大数据驱动下的新一代高速公路 智慧诱导技术

为了解决高速公路出行路径选择问题,基于图论模糊算法,提出了大数据下的智慧诱导技术。首先对高速路网在路径诱导的实时性、线路规划的精准度和算法的适用性方面进行优化;其次通过利用贪心算法和整体寻优算法,对经典路径诱导算法进行研究和比选;最后针对高速路网提出基于大数据动态规划的路径诱导技术,采用大数据、内存计算、图计算和AI结合的方式来实现大数据的动态实时路径诱导。研究结果表明,智慧诱导技术可主动为有不同诉求目标的出行者提供实时最优的方案选择,解决复杂路网下动态路径的合理诱导问题。所提出的方法可实现大数据驱动下的智慧诱导,对进一步提升公路智能化和精细化管理水平具有借鉴意义。

New generation intelligence induction technology for expressway driven by big data

In order to solve the problem of freeway travel route selection, based on graph theory fuzzy algorithm, an intelligence induction technology driven by big data is proposed. Firstly, aiming at the real-time performance of route guidance, the accuracy of route planning and the applicability of the algorithm are improved. Secondly, the classical route guidance algorithms are researched and compared by using the greedy algorithm and the overall optimization algorithm; At last, a new route guidance technology based on large data dynamic programming is proposed for high-speed road network. The technology combines large data, memory computing, graph computing and AI to realize dynamic real-time route guidance based on large data. The result shows that the intelligence induction technology actively provides real-time optimal scheme selection for travelers with different demands, and solves the problem of reasonable route guidance under complex road network. The research method can be used for reference to realize the intelligent induction driven by big data and to further improve the level of highway intelligent and fine management.