کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
525117 868891 2014 16 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Using high-resolution event-based data for traffic modeling and control: An overview
ترجمه فارسی عنوان
با استفاده از داده های مبتنی بر رویداد با وضوح بالا برای مدل سازی و کنترل ترافیک: یک مرور کلی
کلمات کلیدی
داده های با وضوح بالا، داده های مبتنی بر رویداد، مدل سازی ترافیک، کنترل ترافیک، سیستم های سیگنال ترافیک
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر نرم افزارهای علوم کامپیوتر
چکیده انگلیسی


• Provide summary of the completed research using high-resolution event-based data.
• Demonstrate that that event data can be used in many areas of traffic operations.
• Offer perspectives on future research directions on high-resolution data.

Research on using high-resolution event-based data for traffic modeling and control is still at early stage. In this paper, we provide a comprehensive overview on what has been achieved and also think ahead on what can be achieved in the future. It is our opinion that using high-resolution event data, instead of conventional aggregate data, could bring significant improvements to current research and practices in traffic engineering. Event data records the times when a vehicle arrives at and departs from a vehicle detector. From that, individual vehicle’s on-detector-time and time gap between two consecutive vehicles can be derived. Such detailed information is of great importance for traffic modeling and control. As reviewed in this paper, current research has demonstrated that event data are extremely helpful in the fields of detector error diagnosis, vehicle classification, freeway travel time estimation, arterial performance measure, signal control optimization, traffic safety, traffic flow theory, and environmental studies. In addition, the cost of event data collection is low compared to other data collection techniques since event data can be directly collected from existing controller cabinet without any changes on the infrastructure, and can be continuously collected in 24/7 mode. This brings many research opportunities as suggested in the paper.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Transportation Research Part C: Emerging Technologies - Volume 42, May 2014, Pages 28–43
نویسندگان
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