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Heterogeneous Data Fusion Method to Estimate Travel Time Distributions in Congested Road Networks

機譯：擁擠路網(wǎng)中旅行時間分布的異構(gòu)數(shù)據(jù)融合方法

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Travel times in congested urban road networks are highly stochastic. Provision of travel time distribution information, including both mean and variance, can be very useful for travelers to make reliable path choice decisions to ensure higher probability of on-time arrival. To this end, a heterogeneous data fusion method is proposed to estimate travel time distributions by fusing heterogeneous data from point and interval detectors. In the proposed method, link travel time distributions are first estimated from point detector observations. The travel time distributions of links without point detectors are imputed based on their spatial correlations with links that have point detectors. The estimated link travel time distributions are then fused with path travel time distributions obtained from the interval detectors using Dempster-Shafer evidence theory. Based on fused path travel time distribution, an optimization technique is further introduced to update link travel time distributions and their spatial correlations. A case study was performed using real-world data from Hong Kong and showed that the proposed method obtained accurate and robust estimations of link and path travel time distributions in congested road networks.
機譯：擁擠的城市道路網(wǎng)中的旅行時間是高度隨機的。提供旅行時間分布信息（包括均值和方差）對于旅行者做出可靠的路徑選擇決策以確保準(zhǔn)時到達的更高概率非常有用。為此，提出了一種異構(gòu)數(shù)據(jù)融合方法，通過融合來自點和間隔檢測器的異構(gòu)數(shù)據(jù)來估計行進時間分布。在提出的方法中，首先從點檢測器的觀測值中估算出鏈路的行進時間分布。根據(jù)沒有點檢測器的鏈路與具有點檢測器的鏈路的空間相關(guān)性，推算它們的行進時間分布。然后，使用Dempster-Shafer證據(jù)理論將估計的鏈路行進時間分布與從間隔檢測器獲得的路徑行進時間分布融合?；谌诤下窂叫谐虝r間分布，進一步引入了一種優(yōu)化技術(shù)來更新鏈路行程時間分布及其空間相關(guān)性。使用來自香港的真實數(shù)據(jù)進行了案例研究，結(jié)果表明，該方法能夠在擁擠的道路網(wǎng)絡(luò)中獲得準(zhǔn)確而可靠的鏈路和路徑行進時間分布估計。

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