Road Roughness Reconstruction Based On LIDAR Sensor

In the Driver-vehicle-road closed loop system,drivers sense the road information by vehicles,and road roughness is an important contributor to the driving comfort and control ability.In order to control the vehicle better and give drivers a comfortable experience,it is necessary to reconstruct road roughness effectively.There have been a lot of research about road signal generation.But most work rely on the model system construction,and response delay is also a problem in it.Moreover,how to get road signal to control vehicle still has a huge gap.So,this article proposes a way to make a real-time reconstruct of road roughness by using LIDAR sensor.Technically,it collected initial data and made an analysis first,and then gave a new way to construct road roughness.Because single scan information is limited,it calculated overlap area of different scan to increase information density,and final road height needs a further migrated correction.Specific contents is described below;First,it elected LIDAR sensor to collect data because of the high accuracy,and made a comparative analysis of different installation,the car lamp height was decided to make a wider scanning at last.It also selected a reasonable preview area and finished coordinate transformation work in this part.Second,it built a continuous road signal.The height measured value approximate a normal distribution,so probability density was brought to make a constant recursion between different scan data.Experimental result show that the road profile became complete and accurate as the scan time increased,but there’s a shift error with real road.Finally,it corrected the shift error to get an accurate road height.According to the thought that make tires and road contact continuously,it made a real-time motion compensation to eliminate deviation of angle and height.Experimental result show that the profile shift can be corrected.And now,the road roughness reconstruction is finished.