Road condition evaluation system based on vehicle overload data

Abstract

The invention discloses a road condition evaluation system based on vehicle overload data. The system comprises a data processing module and a vehicle information collection module; the data processing module comprises a wireless monitoring module, a display module, a data storage module, and an information transmission module; the vehicle information collection module comprises a laser scanning module, an overload data collection module, and an annular induction coil; and the laser scanning module comprises a radio frequency reader-writer and an electronic tag. The invention further disclosesa road condition evaluation method based on the vehicle overload data. According to the road condition evaluation system and the method based on the vehicle overload data, all vehicles passing by canbe monitored; the statistics are comprehensive; the monitoring result is accurate; and the subsequent analysis is facilitated. The statistical result is comprehensive, so that the limitation of single vehicle type statistics is avoided; the differences in equivalent axle loads of different vehicle types in different time periods are avoided; and the incompletion of the statistical data due to different times of action is avoided.

Description

Technical field [0001] The invention relates to the field of road condition evaluation, in particular to a road condition evaluation method based on vehicle over-limit and overload data. Background technique [0002] In practice in various parts of our country, vehicles in the traffic flow are usually divided into 6 types: small passenger cars, buses, small trucks, medium trucks, large trucks and container trucks, and a representative model and its Typical axle load values, but the method of only classifying all vehicles into 6 types may be too rough for the amount of traffic composition, because such a classification method may classify vehicles with a large difference in axle type and axle load into the same type. Secondly, in practice, the typical axle load value of each representative vehicle has great arbitrariness. It is often determined based on a small amount of data obtained from surveys many years ago. This makes the value of the coefficient when using the equivalent ax...

AI Technical Summary

Problems solved by technology

[0003] The technical problem to be solved by the present invention is that the typical axle load values ​​of each representative vehicle have great randomness, the vehicle classification is relatively single, the information collection is not comprehensive, and the statistical data time is short and not representative.

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