scholarly journals Interval Recognition Algorithm of the Pavement Surface Condition Based on Lagrange Interpolation Method

2020 ◽  
Vol 2020 ◽  
pp. 1-8 ◽  
Author(s):  
Ren He ◽  
Liwei Zhang
Keyword(s):  
Lagrange Interpolation ◽  
Interpolation Method ◽  
Estimation Error ◽  
Surface Condition ◽  
Recognition Algorithm ◽  
Identification Algorithm ◽  
Pavement Surface ◽  
Road Condition ◽  
Road Friction ◽  
Road Friction Coefficient

The accurate recognition of road condition is one of the important factors that influence vehicle safety performance. This paper comes up with an original mathematical method of an interval recognition algorithm of the pavement surface condition based on Lagrange interpolation. The ordinate of the peak point is solved by the Lagrange interpolation method, and the pavement surface condition is deduced by the interval identification algorithm. The simulation results from six typical roads and the varied pavement surface show that besides the cobblestone pavement which is not common in the daily road, the estimation error of the initial tire-road friction coefficient by the Lagrange interpolation method is less than 2%, the pavement surface condition can be identified by interval recognition algorithm quickly and accurately, and the response time is less than 0.2 seconds.

scholarly journals Study on Road Friction Database for Automated Driving - Fundamental Consideration of Measuring Device for Road Friction Database -

2021 ◽  
Author(s):  
Tetsunori Haraguchi ◽  
Ichiro Kageyama ◽  
Yukiyo Kuriyagawa ◽  
Tetsuya Kaneko ◽  
Motohiro Asai ◽  
...  
Keyword(s):  
Friction Coefficient ◽  
Traffic Safety ◽  
Surface Condition ◽  
Automated Driving ◽  
Friction Coefficients ◽  
Measuring Device ◽  
The Road ◽  
Road Friction ◽  
Road Friction Coefficient ◽  
Fundamental Consideration

This research deals with the possibility for construction of the database on the braking friction coefficient for actual roads from the viewpoint of traffic safety especially for automated driving such as level 4 or higher. In an automated driving such levels, the controller needs to control the vehicle, but the road surface condition, especially the road friction coefficient on wet roads, snowy or icy roads, changes greatly, and in some cases, changes by almost one order. Therefore, it is necessary for the controller to constantly collect environment information such as the road friction coefficients and prepare for emergencies such as obstacle avoidance. However, at present, the measurement of the road friction coefficients is not systemically performed, and a method for accurately measuring has not been established. In order to improve this situation, this study examines a method for continuously measurement for the road friction characteristics such as μ-s characteristics.

GPS-Based Real-Time Identification of Tire-Road Friction Coefficient

2002 ◽  
Author(s):  
J. O. Hahn ◽  
R. Rajamani ◽  
L. Alexander
Keyword(s):  
Friction Coefficient ◽  
Control Systems ◽  
Real Time ◽  
Identification System ◽  
Force Model ◽  
Identification Algorithm ◽  
Cruise Control ◽  
Differential Gps ◽  
Road Friction ◽  
Road Friction Coefficient

Vehicle control systems such as collision avoidance, adaptive cruise control and automated lane-keeping systems as well as ABS and stability control systems can benefit significantly from being made “road-adaptive”. The estimation of tire-road friction coefficient at the wheels allows the control algorithm in such systems to adapt to external driving conditions. This paper develops a new tire-road friction coefficient estimation algorithm based on measurements related to the lateral dynamics of the vehicle. A lateral tire force model parameterized as a function of slip angle, friction coefficient, normal force and cornering stiffness is used. A real-time parameter identification algorithm that utilizes measurements from a differential GPS system and a gyroscope is used to identify the tire-road friction coefficient and cornering stiffness parameters of the tire. The advantage of the developed algorithm is that it does not require large longitudinal slip in order to provide reliable friction estimates. Simulation studies indicate that a parameter convergence rate of one second can be obtained. Experiments conducted on both dry and slippery road indicate that the algorithm can work very effectively in identifying a slippery road. Two other new approaches to real-time tire road friction identification system are also discussed in the paper.

Simulation Analyzed of Vehicle Operating Safety in Rain Weather Condition Based on ADAMS

2013 ◽  
Vol 361-363 ◽  
pp. 2057-2060
Author(s):  
Hai Lin Si
Keyword(s):  
Friction Coefficient ◽  
Model Simulation ◽  
Lateral Displacement ◽  
Weather Condition ◽  
Coupling Model ◽  
Lane Change ◽  
Vehicle Speed ◽  
Road Condition ◽  
Road Friction ◽  
Road Friction Coefficient

The safety of vehicle operating has tight relation with the road condition; vehicle operating safety accident is easy occurred in badness road condition. This paper studied the vehicle Operating Safety in rain weather condition based on Multi-Rigid Body system Automatic Dynamic Analysis of Mechanical Systems (ADAMS). The models include Vehicle model, Road model, Vehicle and Road coupling model, Simulation module were set up. By changing road friction coefficient, road conditions in sunny day, dry, and rain weather were simulated. Single lane change text and ramp steering text were carried out, and the response output of lateral displacement was obtained. Computation result indicated that in the single lane change when road friction coefficient in rain weather is 0.4, vehicle speed is 60km/h in the single line simulation; the vehicle will be easily out of control. When vehicle speed is 55 km/h, maximum steer value is 70degree in the single lane simulation, vehicle will go haywire. In the ramp steer simulation when vehicle speed is 40 km/h, vehicle will go haywire.

scholarly journals Analysis of Nonsevere Crashes on Two- and Four-Lane Urban and Rural Highways: Effects of Wet Pavement Surface Condition

2018 ◽  
Vol 2018 ◽  
pp. 1-10 ◽  
Author(s):  
Aschalew Kassu ◽  
Michael Anderson
Keyword(s):  
Negative Binomial ◽  
Surface Condition ◽  
Negative Binomial Regression ◽  
Segment Length ◽  
Mean Values ◽  
Rural Highways ◽  
Explanatory Variables ◽  
Crash Data ◽  
Pavement Surface ◽  
Binomial Regression

This study examines the effects of wet pavement surface conditions on the likelihood of occurrences of nonsevere crashes in two- and four-lane urban and rural highways in Alabama. Initially, sixteen major highways traversing across the geographic locations of the state were identified. Among these highways, the homogenous routes with equal mean values, variances, and similar distributions of the crash data were identified and combined to form crash datasets occurring on dry and wet pavements separately. The analysis began with thirteen explanatory variables covering engineering, environmental, and traffic conditions. The principal terms were statistically identified and used in a mathematical crash frequency models developed using Poisson and negative binomial regression models. The results show that the key factors influencing nonsevere crashes on wet pavement surfaces are mainly segment length, traffic volume, and posted speed limits.

Sign in / Sign up

Export Citation Format

Share Document