This is a no brainer. Using bicycles to commute is the most sustainable form of transport, is the least expensive to use and are pollution-free. Towns and cities have to be made bicycle-friendly to encourage their wide usage. Therefore, cycling paths should be more convenient, comfortable, and safe to ride. This paper investigates a smartphone application, which passively monitors the road conditions during cyclists ride. To overcome the problems of monitoring roads, we present novel algorithms that sense the rough cycling paths and locate road bumps. Each event is detected in real time to improve the user friendliness of the application. Cyclists may keep their smartphones at any random orientation and placement. Moreover, different smartphones sense the same incident dissimilarly and hence report discrepant sensor values. We further address the aforementioned difficulties that limit such crowd-sourcing application. We evaluate our sensing application on cycling paths in Singapore, and show that it can successfully detect such bad road conditions.
Detecting road potholes and road roughness levels is key to road condition monitoring, which impacts transport safety and driving comfort. We propose a crowd sourcing based road surface monitoring system, simply called em CRSM . CRSM can effectively detect road potholes and evaluate road roughness levels using our hardware modules mounted on distributed vehicles. These modules use low-end accelerometers and GPS devices to obtain vibration pattern, location, and vehicle velocity. Considering the high cost of onboard storage and wireless transmission, a novel light-weight data mining algorithm is proposed to detect road surface events and transmit potential pothole information to a central server. The server gathers reports from the multiple vehicles, and makes a comprehensive evaluation on road surface quality. We have implemented a product-quality system and deployed it on 100 taxies in the Shenzhen urban area. The results show that CRSM can detect road potholes with up to 90 accuracy, and nearly zero false alarms. CRSM can also evaluate road roughness levels correctly, even with some interferences from small bumps or potholes. A study by US Federal Highway Administration has shown that road condition is an essential factor of highway quality and smooth roads will lead to more comfortable driving experience and less municipal investment. International Roughness Index (IRI) has been widely used to measure pavement smoothness because it can provide a consistent rating for different measurement tools. However, existing measuring tools based on IRI are usually very expensive. In this paper, we present a low-cost vehicle-based solution, Road Condition Monitoring with Three-axis Accelerometers and GPS Sensors (RCM-TAGPS), by using a cheap three-axis accelerometer and a GPS sensor embedded in a vehicle to monitor the road condition. We analyze the Power Spectral Density (PSD) of pavement roughness, estimate IRI, and classify the pavement roughness level into four levels according to a Chinese industry standard. Experimental results show that RCM-TAGPS can evaluate pavement roughness level correctly, even under some interference like potholes, manholes and decelerating belts, and the total cost of RCM-TAGPS in each vehicle is no more than 50 dollars, which is about 1 4400 to 1 160 of the existing system used in civil engineering and municipal engineering.