Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: , an integrated approach combining offline precomputation of optimal candidate paths with online path retrieval and dynamic adaptation is proposed for a dynamic navigation system in a centralized system architecture. Based on a static traffic data file, a partially disjoint candidate path set is constructed prior to the trip using a heuristic link ight increment method. This method satisfies reasonable path constraints that meet the drivers' preferences, as ll as alternative path constraints, that limit the joint failure probability for candidate paths. The characteristics of the proposed algorithm are the following: 1) The response time for online navigation demand is nearly linear with network size and less dependent on system load; 2) the veracity of the pretrip route plan based on the static data file is improved by taking travel time reliability into account; and 3) system optimization can be approximated without sacrificing driver preferences. The algorithm is tested on randomly generated road networks, and the numerical results show the efficiency of the approach
['Yanyan Chen', 'M.G. Bell', 'Klaus Bogenberger']
I am writing a research paper on a idea Reliable Pretrip Multipath Planning and Dynamic Adaptation for a Centralized Road Navigation System
[{"from": "human", "value": "I am writing a research paper on a idea Reliable Pretrip Multipath Planning and Dynamic Adaptation for a Centralized Road Navigation System"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: , an integrated approach combining offline precomputation of optimal candidate paths with online path retrieval and dynamic adaptation is proposed for a dynamic navigation system in a centralized system architecture. Based on a static traffic data file, a partially disjoint candidate path set is constructed prior to the trip using a heuristic link ight increment method. This method satisfies reasonable path constraints that meet the drivers' preferences, as ll as alternative path constraints, that limit the joint failure probability for candidate paths. The characteristics of the proposed algorithm are the following: 1) The response time for online navigation demand is nearly linear with network size and less dependent on system load; 2) the veracity of the pretrip route plan based on the static data file is improved by taking travel time reliability into account; and 3) system optimization can be approximated without sacrificing driver preferences. The algorithm is tested on randomly generated road networks, and the numerical results show the efficiency of the approach"}]