Locating inefficient links in a large-scale transportation network
Locating inefficient links in a large-scale transportation network
复制标题
DOI：
10.1016/j.physa.2014.10.066
复制
发表时间：
2015-02
影响因子：
3.3
通讯作者：
Li Sun;Like Liu;Zhongzhi Xu;Yang Jie;Dong Wei;Pu Wang
中科院分区：
文献类型：
--
作者：
Li Sun;Like Liu;Zhongzhi Xu;Yang Jie;Dong Wei;Pu Wang
基于地理信息系统（GIS）数据和日常通勤出发地目的地（OD）矩阵，我们估计了旧金山路网的交通流分布，并研究了具有现实出行需求的大规模交通网络中的布雷斯悖论。我们测量了路段封闭时总行程时间ΔT的变化，发现| ΔT|如果ΔT<0或ΔT>0，则服从幂律分布。这意味着大多数道路对路网效率的影响可以忽略不计，而少数关键路段的故障将导致严重的出行延误，而关闭一些低效路段将大大降低出行成本。生成三个理论网络，我们发现异构分布的出行需求可能是观察到的幂律分布|的起源。 ΔT|。最后，使用遗传算法来查明道路网络中的低效链路簇。我们发现，关闭特定路群会进一步提高交通效率。
Based on data from geographical information system (GIS) and daily commuting origin destination (OD) matrices, we estimated the distribution of traffic flow in the San Francisco road network and studied Braess’s paradox in a large-scale transportation network with realistic travel demand. We measured the variation of total travel time Δ T when a road segment is closed, and found that| Δ T| follows a power-law distribution if Δ T< 0 or Δ T> 0. This implies that most roads have a negligible effect on the efficiency of the road network, while the failure of a few crucial links would result in severe travel delays, and closure of a few inefficient links would counter-intuitively reduce travel costs considerably. Generating three theoretical networks, we discovered that the heterogeneously distributed travel demand may be the origin of the observed power-law distributions of| Δ T|. Finally, a genetic algorithm was used to pinpoint inefficient link clusters in the road network. We found that closing specific road clusters would further improve the transportation efficiency.