Algorithms for Automatic Merging of Vehicles

Automakers are trying to make vehicles more intelligent and safe by embedding processors which can be used to implement “by-wire” applications for taking smart decisions on the road or assisting the driver in doing the same. Given this proliferation, there is a need to minimize the computational capacity required without affecting the performance and safety of the applications. The latter is especially important since these by-wire applications are distributed and realtime in nature and involve deadline bound computations on critical data gathered from the environment. These applications have stringent requirements on the freshness of data items and completion time of the tasks. Our work studies one such safetyrelated automotive application namely, Automatic Merge Control (AMC), which ensures safe vehicle maneuver in the region where two or more roads intersect. As our contributions, we (i) propose three algorithms for AMC: Head of the Lane (HoL), Head of the Lane with Propagation Effect (HoLPE) and All Feasible Sequences (AFS) and analyze their behavior assuming single-lane roads and vehicles that allow AMC to control their behavior, (ii) enhance AMC to provide solution for multiple-lane road scenarios and also accommodate mixed traffic (both AMC-controlled and human-driven vehicles) (iii) analyze application of AMC to other real-life scenarios like varying traffic densities (iv) demonstrate how DSRC-based wireless communication protocol can be leveraged for the development of AMC and (v) present a real-time approach towards designing AMC by integrating mode-change and real-time repository concepts for reducing the processing capacity requirements. Simulations and a prototype implementation on robotic vehicular platforms demonstrate the advantages of using our approach for constructing automated merge control systems.