Abstract:In recent years, Intelligent Transportation Systems (ITS) have developed a lot. More and more sensors and communication technologies (e.g., cloud computing) are being integrated into cars, which opens up a new design space for vehicular-based applications. In this paper, we present the Spatial Optimized Dynamic Path Planning algorithm. Our contributions are, firstly, to enhance the effective of loading mechanism for road maps by dividing the connected sub-net, and building a spatial index; and secondly, to enhance the effect of the dynamic path planning by optimizing the search direction. We use the real road network and real-time traffic flow data of Karamay city to simulate the effect of our algorithm. Experiments show that our Spatial Optimized Dynamic Path Planning algorithm can significantly reduce the time complexity, and is better suited for use as a real-time navigation system. The algorithm can achieve superior real-time performance and obtain the optimal solution in dynamic path planning.

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VLIW DSPs can largely enhance the Instruction-Level Parallelism, providing the capacity to meet the performance and energy efficiency requirement of sensor-based systems. However, the exploiting of VLIW DSPs in sensor-based domain has imposed a heavy challenge on software toolkit design. In this paper, we present our methods and experiences to develop system toolkit flows for a VLIW DSP, which is designed dedicated to sensor-based systems. Our system toolkit includes compiler, assembler, linker, debugger, and simulator. We have presented our experimental results in the compiler framework by incorporating several state-of-the-art optimization techniques for this VLIW DSP. The results indicate that our framework can largely enhance the performance and energy consumption against the code generated without it.

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