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Can Historical Vehicle Probe Speeds from Private Sector Vendors be used to Flag Segments with Congestion on Interrupted-flow Arterial Highways?

机译:可以使用来自私营供应商的历史车辆探测速度来标记断流干线公路上拥堵的路段吗?

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Transportation agency operators and planners can now purchase real-time orhistorical vehicle speed data from private-sector vendors covering very large regionalhighway networks. The accuracy of these data products is fundamentally important;however, operators and planners view “accuracy” through different lenses, and whilefreeway data quality has been comprehensively studied, authoritative conclusions aboutsuitability of these sources for interrupted-flow arterial monitoring have not yet beenpublished.Thus, working from a planner’s perspective, the author has taken a macro-levelfirst-cut look at the question. For test highway segments where he already knew wheretypical daily bottlenecks were located, he calculated typical peak-period delay values –segment-by-segment – from default “historical” speed data donated by a private vendor.He juxtaposed these delay calculations against his lists of confirmed daily bottlenecks –the sources for these lists were periodic historical surveys using large sets of time-lapseaerial photography (TLAP), acquired during 24 mid-week morning and evening flyovers.He then refined calculation rules and experimented with various threshold delay values(above which segments would be flagged as “congested”), until he found the bestcorrelation between “congested” ratings generated by the two methods.Reviewing these lists, he found evidence that private-sector speed data oninterrupted-flow arterials may already be good enough to classify segments as“congested”, with varying degrees of severity and duration. After more rigorous researchto confirm, planners may have a more affordable way to calibrate computer models,screen large networks for likely bottlenecks, confirm where long-term degradation isoccurring, or prove the benefits of investments.
机译:运输代理运营商和计划人员现在可以实时购买或 来自私营供应商的历史车速数据涵盖了非常大的区域 公路网。这些数据产品的准确性至关重要。 但是,运营商和计划者通过不同的视角来查看“准确性”,而 对高速公路的数据质量进行了全面的研究,有关的权威结论 这些来源是否适合中断血流动脉监测 发表。 因此,从计划者的角度出发,作者采取了宏观层面 首先看问题。对于他已经知道在哪里的测试高速公路路段 找到了典型的每日瓶颈,他计算了典型的高峰期延迟值– 逐段细分-来自私有供应商捐赠的默认“历史”速度数据。 他将这些延迟计算与确认的每日瓶颈清单并列放置– 这些列表的来源是使用大量延时的定期历史调查 航空摄影(TLAP),在周中的24个上午和晚上的天桥上获取。 然后,他完善了计算规则,并尝试了各种阈值延迟值 (在哪些细分上方将被标记为“拥堵”),直到他找到最好的细分为止 两种方法产生的“拥挤”等级之间的相关性。 回顾这些清单,他发现有证据表明私营部门的速度数据 断流动脉可能已经足够好,可以将段分类为 “拥塞”,严重程度和持续时间各不相同。经过更严格的研究 确认一下,计划者可能有一种更实惠的方式来校准计算机模型, 筛选大型网络以查找可能的瓶颈,确认长期降级在哪里 发生或证明投资的好处。

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