scholarly journals Effects of smartphone sensor variability in road roughness evaluation

2021 ◽  
pp. 1-6
Author(s):  
Hafiz Usman Ahmed ◽  
Liuqing Hu ◽  
Xinyi Yang ◽  
Raj Bridgelall ◽  
Ying Huang
Keyword(s):  
Road Roughness ◽  
Roughness Evaluation ◽  
Smartphone Sensor

Precision Enhancement of Smartphone Sensor-Based Pavement Roughness Estimation by Standardizing Host Vehicle Speed

2021 ◽  
Author(s):  
Janani L ◽  
Rashmi Doley ◽  
Sunitha V. ◽  
Samson Mathew
Keyword(s):  
Road Safety ◽  
Condition Assessment ◽  
Operating Costs ◽  
Vehicle Speed ◽  
Evaluation Technique ◽  
Pavement Roughness ◽  
Smartphone Sensors ◽  
Roughness Evaluation ◽  
Conventional Methods ◽  
Smartphone Sensor

Condition assessment of pavement has a predominant part in delivering safety and comfort to users. Roughness is considered the most important characteristic as it affects road safety and vehicle operating costs. Authorities spend significant quantity of resources on using conventional methods for measuring roughness. Many researches are performed to estimate roughness by deploying smartphone sensors. However, no consideration is given to host vehicle speed influence in roughness evaluation using smartphones. This work explains a smartphone-sensor-based roughness evaluation technique by deploying the QCS model. The accuracy is checked with simultaneously collected IRI by a Roughometer. Results of the smartphone-based pavement roughness estimation experiment showed a high correlation value of 0.73, and proved the accuracy of the method. The data were segregated based on three speed ranges. The correlation between the smartphone-based and Roughometer-based IRI for all ranges was analyzed, and the R2 value of 0.75 was exhibited for 31-50 km/hr range.

scholarly journals Road roughness evaluation using in-pavement strain sensors

2015 ◽  
Vol 24 (11) ◽  
pp. 115029 ◽  
Author(s):  
Zhiming Zhang ◽  
Fodan Deng ◽  
Ying Huang ◽  
Raj Bridgelall
Keyword(s):  
Strain Sensors ◽  
Road Roughness ◽  
Roughness Evaluation

scholarly journals Use of generated artificial road profiles in road roughness evaluation

2017 ◽  
Vol 25 (1) ◽  
pp. 24-33 ◽  
Author(s):  
Giuseppe Loprencipe ◽  
Pablo Zoccali
Keyword(s):  
Road Roughness ◽  
Roughness Evaluation

An investigation on scalability of SMA composite by roughness evaluation of SMA wires

2004 ◽  
Vol 115 ◽  
pp. 343-349 ◽  
Author(s):  
L. F. Campanile ◽  
J. Mircea ◽  
S. Homann
Keyword(s):  
Roughness Evaluation

scholarly journals Road Roughness Estimation Based on the Vehicle Frequency Response Function

Actuators ◽  
2021 ◽  
Vol 10 (5) ◽  
pp. 89
Author(s):  
Qingxia Zhang ◽  
Jilin Hou ◽  
Zhongdong Duan ◽  
Łukasz Jankowski ◽  
Xiaoyang Hu
Keyword(s):  
Frequency Response ◽  
Response Function ◽  
Frequency Response Function ◽  
Gaussian White Noise ◽  
Estimation Method ◽  
Time Shift ◽  
Ride Quality ◽  
The Road ◽  
Road Roughness ◽  
Measured Response

Road roughness is an important factor in road network maintenance and ride quality. This paper proposes a road-roughness estimation method using the frequency response function (FRF) of a vehicle. First, based on the motion equation of the vehicle and the time shift property of the Fourier transform, the vehicle FRF with respect to the displacements of vehicle–road contact points, which describes the relationship between the measured response and road roughness, is deduced and simplified. The key to road roughness estimation is the vehicle FRF, which can be estimated directly using the measured response and the designed shape of the road based on the least-squares method. To eliminate the singular data in the estimated FRF, the shape function method was employed to improve the local curve of the FRF. Moreover, the road roughness can be estimated online by combining the estimated roughness in the overlapping time periods. Finally, a half-car model was used to numerically validate the proposed methods of road roughness estimation. Driving tests of a vehicle passing over a known-sized hump were designed to estimate the vehicle FRF, and the simulated vehicle accelerations were taken as the measured responses considering a 5% Gaussian white noise. Based on the directly estimated vehicle FRF and updated FRF, the road roughness estimation, which considers the influence of the sensors and quantity of measured data at different vehicle speeds, is discussed and compared. The results show that road roughness can be estimated using the proposed method with acceptable accuracy and robustness.

scholarly journals Multi-Objective Optimisation of Tyre and Suspension Parameters during Cornering for Different Road Roughness Profiles

2021 ◽  
Vol 11 (13) ◽  
pp. 5934
Author(s):  
Georgios Papaioannou ◽  
Jenny Jerrelind ◽  
Lars Drugge
Keyword(s):  
Optimal Solution ◽  
Design Parameters ◽  
Road Vehicles ◽  
Propulsion Systems ◽  
Vehicle Handling ◽  
Optimum Parameters ◽  
Trade Offs ◽  
Road Roughness ◽  
Control Technologies ◽  
Tyre Wear

Effective emission control technologies and novel propulsion systems have been developed for road vehicles, decreasing exhaust particle emissions. However, work has to be done on non-exhaust traffic related sources such as tyre–road interaction and tyre wear. Given that both are inevitable in road vehicles, efforts for assessing and minimising tyre wear should be considered. The amount of tyre wear is because of internal (tyre structure, manufacturing, etc.) and external (suspension configuration, speed, road surface, etc.) factors. In this work, the emphasis is on the optimisation of such parameters for minimising tyre wear, but also enhancing occupant’s comfort and improving vehicle handling. In addition to the search for the optimum parameters, the optimisation is also used as a tool to identify and highlight potential trade-offs between the objectives and the various design parameters. Hence, initially, the tyre design (based on some chosen tyre parameters) is optimised with regards to the above-mentioned objectives, for a vehicle while cornering over both Class A and B road roughness profiles. Afterwards, an optimal solution is sought between the Pareto alternatives provided by the two road cases, in order for the tyre wear levels to be less affected under different road profiles. Therefore, it is required that the tyre parameters are as close possible and that they provide similar tyre wear in both road cases. Then, the identified tyre design is adopted and the optimum suspension design is sought for the two road cases for both passive and semi-active suspension types. From the results, significant conclusions regarding how tyre wear behaves with regards to passenger comfort and vehicle handling are extracted, while the results illustrate where the optimum suspension and tyre parameters have converged trying to compromise among the above objectives under different road types and how suspension types, passive and semi-active, could compromise among all of them more optimally.

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