Academic Journal

Area Occupancy-Based Adaptive Density Estimation for Mixed Road Traffic

التفاصيل البيبلوغرافية
العنوان: Area Occupancy-Based Adaptive Density Estimation for Mixed Road Traffic
المؤلفون: Reenu George, Lelitha Devi Vanajakshi, Shankar C. Subramanian
المصدر: IEEE Access, Vol 8, Pp 5502-5514 (2020)
بيانات النشر: IEEE, 2020.
سنة النشر: 2020
المجموعة: LCC:Electrical engineering. Electronics. Nuclear engineering
مصطلحات موضوعية: Adaptive Kalman filter, area occupancy, heterogeneous traffic, lane-less traffic, traffic density estimation, Electrical engineering. Electronics. Nuclear engineering, TK1-9971
الوصف: Managing congestion in mixed traffic conditions, characterized by heterogeneous and lane-less traffic, is a challenging task. Traditionally density, defined as the number of vehicles in a road stretch, is used to quantify congestion. However, direct measurement of density is difficult and hence is usually estimated from other variables. In this paper, a relationship is derived between traffic density and area occupancy, a variable that can incorporate heterogeneity and lane-less movement. Using the derived density-area occupancy relation, a non-continuum macroscopic single state linear time varying model was developed. Estimation of density was done by using the Kalman filtering technique and corroborated with simulated density. The need for dynamic estimation is motivated by evaluating the performance of two static estimation schemes in the presence of uncertainties. Performance was tested for different traffic scenarios such as congestion and non-recurrent traffic incidents. Further, to improve the estimation accuracy in scenarios involving transitions in traffic conditions, an adaptive estimator was developed. It was found that the adaptive estimator provided the best estimation accuracy.
نوع الوثيقة: article
وصف الملف: electronic resource
اللغة: English
تدمد: 2169-3536
Relation: https://ieeexplore.ieee.org/document/8946555/; https://doaj.org/toc/2169-3536
DOI: 10.1109/ACCESS.2019.2963273
URL الوصول: https://doaj.org/article/f2f73f2a5be342aa99e9be8fed1f0bbe
رقم الانضمام: edsdoj.f2f73f2a5be342aa99e9be8fed1f0bbe
قاعدة البيانات: Directory of Open Access Journals