On-Board Road Condition Monitoring System Using Slip-Based Tire-Road Friction Estimation and Wheel Speed Signal Analysis

2006 ◽  
Author(s):  
Kang Li ◽  
James A. Misener ◽  
Karl Hedrick
Keyword(s):  
Monitoring System ◽  
Condition Monitoring ◽  
Wheel Speed ◽  
Road Surface ◽  
Experimental Results ◽  
Probe Vehicle ◽  
Road Surfaces ◽  
Road Condition ◽  
Road Condition Monitoring ◽  
Condition Monitoring System

This paper presents an on-board road condition monitoring system developed for the safety application in Vehicle Infrastructure Integration (VII) project. The system equipped on the so-called probe vehicle is able to continuously evaluate road surface in terms of slipperiness and coarseness. Road surface is classified into four grades using stock mobile sensors and GPS speed-based measurements. The task of distinguishing slippery extents of road surfaces was treated as a "pattern-recognition" problem based on experimental results such that road surfaces can be classified into three slip levels, normal (μmax ≥0.5), slippery (0.3≥μmax <0.5), and very slippery (μmax <0.3) provided enough excitation. To distinguish rough road surfaces like gravel roads from normal asphalt roads, a separate classifier making use of a filterbank for analyzing wheel speed signal was implemented. Experimental results demonstrate the feasibility of this road condition monitoring system for detecting slippery and rough road surfaces in close to real-time. Once a slippery road condition is detected by the probe vehicle, a warning message with accurate GPS position can be transmitted from the probe vehicle to road side equipment (RSE) and further be relayed to following vehicles as well as traffic management center (TMC) via Dedicated Short Range Communication (DSRC); hence the safety of road users can be improved with the aid of this cooperative or VII active safety system.

scholarly journals An IMU-based traffic and road condition monitoring system

HardwareX ◽  
2018 ◽  
Vol 4 ◽  
pp. e00045 ◽  
Author(s):  
Tian Lei ◽  
Abduallah A. Mohamed ◽  
Christian Claudel
Keyword(s):  
Monitoring System ◽  
Condition Monitoring ◽  
Road Condition ◽  
Road Condition Monitoring ◽  
Condition Monitoring System

scholarly journals Development of Platooning Technology with Road Condition Monitoring

2021 ◽  
Vol 9 (10) ◽  
pp. 515-518
Author(s):  
Srinivaas A
Keyword(s):  
Time Delay ◽  
Monitoring System ◽  
Condition Monitoring ◽  
Sensor Data ◽  
Automated Driving ◽  
The Road ◽  
Road Condition ◽  
Road Condition Monitoring ◽  
Condition Monitoring System ◽  
Lead Vehicle

Abstract: In this paper, we present a complete platooning system using a time-delay algorithm. The platooning is achieved by measuring the driver inputs from the lead vehicle and sending these inputs to the trail vehicle with a time-delay so that the trail vehicle can exactly mimic the motion of the lead vehicle. This system also does a road condition monitor as an add-on benefit which will help in assisting the driver of the trail vehicle/vehicle which takes the same path. The function of this monitoring system is to analyse the road surface using a lead vehicle and acquire sensor data, this acquired sensor data helps in assisting drivers who take the same track. The combination of both this platooning method and road condition monitoring system could potentially reduce the current risk of utilising this semi-automated driving system. Index terms: Platooning, Semi-automated driving, Road condition monitoring, Time-delay algorithm.

scholarly journals The development of integrated road condition monitoring system for developing countries using smartphone sensors and dashcam in vehicles

2021 ◽  
Author(s):  
Hidekazu Fukai ◽  
Frederico Soares Cabral ◽  
Fernao A. L. Nobre Mouzinho ◽  
Vosco Pereira ◽  
Satoshi Tamura
Keyword(s):  
Developing Countries ◽  
Monitoring System ◽  
Condition Monitoring ◽  
Low Cost ◽  
Small Body ◽  
Public Works ◽  
Size Estimation ◽  
Road Condition ◽  
Road Condition Monitoring ◽  
Condition Monitoring System

In developing countries like Timor-Leste, regular road condition monitoring is a significant subject not only for maintaining road quality but also for a national plan of road network construction. The sophisticated equipment for road surface inspection is so expensive that it is difficult to introduce them in developing countries, and the monitoring is usually achieved by manual operation. On the other hand, the utilization of ICT devices such as smartphones has gained much attention in recent years, especially in developing countries because the penetration rate of the smartphone is remarkably increasing even in developing countries. The smartphones equip various high precision sensors, i.e., accelerometers, gyroscopes, GPS, and so on, in the small body in low price. In this project, we are developing an integrated road condition monitoring system that consists of smartphones, dashcams, and a server. There are similar trials in advanced countries but not so many in developing countries. This system assumes to be used in developing countries. The system is very low cost and does not require trained specialists in the field side. The items that are automatically inspected in this system were carefully selected with the local ministry of public works and include paved and unpaved classification, road roughness, road width, detection and size estimation of potholes, bumps, etc., at present. All the inspected items are visualized in Google Maps, Open Street Map, or QGIS with GPS information. The survey results are collected on a server and updated to more accurate values by the repeated surveys. On the analysis, we use several state-of-the-art machine learning and deep learning techniques. In this paper, we summarize related works and introduce this project’s target and framework, which especially focused on the developing countries, and achievements of each of our tasks.

scholarly journals Development of automatic road width and pothole size estimation method from dashcam video for under developing countries

2021 ◽  
Author(s):  
Hidekazu Fukai ◽  
Fernão A. L. Nobre Mouzinho ◽  
Ryo Nagae ◽  
Masayuki Uchida
Keyword(s):  
Developing Countries ◽  
Monitoring System ◽  
Condition Monitoring ◽  
Vanishing Point ◽  
Size Estimation ◽  
The Road ◽  
Road Condition ◽  
Road Condition Monitoring ◽  
Road Width ◽  
Condition Monitoring System

Road condition monitoring usually requires extremely expensive special vehicles, equipment, or many human resources. On the other hand, with the development of ICT and data science technologies in recent years, there are several research trials in which the heavy technical tasks of road asset condition monitoring are replaced by automatic inspection systems consisting of common devices such as smartphones and dashcam videos. As the system consists of low-price devices, it also suitable for developing countries. However, there are many differences in the situation and the inspection items on road condition monitoring between advanced countries and developing countries. There are few trials to develop such a road condition monitoring system in developing countries. Our project is developing an integrated road condition monitoring system focusing on developing countries like Timor-Leste. In developing countries, many parts of the road are still unpaved, and the “road width” is an important item to be inspected. In this paper, we discuss the road width and pothole size estimation as a part of the integrated system we are developing. We survey the road width of both paved and unpaved roads. We use a common dashcam to take video along the road. The estimated values are integrated into a database with GPS information and visualized in Google Map, QGIS, or the original visualization system which we developed. To estimate the real width of the road and pothole size, we need to transform the captured forward view image of dashcam video into bird’s-eye-view. For the transformation, we need to estimate the vanishing point in a captured image. However, unlike the advanced countries, it is difficult to detect the vanishing point in developing countries because there are usually no straight lines in the images in the unpaved road of the province. In this study, we propose to use the optical flow method to detect the vanishing point in the rural road. To identify the area of road and the existence of potholes in images, we apply state-of-the-art semantic segmentation using deep learning.

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