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Estimating traffic conditions from smart work zone systems
| 题名： | Estimating traffic conditions from smart work zone systems |
| 正文语种： | 英文 |
| 作者： | Yanning Li Juan C. Mart韓ez Mori; Daniel B. Work |
| 作者单位： | Department of Civil and Environmental Engineering University of Illinois at Urbana-Champaign, Urbana, IL, USA; Department of Civil and Environmental Engineering and Institute for Software Integrated Systems Vanderbilt University, Nashville, TN, USA |
| 关键词： | microsimulation; smart work zone; traffic estimation |
| 摘要： | This article evaluates the effectiveness of sensor network systems for work zone traffic estimation. The comparative analysis is performed on a work zone modeled in microsimulation and calibrated with field data from an Illinois work zone. Realistic error models are used to generate noisy measurements corresponding to Doppler radar sensors, remote traffic microwave sensors (RTMSs), and low energy radars. The velocity, queue length, and travel time are estimated with three algorithms based on (i) interpolation, (ii) spatio-temporal smoothing, and (iii) a flow model–based Kalman filter. A total of 396 sensor and algorithm configurations are evaluated and the accuracy of the resulting traffic estimates is compared to the true traffic state from the microsimulation. The nonlinear Kalman filter provides up to 30% error reduction over other velocity estimators when the RTMS sensor spacing exceeds two miles, and generally offers the best performance for queue and travel time estimation. |
| 出版年： | 2018 |
| 期刊名称： | Journal of Intelligent Transportation Systems Technology Planning and Operations |
| 卷： | 22 |
| 期： | 6 |
| 页码： | 490-502 |
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