Articles tagged with Traffic Engineering
A new AI framework developed by NYU Tandon researchers combines traffic forecasting, spatial mapping, and a locally hosted large language model to provide actionable guidance for urban planners. The system outperformed conventional statistical forecasting techniques and demonstrated improved prediction accuracy on previously unseen data.
A multidisciplinary team of researchers analyzed almost 300,000 km of Roman roads, revealing a complex network with provincial capitals acting as vital crossroads and Rome not being the dominant hub. The study also found a measurable relationship between Roman and modern roads, but with varying strengths across regions.
Researchers aim to create generative cameras that can reconstruct detailed images from sparse measurements using generative AI, reducing bandwidth, computing requirements and energy consumption.
Engineers at Texas A&M University, NASA, and Purdue University create algorithms for managing spacecraft traffic around Gateway, a lunar spaceport. The system balances fuel efficiency and operational demands to reduce the risk of collisions during space missions.
A University of Houston study found that strategic investments in smaller and midsize cities can yield more new riders per dollar than larger metropolitan areas. Smaller systems may have more room to attract new riders due to limited practical transportation options before.
A new study from Carnegie Mellon University and Oxford Saïd Business School found that the entry of ride-hailing platforms drove measurable increases in economic output and intermittent employment. Regional GDP per capita increased, and the number of seasonal, temporary, or intermittent jobs rose after Uber and Lyft entered the region.
Global road injury rates declined by 38.3% for new cases and 32.3% for deaths between 1990 and 2023, but progress was uneven across income groups. Low- and middle-income countries bear the greatest burden, with nearly six times higher mortality rates than high-income countries.
Researchers developed a deep Q-network framework to train traffic signals to protect network resilience. The method achieved significant reductions in relative area index (RAI) across various disruption scenarios, indicating improved recovery rates and reduced congestion costs.
A PolyU project has developed an intelligent portable traffic light system to address bottlenecks during roadworks on narrow streets in Hong Kong. The system uses advanced sensing technologies and adaptive algorithms to dynamically adjust signal timings, reducing traffic queues and preventing gridlock.
The MOVEO general assembly showcased advancements in smart transport connections, with a focus on EU-funded research and innovation. The project aims to unite expertise from nine European countries to improve inspection, monitoring, logistics, mobility, and inclusiveness.
SwRI's Intelligent Systems Division has achieved CMMI, ISO 9001, and CMMC certifications to demonstrate its commitment to delivering secure and reliable transportation solutions. The certifications validate SwRI's robust cybersecurity protections and quality management framework.
Researchers at King's College London developed a new algorithm that can automatically explain why some self-driving cars crash. The approach analyzes past events to identify the root cause of failures in complex and rare cases.
A research project led by University of Tennessee at Knoxville associate professor Candace Brakewood aims to evaluate the impact of congestion pricing on public transit systems. The study will focus on New York City's recent implementation, analyzing how it increased transit ridership across subway, bus, and regional rail systems.
Researchers examined how autonomous vehicles affect morning commutes and parking in business districts, finding that AVs could increase vehicle hours and miles traveled. Urban planners can adapt policies to accommodate AVs by adjusting parking fees or infrastructure, reducing total system cost by up to 28.5 percent.
A new model maps foot traffic in New York City, providing insights into pedestrian activity and hazard locations. The study reveals high densities of foot traffic outside Manhattan, with many streets having similar foot-traffic levels to Manhattan's busiest areas.
A new study by MIT researchers reveals that cities with strong airline connections are more likely to attract multinational firms, particularly in knowledge industries. The study analyzed 7.5 million firms in 800 cities and found that direct flights lead to a 20% increase in subsidiaries, compared to cities with only one-stop connections.
A new international study found that people with central vision loss can judge the motion of vehicles almost as accurately as those with normal vision. When both visual and auditory information were available, the two groups showed comparable accuracy in estimating the arrival time of approaching vehicles. The research, published in PL...
A new method analyzes nearby vehicle motion to estimate road's trajectory and vanishing point, capturing distant road areas and enhancing safety. The system outperformed conventional and deep learning-based techniques in tests under day and night conditions, reducing intersection-related accidents.
A new framework uses weather indicators to estimate how quickly a travel ban may start to lose effectiveness. The approach could inform targeted interventions before storms hit and preserve emergency measures' legitimacy while keeping people safer. It was developed after analyzing two Buffalo storms in late 2022.
Johns Hopkins researchers develop SafeTraffic Copilot, an AI-based tool that identifies risk factors contributing to car crashes across the US. The model provides data-based insights for infrastructure designers and policymakers to mitigate crashes and save lives.
A new study by Portland State University's Transportation Research and Education Center (TREC) reveals that transit-oriented developments (TODs) in the Portland metro area generate significantly fewer car trips than previously estimated. At affordable housing sites, car trips were reduced to only a quarter to two-fifths of expected rates.
Researchers at FAU have developed a smarter AI framework that can manage complex systems with unequal levels of authority and adapt to imperfect information. The framework, based on reinforcement learning and game theory, reduces unnecessary computation while maintaining system stability and optimal strategy outcomes.
A team at the University of Kansas will develop intelligent spectrum management frameworks to enable reliable communication for drones. They aim to study how to use a proposed 5030-5091 MHz frequency band efficiently, with potential benefits including quicker deliveries and improved emergency response.
A recent study published in the Journal of Safety Research found that rented e-bikes have an eight times higher crash risk than rented e-scooters, calculated based on trip distance. The researchers used GPS data to compare micromobility in seven European cities and found a surprising result.
A Safe Systems Approach emphasizes that road users, designers, operators, policymakers, administrators, and healthcare professionals all have a role to play in reducing fatalities. By adopting this approach, countries can realize significant success in eliminating roadway deaths, but full commitment from stakeholders is necessary.
A recent study from Graz University of Technology found that adding front brake lights to vehicles can prevent up to 17% of collisions at road junctions. The research used accident reconstruction and simulation to analyze the effect of the added lights on road safety.
Researchers at UCF used a combination of emerging technologies to evaluate the safety of concrete bridges. By combining infrared thermography, high-definition imaging and neural network analysis, they can quickly identify defects and prioritize repairs.
Researchers demonstrate ultrafast transparency switching across multiple wavelengths using single laser excitation in germanium, opening possibilities for advanced optical technologies. The study highlights the potential of Ge as a key material for ultrafast optical switching with promising applications in high-speed data transmission ...
University of Missouri researchers developed a method using lidar and AI to analyze pedestrian, cyclist, and vehicle interactions at traffic signals. The approach aims to enhance driver awareness, reduce accidents, and improve mobility.
The University of Texas at Arlington (UTA) has earned the prestigious R1 designation, recognizing its highest level of research activity. UTA has maintained this classification since 2015 and continues to demonstrate its commitment to innovation and academic excellence.
Researchers at Mizzou have developed a proactive approach using artificial intelligence to address evolving threats against smart grids. The CIBR-Fort system can predict cyberattacks with 91.88% accuracy and defend against them in real-time, enabling scalable security for power grids of the future.
A new study forecasts Australia's road traffic fatalities to rise to 998 by 2030 and 715 by 2050, with older drivers and male motorcyclists at the greatest risk
The researchers developed a novel camera-based system that adapts to traffic flow in real-time, ensuring efficient monitoring and resource use. The system's two approaches, the Random-Value-Camera-Level Algorithm and the ALL-Random-With-Weight Algorithm, optimize camera usage and save energy while maintaining reliable surveillance.
Researchers at Tokyo University of Science have developed a new method called black-box forgetting, which enables selective removal of unnecessary information from large pre-trained AI models. This approach enhances model efficiency and improves privacy by reducing computational resources and information leakage.
Research shows that remote drivers' reaction time is significantly slowed by distractions and disengagement, increasing response latency and impairing decision-making. This poses serious safety concerns for Level 4 automated vehicles, which rely on remote drivers to make critical decisions.
Researchers developed a multimodal dataset, TimelyTale, to gather passenger-specific sensor data for context-relevant explanations. The approach effectively identified the timing and frequency of passenger demands for explanations, enabling the creation of a machine-learning model to predict the best time for providing an explanation.
A UBC study analyzing pedestrian interactions with vehicles on busy streets found that distracted pedestrians face higher safety risks compared to undistracted road users. Distracted pedestrians remained unaware of their surroundings, making fewer adjustments to their path or speed.
Rice engineers developed an automated data fusion framework called OpenSafe Fusion to sense quickly evolving road conditions during urban flooding events. The framework leverages existing individual reporting mechanisms and public data sources, predicting whether a road is flooded or not.
A new deep learning-based inverse design method allows for the optimization of complex acoustic metamaterials, reducing noise pollution while maintaining ventilation. The approach enables ultra-broadband sound attenuation across various peak frequencies.
A recent study published in the Proceedings of the National Academy of Sciences found that Black drivers in Chicago are disproportionately more likely to be stopped by police (70% vs. under 20%) than being ticketed by speed cameras (54% vs. just under 50%). Researchers call for authorities to investigate racial biases in traffic systems.
Researchers found a 28% reduction in average maximum speeds and 21% decrease in right-turn vehicle speeds with the presence of delineated bike lanes. The study suggests bike lanes can save lives by reducing speeding and improving traffic flow.
China is revolutionizing low-altitude airspace management by integrating unmanned aerial systems (UAS), promoting efficient and safe operations. The country's advancements in UAS technology and regulatory frameworks aim to set international standards for unmanned aviation, transforming the nation's aviation industry.
Alyssa Ryan's research aims to identify populations most at risk for crash injuries, including factors like location, race, sex, ethnicity, and socioeconomic status. Her study combines layered national and state demographic data with injury and fatality data from Emergency Medical Services.
A new study reveals that retention ponds and wetlands can significantly reduce the amount of tyre particles entering aquatic environments, with an average reduction of 75%. The research found that tyre wear particles outweigh other forms of microplastics, but are also removed in greater quantities.
A study found significant decreases in average nitrogen dioxide concentrations and social inequities in California's air pollution during the COVID-19 pandemic lockdown. Non-urban areas saw a 17% decrease, while urban areas experienced a 50% reduction, primarily due to reduced traffic.
A new traffic signal concept, known as the 'white phase,' uses autonomous vehicles to expedite traffic flow at intersections. The concept has been shown to improve travel time for both pedestrians and vehicles, especially when autonomous vehicles make up a higher percentage of traffic.
A University of Michigan team recalibrated traffic signals using GPS data from connected vehicles, resulting in a 20-30% decrease in stops at intersections. The system reduces costs and cuts vehicle emissions by optimizing signal patterns for changing traffic flows.
Assistant Professor Santiago Segarra at Rice University has won the NSF CAREER Award to develop a new approach for AI-powered climate prediction by leveraging structural properties in real-world data. The research aims to create more effective learning algorithms for structured domains.
Researchers have invented a simple yet effective algorithm called SIEVE to optimize cache management. By labeling objects as 'zero' or 'one', the system efficiently evicts the least recently used items, reducing computational complexity and bugs.
The UCLA Mobility Center of Excellence will conduct research on the impacts of new mobility technologies and highly automated vehicles on transportation systems. The center aims to improve efficiency, mobility, and sustainability by studying the long-term effects of emerging mobility technologies.
The University of Missouri's Missouri Work Zone Safety Center of Excellence aims to reduce fatalities and serious injuries in highway work zones through research and outreach. The center will focus on integrating emerging technologies, data analysis, and countermeasures to address distracted driving and other safety concerns.
Researchers at North Carolina State University found that connected vehicles improve travel time through intersections, but automated vehicles without connectivity actually increase wait times. The study suggests that incorporating vehicle-to-vehicle and vehicle-to-infrastructure communication is crucial for optimizing traffic flow.
The University of Houston's CYBER-CARE research center aims to prevent cyberattacks that could compromise the safe movement of people and goods in the US. The center will focus on four goals, including exploring advanced theories to mitigate the impact of large-scale cyberattacks.
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.
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.
Researchers have created a more robust and accurate positioning system that surpasses GPS, particularly in urban settings. The new mobile network infrastructure achieved an accuracy of 10 centimeters, making it suitable for applications such as automated vehicles and quantum communication.
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.
Rice University researchers have received three NSF grants to develop tools and techniques for improving wireless communications. The projects focus on creating more efficient sensing and communication technologies, as well as protocols for resilience in the face of natural or human-induced disasters.
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.
Researchers at NC State University have developed a cooperative distributed algorithm that allows autonomous vehicle software to make calculations more quickly, enabling real-time navigation of complex merging scenarios. The approach improves both traffic flow and safety, with zero incidents in simulations.