With the rapid development of smart cities, interest in vehicle automation continues growing. Autonomous vehicles are becoming more and more popular among people and are considered to be the future of ground transportation. Autonomous vehicles, either with adaptive cruise control (ACC) or cooperative adaptive cruise control (CACC), provide many possibilities for smart transportation in a smart city. However, traditional vehicles and autonomous vehicles will have to share the same road systems until autonomous vehicles fully penetrate the market over the next few decades, which leads to conflicts because of the inconsistency of human drivers. In this paper, the performance of autonomous vehicles with ACC/CACC and traditional vehicles in mixed driver environments, at a signalized intersection, were evaluated using the micro-simulator VISSIM. In the simulation, the vehicles controlled by the ACC/CACC and Wiedemann 99 (W99) model represent the behavior of autonomous vehicles and human driver vehicles, respectively. For these two different driver environments, four different transport modes were comprehensively investigated: full light duty cars, full trucks, full motorcycles, and mixed conditions. In addition, ten different seed numbers were applied to each model to avoid coincidence. To evaluate the driving behavior of the human drivers and autonomous vehicles, this paper will compare the total number of stops, average velocity, and vehicle delay of each model at the signalized traffic intersection based on a real road intersection in Minnesota.
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.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.