scholarly journals A Study on Distance Measurement Module for Driving Vehicle Velocity Estimation in Multi-Lanes Using Drones

2021 ◽  
Vol 11 (9) ◽  
pp. 3884
Author(s):  
Kwan-Hyeong Lee
Keyword(s):  
Estimation Method ◽  
Distance Measurement ◽  
Velocity Estimation ◽  
Detection Distance ◽  
Measuring Point ◽  
Measuring Device ◽  
The Road ◽  
Vehicle Velocity ◽  
On The Road ◽  
Vehicle Information

A method of estimating driving vehicle information usually uses a speed gun and a fixed speed camera. Estimating vehicle information using the speed gun has a high risk of traffic accidents by the operator and the fixed speed camera is not efficient in terms of installation cost and maintenance. The existing driving vehicle information estimation method can only measure each lane’s driving vehicle information, so it is impossible to measure multi-lanes simultaneously with a single measuring device. This study develops a distance measurement module that can acquire driving vehicle information in multi-lanes simultaneously with a single system using a drone. The distance measurement module is composed of two LiDAR sensors to detect the driving vehicle in one lane. The drone is located above the edge of the road and each LiDAR sensor emits the front/rear point of the road measuring point to detect the driving vehicle. The driving vehicle velocity is estimated by detecting the driving vehicle’s detection distance and transit time through radiation, with the drone LiDAR sensor placed at two measurement points on the road. The drone LiDAR sensor radiates two measuring points on the road and estimates the velocity based on driving vehicle’s detection distance and driving time. As an experiment, the velocity accuracy of the drone driving vehicle is compared with the speed gun measurement. The vehicle velocity RMSE for the first and second lanes using drones is 0.75 km/h and 1.3 km/h, respectively. The drone and the speed gun’s average error probabilities are 1.2% and 2.05% in the first and second lanes, respectively. The developed drone is more efficient than existing driving vehicle measurement equipment because it can acquire information on the driving vehicle in a dark environment and a person’s safety.

Analysis of Vehicle–Pedestrian Interactive Behaviors near Unsignalized Crosswalk

2021 ◽  
pp. 036119812199906
Author(s):  
Byeongjoon Noh ◽  
Dongho Ka ◽  
David Lee ◽  
Hwasoo Yeo
Keyword(s):  
South Korea ◽  
Traffic Accidents ◽  
Road Traffic ◽  
The Road ◽  
Video Footage ◽  
Premature Deaths ◽  
Vehicle Velocity ◽  
Behavioral Features ◽  
Velocity Changes ◽  
On The Road

Road traffic accidents are a leading cause of premature deaths and globally pose a severe threat to human lives. In particular, pedestrians crossing the road present a major cause of vehicle–pedestrian accidents in South Korea, but we lack dense behavioral data to understand the risk they face. This paper proposes a new analytical system for potential pedestrian risk scenes based on video footage obtained by road security cameras already deployed at unsignalized crosswalks. The system can automatically extract the behavioral features of vehicles and pedestrians, affecting the likelihood of potentially dangerous situations after detecting them in individual objects. With these features, we can analyze the movement patterns of vehicles and pedestrians at individual sites, and understand where potential traffic risk scenes occur frequently. Experiments were conducted on four selected behavioral features: vehicle velocity, pedestrian position, vehicle–pedestrian distance, and vehicle–crosswalk distance. Then, to show how they can be useful for monitoring the traffic behaviors on the road, the features are visualized and interpreted to show how they may or may not contribute to potential pedestrian risks at these crosswalks: (i) by analyzing vehicle velocity changes near the crosswalk when there are no pedestrians present; and (ii) analyzing vehicle velocities by vehicle–pedestrian distances when pedestrians are on the crosswalk. The feasibility of the proposed system is validated by applying the system to multiple unsignalized crosswalks in Osan city, South Korea.

scholarly journals Vehicle Velocity Estimation Fusion with Kinematic Integral and Empirical Correction on Multi-Timescales

Energies ◽  
2019 ◽  
Vol 12 (7) ◽  
pp. 1242
Author(s):  
Jiangyi Lv ◽  
Hongwen He ◽  
Wei Liu ◽  
Yong Chen ◽  
Fengchun Sun
Keyword(s):  
Autonomous Vehicles ◽  
Estimation Error ◽  
Longitudinal Velocity ◽  
Estimation Method ◽  
Velocity Estimation ◽  
Model Parameters ◽  
Lateral Velocity ◽  
Empirical Correction ◽  
Vehicle Velocity ◽  
Wide Range

Accurate and reliable vehicle velocity estimation is greatly motivated by the increasing demands of high-precision motion control for autonomous vehicles and the decreasing cost of the required multi-axis IMU sensors. A practical estimation method for the longitudinal and lateral velocities of electric vehicles is proposed. Two reliable driving empirical judgements about the velocities are extracted from the signals of the ordinary onboard vehicle sensors, which correct the integral errors of the corresponding kinematic equations on a long timescale. Meanwhile, the additive biases of the measured accelerations are estimated recursively by comparing the integral of the measured accelerations with the difference of the estimated velocities between the adjacent strong empirical correction instants, which further compensates the kinematic integral error on short timescale. The algorithm is verified by both the CarSim-Simulink co-simulation and the controller-in-the-loop test under the CarMaker-RoadBox environment. The results show that the velocities can be accurately and reliably estimated under a wide range of driving conditions without prior knowledge of the tire-model and other unavailable signals or frequently changeable model parameters. The relative estimation error of the longitudinal velocity and the absolute estimation error of the lateral velocity are kept within 2% and 0.5 km/h, respectively.

scholarly journals Raspberry Pi-Based Low-Cost Connected Device for Assessing Road Surface Friction

Electronics ◽  
2019 ◽  
Vol 8 (3) ◽  
pp. 341 ◽  
Author(s):  
Miha Ambrož ◽  
Uroš Hudomalj ◽  
Alexander Marinšek ◽  
Roman Kamnik
Keyword(s):  
Traffic Safety ◽  
Road Network ◽  
Low Cost ◽  
Measurement Data ◽  
Automatic Measurement ◽  
Raspberry Pi ◽  
Measuring Device ◽  
The Road ◽  
Measuring Devices ◽  
On The Road

Measuring friction between the tyres of a vehicle and the road, often and on as many locations on the road network as possible, can be a valuable tool for ensuring traffic safety. Rather than by using specialised equipment for sequential measurements, this can be achieved by using several low-cost measuring devices on vehicles that travel on the road network as part of their daily assignments. The presented work proves the hypothesis that a low cost measuring device can be built and can provide measurement results comparable to those obtained from expensive specialised measuring devices. As a proof of concept, two copies of a prototype device, based on the Raspberry Pi single-board computer, have been developed, built and tested. They use accelerometers to measure vehicle braking deceleration and include a global positioning receiver for obtaining the geolocation of each test. They run custom-developed data acquisition software on the Linux operating system and provide automatic measurement data transfer to a server. The operation is controlled by an intuitive user interface consisting of two illuminated physical pushbuttons. The results show that for braking tests and friction coefficient measurements the developed prototypes compare favourably to a widely used professional vehicle performance computer.

scholarly journals An Intersection Importance Estimation Method Based on the Road Network Topology

2018 ◽  
Vol 12 (1) ◽  
pp. 239-249
Author(s):  
Ting Lu ◽  
Dan Zhao ◽  
Yanhong Yin
Keyword(s):  
Network Topology ◽  
Road Network ◽  
Estimation Method ◽  
Graph Connectivity ◽  
Estimation Model ◽  
Continuous Increase ◽  
Sorting Method ◽  
The Road ◽  
Path Distance ◽  
On The Road

Introduction: The expansion of road network and continuous increase of vehicle ownership challenge the performance of routine traffic control. It is necessary to make a balanced adjustment and control from the perspective of the road network to disperse the traffic flow on the entire road network. Methods: This paper develops a method to quantify the intersections’ importance at a global level based on the road network topology, which is the location of the intersection in the road network and the structural characteristics of the intersection decided by the traffic movement. The priority order in traffic signal coordination is the sorting results of intersection’s importance. The proposed method consists of two consecutive algorithms. Firstly, the graph connectivity of network is defined based on the shortest path distance and spatial connectivity between adjacent intersections. Secondly, The Importance Estimation Model (IEM) is built, which is the function of the importance indexes of current intersection and its neighboring intersections. A simulated case of a six by eight grid network was employed to evaluate the effectiveness of the proposed method in TRANSYT. Results and Conclusion: The results show that the Importance Estimation Model (IEM) minimized the measure of effectiveness compared with the schemes obtained by the volume sorting method, the saturation degree sorting method, and the method SMOO. It also created a higher frequency of small queues than the other methods.

EASYBUS-Bus Monitoring and Searching System

2014 ◽  
Vol 568-570 ◽  
pp. 1621-1624
Author(s):  
Shuai Ma ◽  
Xin Gao ◽  
Bing Rui Dong ◽  
Qing Qing Wang ◽  
Hai Yang Sun
Keyword(s):  
Waiting Time ◽  
Radio Frequency Identification ◽  
Dynamic Information ◽  
The Road ◽  
Bus Stop ◽  
Online Maps ◽  
Frequency Identification ◽  
On The Road ◽  
Vehicle Information ◽  
Exchange Data

With the development of the Internet, people come to use it frequently to search bus lines, such as Google maps, Baidu maps, etc. But these online maps have the information only about bus lines, stops, but the information how long bus will arrive. The paper designs a bus monitoring and searching system to forecast bus waiting time. The system sets up Radio Frequency Identification Technology (RFID) equipment at every bus stop to identify the dynamic information and exchange data with buses on the road; Rely on Global Positioning System (GPS) technology, we obtain the real-time location of the target vehicle information, and through the geographic information system (GIS), the system show the condition of the vehicle and the road network in the electronic map which helps bus companies to monitor easily. Using the Android software, designed for users, users can check waiting time any time any where. The waiting time error in the system is less than two minutes.

Road Vehicle Information Collection System Based on Distributed Fiber Optics Sensor

2014 ◽  
Vol 1030-1032 ◽  
pp. 2105-2109 ◽  
Author(s):  
Li Li Feng ◽  
Yun Tao Wang ◽  
Chi Ruan ◽  
Sheng Tao
Keyword(s):  
Optical Fiber ◽  
Fiber Optics ◽  
High Performance ◽  
Road Surface ◽  
Information Collection ◽  
Collection System ◽  
Road Vehicle ◽  
The Road ◽  
On The Road ◽  
Vehicle Information

A novel distributed fiber optics sensor used for road vehicle information collection system was proposed. Optical fiber was fixed on the road surface to be used as the sensing media. The vehicle information such as speed, vehicle type, vehicle weight and traffic flow can be obtained. To increase the sensitivity of such sensor, an optical Fabry-Perot (F-P) fiber interference was used. Sensing optical fiber was designed to be with a metal coating for fiber protection and high performance. Experiment results show that such distributed fiber optics sensor may be with a high performance in transportation area without digging when it is installed on the road surface.

scholarly journals An improved estimation method for vehicle velocity of distributed drive electric vehicle

2021 ◽  
Author(s):  
Qingqing Xiang ◽  
Zhiqiang Liu ◽  
Guang Liu
Keyword(s):  
Electric Vehicles ◽  
Unscented Kalman Filter ◽  
Estimation Method ◽  
Estimation Algorithm ◽  
Velocity Estimation ◽  
Estimation Model ◽  
Time Performance ◽  
Vehicle Velocity ◽  
Distributed Drive Electric Vehicle ◽  
Tracking Filter

Abstract In this paper, Simulink and Carsim are combined to study the velocity estimation of distributed drive electric vehicles. Firstly, the minimum co-simulation system is established to complete the design and debugging of the algorithm. Then, a new algorithm combining unscented Kalman filter and strong tracking filter is proposed based on the vehicle estimation model. The accuracy and real-time performance of the velocity estimation algorithm are validated by simulation under snake-shaped driving conditions with different road adhesion coefficients. Finally, an experimental test is carried out to verify the effectiveness of the proposed algorithm in estimating vehicle velocity.

Friction of Rubber Wheels on Wet Asphalt Surfaces

2008 ◽  
Author(s):  
Noamen Bouzid ◽  
Bodo Heimann
Keyword(s):  
Water Film ◽  
Experimental Investigations ◽  
Test Surface ◽  
Automotive Safety ◽  
Friction Process ◽  
The Road ◽  
High Speeds ◽  
Vehicle Velocity ◽  
On The Road ◽  
Velocity Water

A reliable online prognosis of the grip between tire and road is a feature with a big potential for further improvements of the automotive safety. Existing grip potential prognosis systems for wet conditions are able only to describe the hydrodynamic decrease of friction at high speeds which depends on vehicle velocity, water film thickness and drainage properties both of the road surface and the tire. The present work deals with the friction at low speeds which depends on the road micro roughness. The experimental investigations are done in laboratory using a small solid rubber wheel and several asphalt samples. All parameters possibly influencing the friction process are varied. The influence of the test surface is found to be related to the micro texture and to be independent of any other parameters.

scholarly journals Vehicle Velocity Relation to Slipping Trajectory Change: An Option for Traffic Accident Reconstruction

2018 ◽  
Vol 30 (4) ◽  
pp. 395-406 ◽  
Author(s):  
Vidas Žuraulis ◽  
Edgar Sokolovskij
Keyword(s):  
Initial Velocity ◽  
Traffic Accident ◽  
Experimental Tests ◽  
Accident Reconstruction ◽  
Slip Mode ◽  
The Road ◽  
Vehicle Velocity ◽  
Computer Aided ◽  
Velocity Relation ◽  
On The Road

In this paper, the relation of the velocity of a vehicle in the slip mode to the parameters of the tire marks on the road surface is examined. During traffic accident reconstructions, the initial velocity of a sideslipping vehicle is established according to the tire mark trajectory radius, and calculations highly depend on the directly measured parameters of the tire marks, in particular cases known as yaw marks. In this work, a developed and experimentally validated 14-degree-of-freedom mathematical model of a vehicle is used for an investigation of the relation between velocity and trajectories. The dependence of initial vehicle velocity on tire yaw mark length and trajectory radius was found as a characteristic relation. Hence, after approximation of the permanent slipping part by a polynomial, the parameters of the latter were related to vehicle velocity. The dependences were established by specific experimental tests and computer-aided simulation of the developed model.

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