Scipediacontent: Scipediacontent moved page Draft Content 294003308 to Wang Zhou 2019a

2021-02-12T13:41:41Z

Scipediacontent moved page Draft Content 294003308 to Wang Zhou 2019a

Scipediacontent: Created page with " == Abstract == Aiming to provide an approach for finding energy-efficient routes in dynamic and stochastic transportation networks for electric vehicles, this paper addresse..."

2021-02-12T13:41:38Z

Created page with " == Abstract == Aiming to provide an approach for finding energy-efficient routes in dynamic and stochastic transportation networks for electric vehicles, this paper addresse..."

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== Abstract ==

Aiming to provide an approach for finding energy-efficient routes in dynamic and stochastic transportation networks for electric vehicles, this paper addresses the route planning problem in dynamic transportation network where the link travel times are assumed to be random variables to minimize total energy consumption and travel time. The changeable signals are introduced to establish state-space-time network to describe the realistic dynamic traffic network and also used to adjust the travel time according to the signal information (signal cycle, green time, and red time). By adjusting the travel time, the electric vehicle can achieve a nonstop driving mode during the traveling. Further, the nonstop driving mode could avoid frequent acceleration and deceleration at the signal intersections so as to reduce the energy consumption. Therefore, the dynamically adjusted travel time can save the energy and eliminate the waiting time. A multiobjective 0-1 integer programming model is formulated to find the optimal routes. Two methods are presented to transform the multiobjective optimization problem into a single objective problem. To verify the validity of the model, a specific simulation is conducted on a test network. The results indicate that the shortest travel time and the energy consumption of the planning route can be significantly reduced, demonstrating the effectiveness of the proposed approaches.

Document type: Article

== Full document ==
<pdf>Media:Draft_Content_294003308-beopen391-4849-document.pdf</pdf>

== Original document ==

The different versions of the original document can be found in:

* [http://downloads.hindawi.com/journals/jat/2019/2607402.pdf http://downloads.hindawi.com/journals/jat/2019/2607402.pdf] under the license https://creativecommons.org/licenses/by

* [http://dx.doi.org/10.1155/2019/2607402 http://dx.doi.org/10.1155/2019/2607402] under the license cc-by

* [http://downloads.hindawi.com/journals/jat/2019/2607402.pdf http://downloads.hindawi.com/journals/jat/2019/2607402.pdf],
: [http://downloads.hindawi.com/journals/jat/2019/2607402.xml http://downloads.hindawi.com/journals/jat/2019/2607402.xml],
: [http://dx.doi.org/10.1155/2019/2607402 http://dx.doi.org/10.1155/2019/2607402] under the license http://creativecommons.org/licenses/by/4.0

* [http://dx.doi.org/10.1155/2019/2607402 http://dx.doi.org/10.1155/2019/2607402],
: [https://doaj.org/toc/0197-6729 https://doaj.org/toc/0197-6729],
: [https://doaj.org/toc/2042-3195 https://doaj.org/toc/2042-3195] under the license http://creativecommons.org/licenses/by/4.0/

* [https://www.hindawi.com/journals/jat/2019/2607402 https://www.hindawi.com/journals/jat/2019/2607402],
: [http://downloads.hindawi.com/journals/jat/2019/2607402.pdf http://downloads.hindawi.com/journals/jat/2019/2607402.pdf],
: [https://academic.microsoft.com/#/detail/2970777207 https://academic.microsoft.com/#/detail/2970777207]

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Wang Zhou 2019a - Revision history

Scipediacontent: Scipediacontent moved page Draft Content 294003308 to Wang Zhou 2019a

Scipediacontent: Created page with " == Abstract == Aiming to provide an approach for finding energy-efficient routes in dynamic and stochastic transportation networks for electric vehicles, this paper addresse..."