Intelligent Transportation Systems (ITS) are widely researched to improve the traffic situation. In ITS, vehicle detection system plays a significant role. At present, is often conducted by inductive loops, which very expensive and inconvenient install maintain. Video camera another frequently used detector, but it needs high computing power. order solve these problems, this paper focuses on development of roadside magnetic sensor for detection. The device installed at side road measures in...

The high-resolution traffic data (HRTD) of all roadway users is important to connected-vehicle systems, safety analysis, performance evaluation and fuel efficiency study. roadside LiDAR (light detection ranging) sensors can provide HRTD by collecting real-time 3D point clouds surrounding objects, which significant applications with mixed flow - connected unconnected road users. background filtering a necessary step improve the accuracy extraction from raw data. At same time, lane space...

The high-resolution micro traffic data (HRMTD) of all roadway users is important for serving the connected-vehicle system in mixed situations. roadside LiDAR sensor gives a solution to providing HRMTD from real-time 3D point clouds its scanned objects. Background filtering preprocessing step obtain different data. It can significantly reduce processing time and improve vehicle/pedestrian identification accuracy. An algorithm proposed this paper, based on spatial distribution laser points,...

High-resolution vehicle data including location, speed, and direction is significant for new transportation systems, such as connected-vehicle applications, micro-level traffic performance evaluation, adaptive control. This research developed a processing procedure detection tracking of multi-lane multi-vehicle trajectories with roadside light ranging (LiDAR) sensor. Different from existing methods onboard sensing this was specifically to extract high-resolution LiDAR sensors. includes...

The problem of traffic safety has become increasingly prominent owing to the increase in number cars. Traffic accidents often occur an instant, which makes it necessary obtain data with high resolution. High-resolution micro (HRMTD) indicates that spatial resolution reaches centimeter level and temporal millisecond level. position, direction, speed, acceleration objects on road can be extracted HRMTD. In this paper, a LiDAR sensor was installed at roadside for collection. An adjacent-frame...

High-resolution micro traffic data are important to safety and efficiency analysis. In this study, a roadside LiDAR sensor is used collect 3D point clouds of surrounding objects. An automatic background construction object detection method proposed on the basis operation principle sensor. algorithm, discrete horizontal vertical angular values can be considered as coordinates pixels in digital images, farthest mean distance each azimuth construct dataset. Then, vehicle pedestrian points...

The previous studies showed that rainy and snowy weather can reduce the quality of LiDAR data. In weather, laser beams were often blocked by raindrops or snowflakes, which was called occlusion. vehicle detection with occlusion is a challenge. When traditional density-based spatial clustering applications noise (DBSCAN) used for clustering, data processing false rate conventional DBSCAN under high. This paper aims to present characteristics roadside in days improve accuracy during challenging...

Wireless signal can be easily influenced by the environment in propagation process. The model is most appropriate for current indoor to ensure ranging accuracy based on received strength indicator (RSSI). In this paper, we propose a robust localization algorithm RSSI scope which error caused using fixed parameter dramatically eliminated. Our contributions paper are twofold. First, influence of positioning well discussed detail wireless model. Second, develop creates one-to-one mapping...

The high-resolution traffic data (HRTD) is important to intelligent transportation systems (ITS). roadside LiDAR (light detection and ranging) sensors can provide HRTD by collecting real-time 3D point clouds of surrounding objects. To analyze HRTD, background filtering vehicle are the essential steps. This paper presents an algorithm extract detect vehicles based on association in clouds. improve accuracy, DBSCAN combined with time-limited window for according relationship between points.

Environmental pollution problem has been a great threat to the development of social economic and human's daily life. The Internet Things technology provides an effective method for solving environmental problem. Hence, it is very important construct real-time monitoring system in order solve In this paper, hardware built collect parameters including temperature, humidity, PM <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2.5</sub>...

As one of the most important elements in intelligent transportation system (ITS), road traffic monitoring (RTMS) needs to be functioned with a recognition mechanism. Current works on mainly target at field automatic driving and cannot directly used RTMS. In this paper, we propose decision tree-based algorithm using roadside fixed light detection ranging (LiDAR) sensors These LiDAR have low vertical resolution, which implies that get clear far boundary obvious features roads from point cloud...

Traffic information collection is an important foundation for intelligent transportation systems. In this paper, 3D Light Detection And Ranging (LiDAR) deployed in the roadside of urban environments to collect vehicle and pedestrian information. A background filtering algorithm, including a mean modeling build map difference method filter static noise points, proposed fixed LiDAR facilities. Background points are filtered through between data frames multi-level map, then there still small...

Traffic sign detection and recognition (TSDR) has attracted extensive studies recently due to its broad application prospect in Intelligent Transport Systems. TSDR is still challenging the small size of traffic signs image. Besides, real world exhibit a long-tailed distribution (i.e., data for most categories are scarce while others abundant.), which will lead significant performance drop framework. In this paper, we propose novel framework address these problems. order detect signs, an...

Along with the development of industry, number vehicles is growing very fast. Then, traffic situation will be complicated. In order to alleviate pressure and decrease congestion, study vehicle detection becomes important necessary. The traditional method, which named inductive loop costs a lot has high impact on flow. Therefore, this paper studies by using wireless sensor network. sensed magnetic sensors, signal transmitted communication way. Due deployment sensors side roads, it difficult...

To improve traffic efficiency, the intelligent transportation system (ITS) is widely used in urban roads. The sensing preferred to be deployed at roadside because normal would not interfered. In field of magnetic vehicle detection, one most challenging problems disturbance from other lane. Most existing detection systems need more than sensor solve disturbance. This paper proposes a portable based on multi-sensing fusion. Cooperated with and ultrasonic sensor, non-detected lane can excluded...

The emerging intelligent transportation systems puts higher demands on the collection and analysis of traffic data. LiDAR can provide high-precision point clouds objects, making it a promising choice for surveillance device. This article focuses object detection with roadside LiDAR: estimating both positions categories them. To overcome challenges posed by clouds, we propose GC-net, which is based three-stage pipeline, including gridding, clustering, classification. First, design one-to-one...

Swarm decomposition (SWD) is an emerging signal method and has been applied in the fault diagnosis of rotating machinery. However, performance SWD highly dependent on user-defined parameter. In this article, adaptive swarm (ASWD) guided by spectral characteristic information scanner (SCIS) proposed to automatically decompose vibration into a set subcomponents. The can not only adaptively extract weak fault-related component from contaminated strong noise but also avoid problem parameter...

In wireless sensor networks (WSNs), location information is regarded as essential to achieve intelligent monitoring and control. Recently, a large number of range-based localisation algorithms were proposed. Nearly, all the are based on least square method, in which sum ranging error treated performance index. The disadvantage ignoring probability characteristics error. This paper aims integrate characteristic improve accuracy. First, introducing factor represents credibility distance...

Location information is essential when dealing with Wireless Sensor Networks (WSNs). This paper focuses on the error analysis of range–based localisation algorithms in WSNs. The mainly derived from measurement error. As seen through prior literature, researchers often assume similar measuring noise, which not rational practice. However, attempt this process to locate characteristic noise different. By a large number simulation experiments, has obtained quantitative relationship between...

The intelligent road is an important component of the vehicle infrastructure cooperative system, latest development transportation systems. As advanced sensor, Light Detection and Ranging (LiDAR) has gradually been used to collect high-resolution micro-traffic data on roadside roads. Furthermore, a fusion multiple LiDARs become current hot spot extend collection range improve detection accuracy. This paper focuses point cloud registration in complex traffic environment proposes...

This paper addresses the effects of leaders on consistency group behaviour. First, a mathematical model is established so that attempts to reach common velocity direction. The action range formulated by their communication range. followers update states according both other in vicinity and which can communicate with current follower. After establishing system model, we then conduct simulations discover Finally, obtain following results: (a) leader very useful compelling be consistent, even...