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Traffic signal synchronization in the saturated high-density grid road network.

Hu X, Lu J, Wang W, Zhirui Y - Comput Intell Neurosci (2015)

Bottom Line: Most existing traffic signal synchronization strategies do not perform well in the saturated high-density grid road network (HGRN).Using the strategy, the LGLR traffic signal synchronization model is developed, with the objective of minimizing the number of stops.Finally, the simulation is executed to analyze the performance of the model by comparing it to other models, and the superiority of the LGLR model is evident in terms of delay, number of stops, queue length, and overall performance in the saturated HGRN.

View Article: PubMed Central - PubMed

Affiliation: Jiangsu Key Laboratory of Urban ITS, Southeast University, Sipailou No. 2, Nanjing 210096, China ; Jiangsu Province Collaborative Innovation Center of Modern Urban Traffic Technologies, Sipailou No. 2, Nanjing 210096, China ; Beijing Key Laboratory for Cooperative Vehicle Infrastructure Systems and Safety Control, Sipailou No. 2, Nanjing 210096, China.

ABSTRACT
Most existing traffic signal synchronization strategies do not perform well in the saturated high-density grid road network (HGRN). Traffic congestion often occurs in the saturated HGRN, and the mobility of the network is difficult to restore. In order to alleviate traffic congestion and to improve traffic efficiency in the network, the study proposes a regional traffic signal synchronization strategy, named the long green and long red (LGLR) traffic signal synchronization strategy. The essence of the strategy is to control the formation and dissipation of queues and to maximize the efficiency of traffic flows at signalized intersections in the saturated HGRN. With this strategy, the same signal control timing plan is used at all signalized intersections in the HGRN, and the straight phase of the control timing plan has a long green time and a long red time. Therefore, continuous traffic flows can be maintained when vehicles travel, and traffic congestion can be alleviated when vehicles stop. Using the strategy, the LGLR traffic signal synchronization model is developed, with the objective of minimizing the number of stops. Finally, the simulation is executed to analyze the performance of the model by comparing it to other models, and the superiority of the LGLR model is evident in terms of delay, number of stops, queue length, and overall performance in the saturated HGRN.

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Related in: MedlinePlus

Comparison of average numbers of stops at the intersections.
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Related In: Results  -  Collection


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fig4: Comparison of average numbers of stops at the intersections.

Mentions: In terms of the number of stops in the intersections, the superiority of the LGLR traffic signal synchronization model is obvious. In three cases of 1200 veh/h, 1400 veh/h, and 1600 veh/h (see Figures 4(a), 4(b), and 4(c)), the average numbers of stops at all intersections are less than 0.6 in the LGLR model and are obviously less than those in other models.


Traffic signal synchronization in the saturated high-density grid road network.

Hu X, Lu J, Wang W, Zhirui Y - Comput Intell Neurosci (2015)

Comparison of average numbers of stops at the intersections.
© Copyright Policy - open-access
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC4309220&req=5

fig4: Comparison of average numbers of stops at the intersections.
Mentions: In terms of the number of stops in the intersections, the superiority of the LGLR traffic signal synchronization model is obvious. In three cases of 1200 veh/h, 1400 veh/h, and 1600 veh/h (see Figures 4(a), 4(b), and 4(c)), the average numbers of stops at all intersections are less than 0.6 in the LGLR model and are obviously less than those in other models.

Bottom Line: Most existing traffic signal synchronization strategies do not perform well in the saturated high-density grid road network (HGRN).Using the strategy, the LGLR traffic signal synchronization model is developed, with the objective of minimizing the number of stops.Finally, the simulation is executed to analyze the performance of the model by comparing it to other models, and the superiority of the LGLR model is evident in terms of delay, number of stops, queue length, and overall performance in the saturated HGRN.

View Article: PubMed Central - PubMed

Affiliation: Jiangsu Key Laboratory of Urban ITS, Southeast University, Sipailou No. 2, Nanjing 210096, China ; Jiangsu Province Collaborative Innovation Center of Modern Urban Traffic Technologies, Sipailou No. 2, Nanjing 210096, China ; Beijing Key Laboratory for Cooperative Vehicle Infrastructure Systems and Safety Control, Sipailou No. 2, Nanjing 210096, China.

ABSTRACT
Most existing traffic signal synchronization strategies do not perform well in the saturated high-density grid road network (HGRN). Traffic congestion often occurs in the saturated HGRN, and the mobility of the network is difficult to restore. In order to alleviate traffic congestion and to improve traffic efficiency in the network, the study proposes a regional traffic signal synchronization strategy, named the long green and long red (LGLR) traffic signal synchronization strategy. The essence of the strategy is to control the formation and dissipation of queues and to maximize the efficiency of traffic flows at signalized intersections in the saturated HGRN. With this strategy, the same signal control timing plan is used at all signalized intersections in the HGRN, and the straight phase of the control timing plan has a long green time and a long red time. Therefore, continuous traffic flows can be maintained when vehicles travel, and traffic congestion can be alleviated when vehicles stop. Using the strategy, the LGLR traffic signal synchronization model is developed, with the objective of minimizing the number of stops. Finally, the simulation is executed to analyze the performance of the model by comparing it to other models, and the superiority of the LGLR model is evident in terms of delay, number of stops, queue length, and overall performance in the saturated HGRN.

Show MeSH
Related in: MedlinePlus