Road Surface Friction Coefficient Research Articles

FriC-PM: Machine Learning-based road surface friction coefficient predictive model using intelligent sensor data

Providing a robust traffic management system is a given for road authorities today, for safer mobility and reliable day-to-day operations. Therefore, to improve traffic management procedures in order to provide an open road for road users at all times, understanding road surface friction measurement is crucial. Currently, the automatic prediction model of road surface friction measurement (FriC-PM) is highly demanded by road transport owners and operators. The prediction accuracy of road surface friction is linked to several external variables related to the weather conditions, road surface micro- and macro-texture, tire properties, driving speed and behaviour of road users. This paper presents a trained novel predictive model developed for the measurement of road surface friction considering a big dataset of 18 months with daily records through novel intelligent road-based passive sensor measurement, on a Spanish highway section. The trained predictive model is developed on the machine learning (ML) approaches, namely support vector machine (SVM), and validated with the K-Fold cross-validation (CV) algorithm taking into account various kernels. In addition, error evaluation strategies are applied to the trained model in order to identify the efficiency, accuracy, and reliability of the predictive model. The main purpose of the proposed prediction model is to provide comprehensive knowledge about predictive road surface friction coefficient, and to support decision-making elements to road owners or operators for reliable predictive maintenance process.

Addressing Uncertainty by Designing an Intelligent Fuzzy System to Help Decision Support Systems for Winter Road Maintenance

One of the main challenges in developing efficient and effective winter road maintenance is to design an accurate prediction model for the road surface friction coefficient. A reliable and accurate prediction model of road surface friction coefficient can help decision support systems to significantly increase traffic safety, while saving time and cost. High dynamicity in weather and road surface conditions can lead to the presence of uncertainties in historical data extracted by sensors. To overcome this issue, this study uses an adaptive neuro-fuzzy inference system that can appropriately address uncertainty using fuzzy logic neural networks. To investigate the ability of the proposed model to predict the road surface friction coefficient, real data were measured at equal time intervals using optical sensors and road-mounted sensors. Then, the most critical features were selected based on the Pearson correlation coefficient, and the dataset was split into two independent training and test datasets. Next, the input variables were fuzzified by generating a fuzzy inference system using the fuzzy c-means clustering method. After training the model, a testing set was used to validate the trained model. The model was evaluated by means of graphical and numerical metrics. The results show that the constructed adaptive neuro-fuzzy model has an excellent ability to learn and accurately predict the road surface friction coefficient.

A Concept for Using Road Wetness Information in an All-Wheel-Drive Control

This paper presents a concept for using road wetness information in an all-wheel-drive (AWD) control that distributes drive torques in the longitudinal direction. Driving on wet roads requires special attention. Not only does the road surface friction coefficient decrease, but driving dynamics targets must be adjusted to prevent vehicle instability under wet conditions. As an exemplary application, the otherwise generic control concept is implemented on an AWD vehicle with a torque-on-demand transfer case. Therefore, the AWD topology of a drive train with a torque-on-demand transfer case is analysed in advance in terms of occurring torques and rotational speeds. In the following, the vehicle dynamics goals for driving in wet road conditions are described—divided into primary and secondary goals. Starting from a state-of-the art AWD control, an adaptive control strategy is derived by superimposing a wetness coordination unit. With the knowledge of occurring road wetness, this unit adapts newly introduced parameters in order to meet the target driving behaviour under wet conditions. Lastly, the derived AWD control is implemented into a 14-DOF, non-linear vehicle model in Matlab/Simulink, which is used as a virtual plant. The performance of the developed concept is assessed by the driving maneuver “Power On Cornering“ (PON), which means an acceleration out of steady-state circular motion. As its essential benefit, the AWD control enables a maximum spread between driving stability, agility and traction under combined dynamics when using wetness information. The newly introduced wetness coordination unit uses only a few additional and physically interpretable key parameters for this purpose, without significantly increasing the controller complexity.

Real-time measurement of road friction coefficient with intelligent tires

In recent years, various Advanced Driver Assistance Systems (ADAS) have been developed. Current ADAS generally use information obtained from wheel speed, acceleration, yaw rate sensors and so on. However, it is difficult to measure the road friction coefficient in real time with ordinary sensors, and vehicle motion control according to the road surface has not been realized. Therefore, the measurement of road surface friction coefficients is important to improve vehicle safety. Thus, this research is being conducted to develop intelligent tires that can measure the road surface friction coefficient. The authors have already proposed a method to measure the road surface friction coefficient from the strain generated on the bottom surface of the wheel. In this study, real-time measurement of the road surface friction coefficient using the proposed method was conducted on four wheels, and the validity of the measurement was verified by comparing the results with simulation results using CarSim.

Measurement of road surface friction coefficient in real-time with measuring the tire deformation

Measurement of road surface friction coefficient in real-time with measuring the tire deformation

Road tire friction coefficient estimation for four wheel drive electric vehicle based on moving optimal estimation strategy

In this paper, a moving horizon estimation strategy for the four-wheel drive electric vehicle is proposed considering the characteristic that the torque and wheel speed can be obtained. Based on the HSRI tire model, two methods for estimating the friction coefficient of the road surface are designed. The first method indirectly uses the utilization friction coefficient to estimate the road surface friction coefficient. The second method performs the estimation by transforming the equation of the HSRI and changing the implicit form into a explicit form. The estimation algorithm can fully consider the constraints of the estimated amount under actual physical conditions, and not depend on the selection of the initial estimate information. Then, using the advantages of the two methods, the combined optimization design is performed to obtain the accurate estimation. Finally, the effectiveness of the estimator was verified by the joint simulation platform of AMESim and Simulink under high friction coefficient pavement, low friction coefficient pavement and varying friction coefficient pavement conditions.

Study of Accuracy Improvement on NIR Spectral Polarimetry and Application to Image Analysis by Backscattered Light for Measurement of Friction Coefficient of Icy Road Surface

Study of Accuracy Improvement on NIR Spectral Polarimetry and Application to Image Analysis by Backscattered Light for Measurement of Friction Coefficient of Icy Road Surface

Driving risk of road vehicle shielded by bridge tower under strong crosswind

Moving on a bridge, a road vehicle will experience a gusty crosswind caused by the shielding effects of the bridge tower. The corresponding driving safety is affected by several uncertain factors. In this study, a closed-loop driver-vehicle-crosswind (DVC) model is established to obtain the dynamic responses of the vehicle under given driving conditions. The nonlinear tire cornering force, the real driver behavior and the vehicle aerodynamic loads considering the wind shielding effects of the bridge tower can be taken into account. Based on the support vector classifier approach, a probability-based procedure is established to assess the driving risk of a road vehicle passing by a bridge tower under crosswind. A typical two-axle road vehicle passing by a bridge tower is studied as a numerical case. The dynamic responses of the vehicle and driver reaction under two given driving conditions are analyzed by solving the DVC numerical model firstly. Then, the probability-based model is used to assess the driving risk of the vehicle under different driving conditions; the effects of vehicle speed, wind velocity and friction coefficient of road surface on the driving risk are investigated.

Theoretical Study of NIR Spectral Polarimetry and Application to Image Analysis for Measurement of Friction Coefficient of Icy Road Surface

Theoretical Study of NIR Spectral Polarimetry and Application to Image Analysis for Measurement of Friction Coefficient of Icy Road Surface

Measurement of road surface friction coefficient with strains on a side surface of a tire

Measurement of road surface friction coefficient with strains on a side surface of a tire

Proposal of the road surface friction coefficient real-time estimation method

Proposal of the road surface friction coefficient real-time estimation method

凍結防止剤散布による氷膜の融解を伴う密粒度および粗面系舗装面のすべり摩擦係数の推定法

本論文では，密粒度舗装，機能性SMAおよび排水性舗装を対象に，低温恒温室で氷膜路面への凍結防止剤散布実験を実施し，凍結防止剤散布後の各舗装上の氷膜厚および路面すべり摩擦係数μを評価した．また，凍結防止剤散布後のμの推定法を構築し，任意の路面温度における凍結防止剤散布後のμの推定値を舗装種別間で比較した． 結果，(1)平均氷膜厚は，いずれの舗装も凍結防止剤散布量の増大とともに線形的に低下する．(2)μは，平均氷膜厚の増大とともに指数関数的に低下する．(3)機能性SMAおよび排水性舗装の鉛直損失塩率は，散水量の増大につれて減少する傾向にある，ことが分かった．本研究により，凍結防止剤散布後のμは，路面温度・散水量・凍結防止剤散布量が同じであっても，舗装の種類によって異なることが示された．

차량속도와 도로의 종단경사 변화에 따른 차량거동 특성

Abstract When a vehicle is running on the road, the surface conditions and environment of road by reason of insufficient road design standards is so greatly that have an effect on drivers. In particular, the road design of the past is conducted empirical and ideal judgment, but recently, the new technical development is attempted that three and four dimensional parameters is reconsidering and adjusting at the same time. In this study, we analyzed the vehicle behavior characteristics according to the change of driving speed and vertical grades on braking at the peak point of the frozen road by using a PC-crash program for traffic accident reconstruction. As a result, we were conformed the fact that the friction coefficient of road surface and the vehicle speed is affected by vehicle behavior characteristics for intersection vertical grades and were showed the feasibility of verification through a simulation in order to solve the problem of road design in advance. Key Words : Intersection, Vertical Grades, PC-crash, Load Alignment

PC-Crash 프로그램을 이용한 교통사고 충돌해석에 관한 신뢰성 연구

자동차 충돌해석은 다양한 형태로 구성되어 충돌중 차량에 대한 속도변화는 차량간의 충돌정도 또는 승객의 안전도를 평가하는 데 중요한 요소로 활용된다. 이로 인해 충돌해석 프로그램을 활용한 속도변화에 따른 결과치를 해 석하는 방법이 필요하다. 본 연구에서는 PC-Crash 프로그램을 이용하여 노면의 마찰계수에 따라 차량속도에 따른 제 동거리를 실제값과 해석값을 비교하여 마찰계수가 작을 때 오차가 큼을 알 수 있었고, 서로 다른 주 차량(MATIZ, SONATA 및 버스 적용)이 교차로에서 충돌하는 속도의 오차범위는 차량무게의 차이에 따라 최대오차는 1.2%, 1.8%, 3.1%으로 나타났다. 또한 인천대교 버스추락 사고를 재현하기 위하여 시뮬레이션을 한 결과로 다소 오차는 있었으나 사고 재구성을 검증할 수 있었다.

Research of Safe Speed at Snow on Freeway Based on Braking Model of Stopping Sight Distance

The brake model derivation based on the kinematics of the stopping sight distance analysis, considering the freeway visibility and road surface friction coefficient, put forward freeway safety speed calculation model in snow condition, reach maximum safe speed of snow freeway in a different visibility and road adhesion coefficient snow condition, provide a management reference for freeway snow driving safety.

衝突被害軽減ブレーキの効果に及ぼす路面摩擦係数の影響 : 車両衝突シミュレーションによる検討(<特集>D&D2009)

Collision Mitigation Brake (CMB) is a part of the Pre-crash safety system intended to mitigate damage during vehicle collisions. In this study, the effects of CMB system on vehicle rear-end collision accidents were investigated. To this end, a dynamic vehicle simulation model was constructed, in which the sensor and the CMB model were built. By using this model, the reduction of collision speed by the CMB system was evaluated numerically. Here, the road surface friction coefficient is considered to have a large influence on the CMB. In addition, the Time to Collision (TTC) which is the judgment line of the brake initiation is the key factor to the efficient operation of CMB. Therefore, simulations were carried out on road surfaces with different friction coefficient and CMB system with different values of TTC. Generally, the effect of CMB is expected to increase with the rise of friction coefficient of the road and the value of TTC. A larger value of TTC will be preferred for the cases of roads with low friction coefficients. However, collision avoidances might occur when the large value of TTC is employed in low speed collisions. Finally, the findings reveled that the value of TTC should be controlled in such that the value is increased for roads with low friction coefficient and decreased for low speed collisions.

The Influence of Road Surface Friction Coefficient on the Effect of Collision Mitigation Brake

Collision Mitigation Brake (CMB) is a part of the Pre-crash safety system intended to mitigate damage during vehicle collisions. In this study, the effects of CMB system on vehicle rear-end collision accidents were investigated. To this end, a dynamic vehicle simulation model was constructed, in which the sensor and the CMB model were built. By using this model, the reduction of collision speed by the CMB system was evaluated numerically. Here, the road surface friction coefficient is considered to have a large influence on the CMB. In addition, the Time to Collision (TTC) which is the judgment line of the brake initiation is the key factor to the efficient operation of CMB. Therefore, simulations were carried out on road surfaces with different friction coefficient and CMB system with different values of TTC. Generally, the effect of CMB is expected to increase with the rise of friction coefficient of the road and the value of TTC. A larger value of TTC will be preferred for the cases of roads with low friction coefficients. However, collision avoidances might occur when the large value of TTC is employed in low speed collisions. Finally, the findings revealed that the value of TTC should be controlled in such that the value is increased for roads with low friction coefficient and decreased for low speed collisions.

1216 ABS信号を利用した路面の摩擦係数測定システム : 旋回を考慮したスリップ率の測定(機械力学・計測制御III)

1216 ABS信号を利用した路面の摩擦係数測定システム : 旋回を考慮したスリップ率の測定(機械力学・計測制御III)

656 衝突被害軽減ブレーキの効果に及ぼす路面摩擦係数の影響 : 車両衝突シミュレーションによる検討

656 衝突被害軽減ブレーキの効果に及ぼす路面摩擦係数の影響 : 車両衝突シミュレーションによる検討

Nonlinear Body Slip Angle Observer for Electric Vehicle Stability Control

This paper proposes a nonlinear observer for Body Slip Angle (β) estimation, in which a nonlinear tire model is adopted for the observer design. A newly developed method to identify parameters of road surface friction coefficient (μ) is introduced into this observer, which makes the observer adaptive to road condition changing. Simulations and field tests are conducted, where the feasibility of μ identification and effectiveness of the observer are checked, especially for nonlinear cornering situations.