Articles tagged with Automobile Traffic
Yu Yang's NSF-funded research aims to reduce vehicle emissions and promote the use of electric bikes and scooters by developing socially informed traffic signal control systems. The project involves a three-pronged method that uses low-cost mobile air-quality sensing, spatial-temporal graph diffusion learning, and reinforcement learnin...
A study found that wildlife exits designed for ocelots in Texas were used by 10 mammal species, including bobcats and coyotes, to exit highways. The exits function as designed, but ongoing research aims to improve their effectiveness.
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.
A novel AI system developed by City University of Hong Kong improves predictive accuracy in dense traffic, reducing latency and increasing efficiency. QCNet achieves speed and accuracy in predicting road users' movements, even with long-term predictions, making autonomous driving safer and more human-like.
A study found large increases in cannabis-involved traffic injury emergency department visits in Ontario, Canada. The research suggests that commercialization of non-medical cannabis may have accelerated these incidents, highlighting the need for greater prevention efforts.
A recent study published in JAMA Network Open found that the commercialization of cannabis in Ontario, Canada led to a significant increase in emergency department visits for cannabis-involved traffic injuries, with rates rising by 475% over 13 years.
A new method can detect drivers' attention levels from their eye movements, enabling the development of more effective takeover signals. The study found that drivers who are engrossed in on-screen activities take longer to respond to warnings, highlighting a potential safety concern.
New research from the University of Ottawa's Telfer School of Management suggests that managing public transit projects requires a comprehensive approach considering rational, psychosocial, and political dimensions. This involves engaging stakeholders, including non-users, to ensure societal impact and cost-effectiveness.
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.
A large long-term study found exposure to high levels of air pollution is associated with increased community mental health services use among people with dementia. Reducing nitrogen dioxide and particulate matter could help free up resources in overstretched psychiatric services.
A study by Ohio State University researchers uses mobile cameras installed on campus buses to count vehicles, detect objects in the road, and track movements. The AI-powered YOLOv4 model provides accurate measurements with high spatial and temporal coverage, which could enhance current traffic systems and improve efficiency.
A study by University of Houston and Texas A&M Transportation Institute found that daily driving is stressful to many people, particularly those with a predisposition to anxiety, who experience significant cardiovascular activation
Researchers found that electric rideshare fleets can significantly reduce greenhouse gas emissions, but may also increase air pollution and traffic problems. The study used real-world data from Chicago to simulate the impacts of electrification.
A new study found that older drivers who use substances are up to four times more likely to be at fault in a car crash. The research team suggests implementing risk awareness campaigns tailored for older adults and other measures such as improved road visibility, automatic safety features and licensing requirements.
A study by Carnegie Mellon University found that ridesharing platforms significantly outperformed traditional taxi systems during urban emergencies. The platforms' use of technology and elastic supply of vehicles and drivers enabled them to cope with uncertainties more effectively.
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 cheap charcoal air filter can significantly improve in-vehicle air quality, reducing nitrogen dioxide (NO2) levels by up to 90%. The study found that NO2 concentrations were on average 14.3 times lower with activated carbon filters fitted compared to pollen filters.
A study by University of Gothenburg found that conifer trees are generally better at purifying air from gaseous pollutants, while broadleaved trees excel at capturing particle-bound pollution. The researchers analyzed leaves and needles from eleven different tree species to determine which ones absorb air pollutants most effectively.
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.
Repurposing regular shelters could cut travel times for vulnerable populations by up to 70%. Researchers used storm surge modeling to analyze how quickly residents could reach special needs shelters. The study showed that repurposing one shelter reduced average travel time from 28.5 minutes to 7.4 minutes.
A research team developed a method to efficiently identify potentially dangerous intersections for child traffic accidents using a combination of empirical Bayesian estimation and geo-informatized data. The model proved effective in identifying seven or more high-risk spots, improving upon methods based solely on past accident data.
A new study in The American Journal of Medicine found that adults who neglect COVID-19 vaccination may also neglect basic road safety guidelines. Unvaccinated individuals were more likely to be involved in traffic crashes, with a 72% increased relative risk compared to those vaccinated.
A new study published in AGU Advances found that post-lockdown auto emissions rebounded in some California areas, with affluent neighborhoods experiencing less pollution drop. The researchers used mobile laboratory data and analyzed grass samples to track CO2 levels and found significant differences between regions.
A 3-year study of a 20 mph speed limit in Belfast found no significant reduction in road traffic collisions or driver speed, despite a notable decrease in traffic volume. The reduction in traffic volume was 57 vehicles per week after implementation.
The UC San Diego TREDS program aims to educate drivers and pedestrians about road safety with a new self-paced online program targeting underage drivers. The initiative seeks to reduce traffic-related injuries and deaths, particularly among teens aged 15-20 who are at higher crash rates.
Kan and his team will focus on side impact protection, roof crush resistance, and airbag systems for rear occupants. The research aims to develop limousine FE models for various categories, including stretch and van-converted limousines.
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.
A recent study by Prof. Yong-Kyun Bae found that recall letters with riskier defects and 'free of charge' notices prompt quicker corrective actions. The research highlights the need for effective, standardized communication in recall letters to improve public safety.
A new study found that ultrafine particle concentration decreased by 48% during the COVID-19 state-of-emergency period due to reduced aviation and road activity. This reduction corresponded with flight activity dropping by 74% and highway traffic volume decreasing by 51%.
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.
Research found a 5.8% increase in traffic crash injuries and a 4.1% increase in fatal crash rates after legalization. States with retail sales saw an initial jump in injury crash rate before it decreased.
A new study led by the University of Washington strengthens evidence that air pollution can harm childhood behavioral problems and IQ. Researchers found prenatal and postnatal exposure to nitrogen dioxide and small-particle air pollution were associated with poorer child behavioral functioning and cognitive performance.
A Rutgers study suggests that using automated traffic safety cameras as a tool to limit racially divisive interactions with the police can increase public support. The research found that emphasizing the technology's role in reducing racial profiling and minimizing police-driver interactions can broaden support for the cameras, particu...
Researchers developed a lidar-based system for smart cars to recognize objects more accurately than cameras. The system uses a grid map to divide the field of view into regions containing individual objects.
Researchers analyzed over 240,000 Google Street View images to find that streets with more visible sky, roadway, and signs have 48% more crashes than residential areas. The study highlights the dangers of 'open road' segments in urban areas, which drivers often perceive as highways, despite being near pedestrians and human activity.
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...
Research using a network model and air pollution data before and during COVID-19 outbreaks found that surrounding traffic conditions influenced air quality in certain cities. Pollution tended to peak in cities as they contained the virus, with some cities experiencing worse air quality than ever.
Researchers found that larger numbers in fatality messages increase additional crashes, particularly in areas with heavy traffic or complex highways. However, low-toll messaging had a reduction in crashes when displayed on less complex highways.
Traffic-related air pollution contributes to high rates of asthma prevalence in Mott Haven and Port Morris, with significant increases in congestion in mixed-use areas and at night. The study's findings highlight the need for measures to mitigate environmental health impacts of traffic congestion.
A study of 749 European cities found nearly 60 million adults subjected to unhealthy vehicle-generated noise, with compliance to WHO guidelines potentially preventing 3,600 annual deaths from ischaemic heart disease. Over 11 million adults were highly annoyed by road traffic noise, leading to increased stress and health problems.
Research from Rensselaer Polytechnic Institute found a significant drop in traffic accidents during the COVID-19 pandemic, with accidents involving males, nonwhite drivers, and individuals in the 25-64 age group showing smaller reductions.
Researchers at NYU Abu Dhabi have published a comprehensive review of 50 fundamental traffic models using an extensive data set of 2.3 billion vehicle observations from 25 cities worldwide. The study found that a non-parametric model outperformed other traffic flow models, regardless of road type and congestion level.
Researchers developed a novel scheme that reduces energy consumption while improving traffic prediction accuracy by up to 40% compared to benchmark schemes. The scheme uses software defined network and edge computing to control the operation of base stations, ensuring both sustainability and performance.
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.
Researchers at Columbia University School of Engineering and Applied Science teamed up with the Fire Department of New York to upgrade FDNY's EMS response operations. They developed an optimization system that minimizes response time, reduces overcrowding, and balances demand and supply of patient intakes at a city-wide level.
Researchers develop an algorithm to find optimal or near-optimal solutions in the space of 'infeasible solutions' to speed up search, alleviating traffic congestion and improving city living. A novel solution to a combinatorial optimization problem in bicycle sharing systems is proposed.
A recent study by Penn State and Boston University found that ride-hailing services may decrease or increase traffic congestion depending on the day of the week and regional public transportation use. The researchers analyzed data from over 10,000 vehicle detector station units across California, finding a 0.5% decrease in traffic cong...
The UTSA-Glasgow model analyzed nearly 100 American cities to understand the relationship between city design and traffic congestion. It found that high-intensity urban land use and polycentric city shapes are associated with higher levels of congestion, supporting the long-held belief that traffic congestion is tied to urbanization.
Researchers developed a robust, deep neural network model to analyze automobile traffic impacts of construction zones. The model estimates hourly traffic volumes without adjustment factors, helping transportation agencies plan for efficient work zone operations.
A Brazilian-UK study found that older individuals with both abdominal fat and muscle weakness experience a significant loss of gait speed over eight years. This decline can lead to difficulty walking and increased risk of falls, impacting independence. Researchers urge health workers to measure abdominal fat and muscle strength to pred...
Simple chemical compounds, like hydroxy acids, spontaneously link together to form structures reminiscent of modern cells when dried from solution. These structures may have helped scaffold the emergence of biological cellularity.
A new legal framework for traffic enforcement, proposed by University of Arkansas law professor Jordan Blair Woods, separates traffic laws from critical police functions. This would delegate most traffic enforcement to newly created traffic agencies, reducing racial and economic injustice in stops.
A new model developed by MIT's Andres Sevtsuk can estimate pedestrian journeys and trip distribution, providing a solution for planners and developers to better understand foot traffic in cities. The model uses network analysis and real-world data to calculate pedestrian flows, which can be applied to various urban settings.
Researchers analyzed traffic volume and motor vehicle crash injuries before, during, and after COVID-19-related state-of-emergency orders. The study found a significant decrease in accidents and injuries following the implementation of social distancing policies.
A new study proposes a modeling framework for V2V and V2I cooperative driving, which prioritizes saving fuel and reducing emissions. The automated algorithm saves energy by 7% under light traffic and 23% under heavy traffic along the corridor.
Researchers have created smart road signs that use built-in Doppler radar, video, and acoustic radar devices to monitor traffic and conditions. The signs display dynamically updated recommended speeds and alert drivers in real time to hazards ahead.
A new machine learning algorithm, TranSEC, uses traffic datasets from UBER drivers and publicly available sensor data to map street-level traffic flow over time. This creates a big picture of city traffic, allowing for near-real-time analysis and predictive modeling.
Researchers developed a computer algorithm that captures traffic network topology to identify congestion hotspots. The algorithm suggests ways around congested areas in cities.
Researchers will develop an adaptive traffic control system leveraging connected vehicles and infrastructures to optimize and manage traffic flow. The goal is to reduce corridor-level fuel consumption by 20 percent, while maintaining a highly operable and safe transportation environment.