“Roll-Up-The-Rim” has a different meaning when, every spring, Ontario drivers pay thousands of dollars to replace rims damaged from striking roadway “potholes”. The meaning conveyed to the public is that this is some kind of God-sent, but innocuous, plague that we can only curse at when we are the lucky ones who hit the jackpot. The reality is not so cute.
Those potholes occur when road surfaces are beyond the threshold of minor repair. They are not just isolated dots in an otherwise safe and smooth road surface. They are comparable to a World War II minefield in which we play: rarely do we blow up, but when we do it can be deadly. The deadly aspect of road surface problems, where you could be the unlucky “Roll-Up-The-Rim” winner, is simply not discussed.
But what can you do when your vehicle is damaged from a road surface problem? Many drivers cannot file a claim with their insurance company because that could lead to an increase in their premiums. They might also chose to file a claim with the municipality that is responsible for the road’s maintenance. But Risk Management departments of municipalities are not isolated bodies living in a cave. Risk Managers talk among themselves and know precisely what has been successful in past incidents and in other localities. Their procedures are fine-tuned so that denial of a claim is most likely to wear down most claimants. Often the erection of a “Bump Ahead” or “Rough Road” sign is all that is necessary to deny the claim even though a driver may not be given any useful information from such signs to distinguish a minor surface problem from a damaging one.
The Canadian Automobile Association (CAA) has developed a well-publicized campaign to allow drivers to vent their frustrations by electing roadways with the prized “Worst Road” designation in Ontario. The program requires drivers to submit their complaints to the CAA which then tallies up which roads received the most. Then the road with the most complaints receives the Worst Road designation. This would work well if the number of complaints could reliably differentiate between a bad road in Ottawa from one in Windsor. But subjective comments from participants with unknown intentions or hidden motives is simply a bad way to decide which roads should be fixed while others remain unfixed.
Yet there is a simple way to obtain a scientifically reliable description of the quality and safety of a road surface. By simply using the spying features of a smart phone. Almost everyone carries a smart phone yet few are particularly concerned that these sensing and tracking devices can detect every detail about the user’s actions and where they are located. As an example, the Apple Iphone senses every minute detail about its motion and location in the guise that this data is needed by computer gamers who often communicate their scores over the internet. It does not take much imagination to conceive how such data can also be used to track what a person is doing just from the motions of the Iphone that are detected when it is located on the user’s body. Data can differentiate whether the user is walking, running or travelling in a vehicle.
Those abilities to illegally snoop on everyone’s private actions can be turned into a useful asset. The detailed motions of a person that are sensed by the Iphone can also be used to detect the motions of a vehicle as the principle is exactly the same. Details about the position of the Iphone within the axes of space (x,y,z) can be a direct descriptor of a vehicle’s position when the Iphone is attached, with reasonable security, to the body of the vehicle. Since the Iphone also detects the rate of change in its angle this also provides a very useful descriptor of the rate of change in the motion of a vehicle, and this is where the road surface comes in. By knowing the rate at which the vehicle angle changes we can know how the qualities of a road surface have caused a vehicle to be “bumped around” in space as it travels along a roadway.
At Gorski Consulting we have chosen to use the rate of change in the lateral and longitudinal motions of a vehicle to describe what the road surface must be like in order to produce those reactions. Given that a cyclical motion can provide angles that are either negative or positive it was decided to take the standard deviation of those data as a way of describing the magnitude of that motion regardless of its direction. Through our testing on a variety of roads in South-Western Ontario we have developed a set of guidelines for the interpretation of the data. The rate of rotation of the vehicle is expressed in radians per second. One radian is equal to 57.3 degrees. We have observed that the following descriptions apply for the following, data ranges:
Below 0.0200 radians per second = A good, smooth road surface,
0.0200 to 0.0500 radians per second = A range of relatively good surface at the low end and approaching a poor surface at the high end,
Above 0.0500 radians per second = A poor road surface that may be a safety risk depending on the type of vehicle and the existing environmental factors.
These guidelines are for situations where a vehicle is travelling at a typical speed for the road in question and the data are an average over time of at least 20 seconds. As an example, at a highway speed of 80 km/h a vehicle travels about 22.2 metres every second. So a travel time of 20 seconds would result in a travel distance of about 444 metres, or almost a half a kilometre. The purpose of using such longer distances is so that the judged quality of the road surface is not dominated by an isolated defect on an otherwise, good-quality road. Although the data is reported for such longer distances it can be appreciated that the raw data is always in its original form and any shorter or longer segments can be selected to a user’s preference. Descriptors for shorter distances may be preferred for those instances where an analyst is examining a specific road feature.
As an example, the standard deviation of a lateral rate of rotation of 0.0500 radians per second would be equal to a rotation of 2.9 degrees per second. This means that the vehicle’s body could be moving up or down, alternating on each side, in a cyclical fashion such that the speed of that lateral rotation results in a change of lateral angle of 2.9 degrees every second.
The type of surface that would produce that type of lateral motion has been found on Sunningdale Road between Highbury Ave and Clarke Road in the north-eastern outskirts of the City of London, Ontario. This road segment of about 2.5 kilometres long and has a posted maximum speed of 80 km/h. A large amount of testing has been done at this site at speeds ranging between 40 and 90 km/h. A number of articles have been uploaded to the Gorski Consulting website in 2014 and 2015.
While these discussions may appear to be detailed, the procedure to obtain reliable, scientific data that identifies the character of a road surface is not that complicated. Usually an app is purchased at a nominal price that allows access to the Iphone data. A location in the test vehicle is found which is preferably in the centre and at a low vertical level. The Iphone needs to be attached securely to the vehicle body and that can often be accomplished with Velcro tape. A button is pressed in the app which starts the recording and the same button is used to stop. The recorded file is then sent in an e-mail to the user’s office computer. At the office the file is transferred to an Excel spreadsheet where changes are made to remove unneeded data while making changes to the format so that it can be easily displayed in Excel charts. Finding the columns containing the “X rate of Rotation” and the “Y rate of Rotation” data is straightforward as the titles will be displayed at the top of each column. Excel proves a variety of formulas that allow a selection of a subset of the recording and display of statistics such as standard deviations.
At Gorski Consulting the capture of the Iphone data is also accompanied by the use of multiple video cameras. The instrument panel cluster is videotaped to document the vehicle speed and the value of other instruments. A camera may be positioned at the brake/accelerator pedals. A large protractor is often attached to the steering wheel and a video camera documents the steering inputs. Views of the underside of the test vehicle may display the motions of the vehicle suspension. External views of the roadway enable a visual record of the surface conditions that resulting in the Iphone data.
None of these videotaping procedures are essential to the average person unless there is a need to demonstrate how the data was captured for official purposes such as potential civil or criminal litigation. Whatever data is captured can be compared to what is uploaded in the Road Data page of the Gorski Consulting website and we would be pleased to cooperate with such ventures if asked. Up to now a single test vehicle (2007 Buick Allure) has been used in gathering the data. Some maintenance procedures such as the replacement of all the struts had to be made to make sure the aging of the test vehicle did not produce confounds in the data.
In the end, the objective data that is obtained via a smart phone in a test vehicle can be a reliable way of comparing the severity of problems with one road surface versus another. The utility of the procedure is in the fact that almost everyone carries a smart phone and no special equipment needs to be purchased to obtain the road data. Similarly, any roadworthy motor vehicle can be used in the testing although consideration needs to be given to how the data might change if the vehicle characteristics are largely variant. Thus a passenger car with a cruising-type of suspension may provide different data from a sports car with a tight suspension and possible low-profile tires. Obviously a truck test vehicle is likely to produce different data from a passenger car. A car with small diameter rims may produce different data than one with large rims. And so on.
For collision reconstruction experts procedures like these can be used to compare the data that may be captured in an Event Data Recorder (“Black Box”). The newer vehicles are often equipped with modules that may capture the tri-axial accelerations as well as the vehicle motions. As these data are generated from proprietary sensors and algorithms it is not always possible to understand how the EDR data was generated even when general descriptors are provided. Using an independent method of capturing data while travelling over the same collision site may provide additional insights into the meaning of the EDR data. This is particularly so with the use of the additional equipment such as the multiple video cameras and steering wheel protractor.