Road quality is one of the most important factors influence the behaviors of vehicles, which may increase the safety of the autonomous vehicle with adaptive cruise control (ACC) model if take into consideration. This paper tends to investigate the impact of ride quality on the driving behavior of autonomous vehicles through the simulation tool, VISSIM. The road impact factor (RIF), a road quality index detected from the accelerometers on the smart mobile devices placed on regular vehicles, is used to describe the road quality. If the detected peak RIF is over a certain value, the communication to the autonomous vehicle will indicate a need to reduce the speed in the micro-simulator “Verkehr In Städten – SIMulationsmodell” (VISSIM) simulation. The difference between the driving behavior of the ACC vehicles with and without knowing the ride quality will be used to evaluate the impact of ride quality on driving behavior of autonomous vehicles through simulation.
According to the Federal Highway Administration (FHWA), in 2012, there were 1,357,430 miles of unpaved road in the United States, accounting for almost 35 percent of the more than 4 million miles of roadway in the Nation. Maintaining unpaved roads in good condition requires frequent evaluation of their ride quality. Common methods of ride quality evaluation such as the international roughness index (IRI) and profilograph index (PrI) are applicable for paved roads only. They require special types of equipment that are expensive and time-consuming to use. Hence, agencies cannot afford to extend the capabilities of existing equipment to monitor the ride quality of unpaved roads. This paper evaluates the use of smartphones on regular vehicles as an alternative. The method used a road roughness index called the road impact factor (RIF) to quantify the ride quality. Field experiments showed that the method provides consistent measurements and, therefore, is an attractive alternative for monitoring the ride quality of all unpaved roads in the Nation.
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