the hotter droplet and cooler surface, replicating experiments with high accuracy.
Developed a highly efficient boiling immersion cooler using lotus metals, increasing critical heat flux from 200 W/cm² to 530 W/cm² or more. The technology is expected to solve the heat concentration problem of in-vehicle power semiconductors and be applied to CPUs for workstations and large-scale servers.
Engineering researchers at Ohio State University developed a method to use Starlink satellite signals to accurately locate positions on Earth, similar to GPS. The accuracy of this technique is comparable to or even surpasses that of GPS, with the potential to be used as an alternative navigation system.
Researchers have discovered a new material that can produce beautiful optical phenomena, including concentric rainbows. The technology has potential applications in aiding autonomous vehicles in recognizing traffic signs, particularly in real-world conditions.
Scientists from KIT have investigated the behavior of iridium oxide catalysts under dynamic conditions using X-ray absorption spectroscopy. The study reveals highly unexpected structural modifications connected to a stabilization of the catalyst at high voltages, contributing to more efficient and sustainable green hydrogen production.
A North Carolina State University panel of experts assesses AV deployment risks and benefits, predicting substantial benefits if well-regulated. The study's findings suggest regulations could limit urban use of AVs and commercial fleet ownership, reducing risk and increasing benefits.
Researchers at Portland State University developed data-driven speed management strategies to improve safety and efficiency in multimodal transportation. They found that disabling speed feedback signs on conventional roadways resulted in reduced driver speeds and a lower likelihood of severe crashes.
The Research Roadmap addresses important active transportation needs, focusing on speed management strategies, pedestrian and bicyclist safety, and addressing racial and economic disparities. Funded by NCHRP, the project provides guidance for future research directions.
Shiloh Deitz's dissertation project focuses on filling the data gap for accessible pedestrian routing and tools, particularly for persons with limited mobility. The research evaluates AI methods and critical geoAI to improve data quality and enhance independent travel options.
Scientists have discovered that current methods for calculating stress received by underground pipelines during an earthquake are inaccurate, leading to a significant risk assessment. The new theory of seismic wave propagation addresses this issue, highlighting the need for modernization and replacement of existing pipelines.
A research team led by George Mason University's Jiayang Sun is examining the impact of patient transfers between hospitals on health outcomes. The study aims to inform training and education programs for future scientists, with funding from the National Institutes of Health.