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020 ▼a 9780438324756
035 ▼a (MiAaPQ)AAI10816581
035 ▼a (MiAaPQ)berkeley:17861
040 ▼a MiAaPQ ▼c MiAaPQ ▼d 248032
0820 ▼a 385
1001 ▼a Amini, Zahra.
24510 ▼a Data-driven Approaches for Robust Signal Plans in Urban Transportation Networks.
260 ▼a [S.l.] : ▼b University of California, Berkeley., ▼c 2018
260 1 ▼a Ann Arbor : ▼b ProQuest Dissertations & Theses, ▼c 2018
300 ▼a 68 p.
500 ▼a Source: Dissertation Abstracts International, Volume: 80-01(E), Section: A.
500 ▼a Adviser: Alexander Skabardonis.
5021 ▼a Thesis (Ph.D.)--University of California, Berkeley, 2018.
520 ▼a In urban transportation networks with signalized intersections a robust pre-timed signal plan is a practical alternative to adaptive control strategies, since it has less complexity and an easier implementation process. Recent advances in techno
520 ▼a Firstly, I discuss the development and testing of two algorithms for checking the quality of traffic data and for estimating performance measures at intersections. The first of these algorithms estimates the systematic error of the detector data
520 ▼a An offset optimization algorithm was developed to adjust signal offsets so as to improve the delay in the system. The performance of three real-world networks using the offsets obtained by the algorithm and those obtained from the widely used Sy
520 ▼a In conclusion, these four algorithms extract useful information from HR data about traffic at signalized intersections. Moreover, the algorithms assist in designing robust timing plans for satisfying demand fluctuations at signalized intersectio
590 ▼a School code: 0028.
650 4 ▼a Transportation.
690 ▼a 0709
71020 ▼a University of California, Berkeley. ▼b Civil and Environmental Engineering.
7730 ▼t Dissertation Abstracts International ▼g 80-01A(E).
773 ▼t Dissertation Abstract International
790 ▼a 0028
791 ▼a Ph.D.
792 ▼a 2018
793 ▼a English
85640 ▼u http://www.riss.kr/pdu/ddodLink.do?id=T14998268 ▼n KERIS
980 ▼a 201812 ▼f 2019
990 ▼a 관리자