Browse Topic: Roads and highways
Single motorcycle accidents are common in Nagano Prefecture where is mountainous areas in Japan. In a previous study, analysis of traffic accident statistics data suggested that the fatality and serious injury rates for uphill right curves and downhill left curves are high, however the true causes of these accidents remain unclear. In this study, a motorcycle simulator was used to evaluate the driving characteristics due to these road alignments. Evaluation courses based on combinations of uphill/downhill slopes and left/right curves were created, and experiments were conducted. The subjects of the study were expert riders and novice riders. The results showed that right curves are even more difficult to see near the entrance of the curve when accompanied by an uphill slope, making it easier to delay recognition and judgment of the curve. Expert riders recognized curves faster than novice riders. Additionally, expert riders take a large lean of the vehicle body, actively attempted to
Dynamic monitoring of queue lengths of vehicles waiting for toll booths on highways is critical for maximizing traffic flow and increasing traffic performance. On the other hand, traditional methods mainly utilize fixed sensors that have various issues including high cost and low flexibility. To address this problem, this paper introduces a novel model based on the YOLOv5 object detection algorithm and Kalman filter tracking algorithm to achieve real-time monitoring of vehicle queue length. First of all, the novel model utilizes YOLOv5 to accurately detect vehicles and get each vehicle’s bounding box information. Then Kalman filter algorithm is used to predict and track the motion state of the vehicle, and the position and speed of each vehicle are estimated accurately. The model calculates queue length in real-time by continuously monitoring the position and speed of each vehicle. To improve the complexity and accuracy of the model, a multi-target tracking framework is introduced to
With the continuous promotion and pilot application of the “a country with strong transportation network” project, BIM technology has been more and more widely used in expressway projects. With BIM technology as the core, based on the unified data standard, combined with the business management needs of the expressway in the early stage, construction period and operation period, build an integrated platform to explore the application of BIM technology in the whole life cycle of the expressway. Take Majing Expressway in Shaanxi Province as an example, carry out application at all stages, integrate the management information of the whole process, carry out data flow at all stages, and realize the digitalization of the whole life cycle.
This study focuses on analyzing the impact of the Francis Scott Key Bridge collapse on traffic flow and the traffic network in Baltimore City. By employing the processing of publicly available datasets, the construction of a traffic network model and a comprehensive scoring method and an improved K-means clustering algorithm based on the idea of the rotational method, the following conclusions have been drawn in this study. First, the bridge collapse significantly changed the distribution of traffic flow. According to the AADT data of 17 key traffic nodes, after the bridge collapse, the AADT of all nodes generally increased except for the nodes closest to the tunnel and bridge. For example, traffic nodes around the city center (e.g., nodes with OSMID numbers 37831627 and 602433660) experienced an increase in AADT, suggesting that traffic flows we Second, the 17 key nodes selected represent the major nodes of the Baltimore City traffic system and provide accurate data to support
To evaluate the performance evolution patterns of road structures under natural environmental conditions and loading, data were collected from the RIOHTrack system. Pavement deflection, smoothness, and skid resistance were selected as evaluation indicators. The performance evolution characteristics over 50 million load cycles were analyzed to investigate the impact of different structural configurations on service performance. The study results are summarized as follows: The deflection basin area exhibits significant annual cyclic fluctuations, indicating that ambient temperature significantly affects pavement deflection. The initial rapid decrease in texture depth was attributed to the compaction of the surface layer under traffic loading, leading to a reduction in texture depth. Differences in tire and subgrade stiffness can cause variations in texture depth across various scenarios. Circular pavement structures' smoothness can be categorized into three classes; however, even within
In the commercial and off-highway sectors, equipment reliability isn't just a maintenance target but a business imperative. Whether it's a long-haul truck on the interstate or a dozer working through dust and rock, these machines operate in some of the most demanding environments on Earth. And while engine design and fuel choice often dominate conversations about performance, the role of grease is just as critical, particularly as equipment is pushed harder and longer under more variable conditions. Over the last decade, heavy-duty grease development has undergone a quiet evolution. Performance expectations have risen sharply. So have the environmental and regulatory considerations that influence formulation decisions.
The road network is a critical component of modern urban mobility systems, with signalized traffic intersections playing a pivotal role. Traditionally, traffic light phase timings and durations at intersections are designed by transportation engineers using historical traffic data. Some modern intersections employ trigger-based mechanisms to improve traffic flow; however, these systems often lack global awareness of traffic conditions across multiple intersections within a network. With the increasing availability of traffic data and advancements in machine learning, traffic light systems can be enhanced by modeling them as agents operating in an environment. This paper proposes a Reinforcement Learning (RL) based approach for multi-agent traffic light systems within a simulation environment. The simulation is calibrated using real-world traffic data, enabling RL agents to learn effective control strategies based on realistic scenarios. A key advantage of using a calibrated simulation
Road noise caused by road excitation is a critical factor for vehicle NVH (Noise, Vibration, and Harshness) performance. However, assessing the individual contribution of components, particularly bushings, to NVH performance is generally challenging, as automobiles are composed of numerous interconnected parts. This study describes the application of Component Transfer Path Analysis (CTPA) on a full vehicle to provide insights into improving NVH performance. With the aid of Virtual Point Transformation (VPT), blocked forces are determined at the wheel hubs; afterward, a TPA is carried out. As blocked forces at the wheel hub are independent of the vehicle dynamics, these forces can be used in simulations of modified vehicle components. These results allow for the estimation of vehicle road noise. To simulate changes in vehicle components, including wheel/tire and rubber bushings, Frequency-Based Substructuring (FBS) is used to modify the vehicle setup in a simulation model. In this
Items per page:
50
1 – 50 of 1290