Route planning is one of the most important and attractive topics in complex networks, geographical information science (GIS) and logistics. Travelers' route choice behaviors may affect the actual throughput of a transportation network. This study aims to analyze the influence of travelers' route choice behaviors on network traffic throughput. Two kinds of route choice behaviors, called continuous optimization behavior and hybrid optimization behavior, are defined. Based on this, two traffic scenarios are constructed to describe these behaviors and examine their effect on the network's actual traffic throughput. The application of our approach to urban street networks, Barabási-Albert scale-free network and Erdös-Rényi random network demonstrates that if all travelers choose optimal paths constraint with time from the start, network throughput is insensitive to the continuous optimization behavior but depends on the relationship between time and distance in the routing algorithm. Besides, network throughput is sensitive to the hybrid optimization behavior that the more travelers choose time-dependent optimal paths, the higher the throughput. The results indicate that the choice of initial paths and the time dependence of routing algorithms can directly affect the network's actual throughput which is enhanced >50 % when the time dependence parameter is >0.2 or the proportion of time-dependent shortest paths in initial paths is >0.2. Our findings provide supports for exploring efficient routing algorithms to enhance the throughput of urban street networks and other kinds of networks.

中文翻译：

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了解动态交通网络中路线选择行为对交通吞吐量的影响

路线规划是复杂网络、地理信息科学（GIS）和物流中最重要和最有吸引力的主题之一。出行者的路线选择行为可能会影响交通网络的实际吞吐量。本研究旨在分析出行者的路径选择行为对网络流量吞吐量的影响。定义了两种路径选择行为，称为连续优化行为和混合优化行为。在此基础上，构建了两个流量场景来描述这些行为并检查它们对网络实际流量吞吐量的影响。我们的方法在城市街道网络、Barabási-Albert 无标度网络和 Erdös-Rényi 随机网络中的应用表明，如果所有旅行者从一开始就选择最优路径约束，则网络吞吐量对连续优化行为不敏感，但取决于路由算法中时间和距离的关系。此外，网络吞吐量对混合优化行为敏感，选择时间相关的最优路径的旅行者越多，吞吐量就越高。结果表明，初始路径的选择和路由算法的时间依赖性可以直接影响网络的实际吞吐量，当时间依赖性参数>0.2或初始路径中时间依赖性最短路径的比例为时，网络的实际吞吐量提高>50%。 >0.2。我们的研究结果为探索有效的路由算法以提高城市街道网络和其他类型网络的吞吐量提供了支持。