Abstract

Accurate and fast path computation is essential for applications such as onboard navigation systems and traffic network routing. While a number of heuristic algorithms have been developed in the past few years for faster path queries, the accuracy of them are always far below satisfying. In this paper, we first develop an agglomerative graph partitioning method for generating high balanced traverse distance partitions, and we constitute a three-level graph model based on the graph partition scheme for structuring the urban road network. Then, we propose a new hierarchical path computation algorithm, which benefits from the hierarchical graph model and utilizes a region pruning strategy to significantly reduce the search space without compromising the accuracy. Finally, we present a detailed experimental evaluation on the real urban road network of New York City, and the experimental results demonstrate the effectiveness of the proposed approach to generate optimal fast paths and to facilitate real-time routing applications.

Highlights

  • In onboard navigation systems, a primary function is to find the route from the current location of a vehicle to a desired destination with a minimum expected travel time

  • We address the problem of efficient path computation on large urban road networks, where the delay time at road intersections is used for measuring the time taken on a route and can be treated as a kind of weight associated with the node

  • We have addressed the problem of efficient path computation on large urban road networks

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Summary

Introduction

A primary function is to find the route from the current location of a vehicle to a desired destination with a minimum expected travel time. Where the weight of any connect edge (i, j) is computed by the shortest path distance from node i to j within subgraph Gu. Definition 6.

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