Abstract

The SPECIALIST algorithm can resolve jam waves on freeways using roadside technology: detector loops and speed limit gantries. In this paper we extend the algorithm, enabling the integration with cooperative system technologies and other road side detectors, such as in-car detection and actuation, and video-based monitoring (VBM). Integrating these cooperative elements can provide faster and more accurate jam detection, which leads to a better performance of the SPECIALIST algorithm. For the fusion of the various data sources (loops, VBM, floating car data) an extension of the Adaptive Smoothing Method is used. The data fusion method is also adapted to comply with the input requirements of the SPECIALIST algorithm. The resulting system is suitable for a mixed roadside/in-car detection and actuation environment. The performance of the resulting system is evaluated using the microscopic simulator VISSIM. The results show that floating car data and VBM can considerably improve the jam detection times and the accuracy of the detected jam location, which lead to more efficient speed limit schemes.

Abstract

The effects of Cooperative Adaptive Cruise Control (CACC) on traffic flow is an important issue as traffic flow stability, capacity and safety are concerned. In contrast to most research we focus on traffic flow stability. We use the Intelligent Driver Model and CACC algorithms to assess the effects. A recently field-tested and CACC-based advisory system is also evaluated as an intermediate solution. It is found that CACC can quickly damp shockwaves at lower penetration rates (50%) and that shockwaves move faster. ©2010 IEEE.