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|Title:||An arterial speed estimation model fusing data from stationary and mobile sensors|
|Authors:||Cheu, R.L. |
Global Positioning Systems
|Source:||Cheu, R.L.,Lee, D.-H.,Xie, C. (2001). An arterial speed estimation model fusing data from stationary and mobile sensors. IEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC : 573-578. ScholarBank@NUS Repository.|
|Abstract:||This paper presents an arterial speed estimation model using data from two distinct sources: mobile probe vehicles and inductive loop detectors. The model consists of three modules: (1) probe vehicle module which measure arterial speed using vehicles equipped with differential global positioning system receivers; (2) loop detector modules which estimate link speed using loop detector data, incorporating traffic signal timing parameters; and (3) data fusion module, which uses a neural network to combine outputs from the above two modules to improve the speed estimation accuracy. The computational procedures of the three modules are presented. This paper presents a validation test of the model using a set of data generated from a calibrated simulation model. Our test results show that, the probe vehicle and loop detector modules are capable of making speed estimation with 2-RMSE of less than 3.20 km/h. Using a neural network to fuse the estimates from the two sources reduces the 2-RMSE to less than 1.32 km/h.|
|Source Title:||IEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC|
|Appears in Collections:||Staff Publications|
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