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Optimizing traffic network signals a...

Zhang, Li.

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Optimizing traffic network signals around railroad crossings.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Optimizing traffic network signals around railroad crossings./
作者:	Zhang, Li.
面頁冊數:	163 p.
附註:	Source: Dissertation Abstracts International, Volume: 61-06, Section: B, page: 3189.
Contained By:	Dissertation Abstracts International61-06B.
標題:	Engineering, Civil. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=9974751
ISBN:	9780599808645

Optimizing traffic network signals around railroad crossings.
Zhang, Li.

Optimizing traffic network signals around railroad crossings. - 163 p.

Source: Dissertation Abstracts International, Volume: 61-06, Section: B, page: 3189.

Thesis (Ph.D.)--Virginia Polytechnic Institute and State University, 2000.

The dissertation proposed an approach, named "S&barbelow;ignal O&barbelow;ptimization U&barbelow;nder R&barbelow;ail C&barbelow;rossing sA&barbelow;fety cO&barbelow;nstraints" (SOURCAO), to the traffic signal control near a highway rail grade crossing (HRGC). SOURCAO targets two objectives: HRGC safety improvement (a high priority national transportation goal) and highway traffic delay reduction (a common desire for virtually all of us). Communication and data availability from ITS and the next generation train control are assumed available in SOURCAO.

ISBN: 9780599808645Subjects--Topical Terms:

783781
Engineering, Civil.

Optimizing traffic network signals around railroad crossings.
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245 1 0 $a Optimizing traffic network signals around railroad crossings.
300 $a 163 p.
500 $a Source: Dissertation Abstracts International, Volume: 61-06, Section: B, page: 3189.
500 $a Chairman: Antoine G. Hobeika.
502 $a Thesis (Ph.D.)--Virginia Polytechnic Institute and State University, 2000.
520 $a The dissertation proposed an approach, named "S&barbelow;ignal O&barbelow;ptimization U&barbelow;nder R&barbelow;ail C&barbelow;rossing sA&barbelow;fety cO&barbelow;nstraints" (SOURCAO), to the traffic signal control near a highway rail grade crossing (HRGC). SOURCAO targets two objectives: HRGC safety improvement (a high priority national transportation goal) and highway traffic delay reduction (a common desire for virtually all of us). Communication and data availability from ITS and the next generation train control are assumed available in SOURCAO.
520 $a The first step in SOURCAO is to intelligently choose a proper preemption phase sequence to promote HRGC safety. An inference engine is designed in place of traditional traffic signal preemption calls to prevent the queue from backing onto HRGC. The potential hazard is dynamically examined as to whether any queuing vehicle stalls on railroad tracks. The inference engine chooses the appropriate phase sequence to eliminate the hazardous situation.
520 $a The second step in SOURCAO is to find the optimized phase length. The optimization process uses the network traffic delay (close to the control delay) at the intersections within HRGC vicinities as an objective function. The delay function is approximated and represented by multilayer perceptron neural network (off-line). After the function was trained and obtained, an optimization algorithm named Successive Quadratic Programming (SQP) searches the length of phases (on-line) by minimizing the delay function. The inference engine and proposed delay model in optimization take the on-line surveillance detector data and HRGC closure information as input.
520 $a By integrating artificial intelligence and optimization technologies, the independent simulation evaluation of SOURCAO by TSIS/CORSIM demonstrated that the objectives are reached. The average network delay for 20 runs of simulation evaluation is reduced over eight percent by a t-test while the safety of HRGC is promoted. The sensitivity tests demonstrate that SOURCAO works efficiently under light and heavy traffic conditions, as well as a wide range of HRGC closure times.
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790 1 0 $a Hobeika, Antoine G., $e advisor
790 $a 0247
791 $a Ph.D.
792 $a 2000
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