|Table of Contents|

RLRM control method of single entrance ramp for highway(PDF)

《交通运输工程学报》[ISSN:1671-1637/CN:61-1369/U]

Issue:
2012年03期
Page:
101-107
Research Field:
交通信息工程及控制
Publishing date:

Info

Title:
RLRM control method of single entrance ramp for highway
Author(s):
WANG Xing-ju1; 2;  GAO Gui-feng1; 2;  MIYAGI T3
1. School of Traffic and Transportation, Shijiazhuang Tiedao University, Shijiazhuang 050043, Hebei, China; 2. Traffic Safety and Control Laboratory of Hebei Province, Shijiazhuang 050043, Hebei, China; 3. Graduate School of Information Sciences, Tohoku University, Sendai 9808578, Miyagi, Japan
Keywords:
traffic control;  ramp;  traffic flow simulation;  artificial intelligence;  reinforcement learning;  RLRM control
PACS:
U491.54
DOI:
-
Abstract:
In order to relieve freeway traffic congestion, reinforcement learning ramp metering(RLRM)control method for single entrance ramp of highway under the incomplete information was proposed based on the artificial intelligence theories of reinforcement learning. Average speeds, average densities, traffic outflows and travel times of numerical cases 1-6 were calculated, and the control effect of RLRM was compared with no control and fixed-time control. Simulation result shows that in case 1 with the lowest traffic inflow, the congestion relief rates of fixed-time control and RLRM control depending on travel time are -6.25% and -9.38% respectively, which indicates that the control effect is not significant. When the traffic inflow increases in case 3, the congestion relief rates of fixed-time control and RLRM control depending on travel time are -8.19% and 3.51% respectively, which indicates that the control has some effect, and RLRM control performs better than fixed-time control. In case 6 with the highest traffic inflow, the congestion relief rates of fixed-time control are 8.20%, 0.39%, 18.97% and 23.99% respectively, and those of RLRM control are 18.18%, 3.42%, 30.65% and 44.41% taking average speed, average density, traffic outflow and travel time as evaluating indexes respectively, which shows that RLRM control effect is more significant than fixed-time control. So the greater the traffic inflow is, the better the control effect of RLRM is. 5 tabs, 14 figs, 16 refs.

References:

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Last Update: 2012-06-30