To satisfy the multiple priority requests from buses that arrive at different phases within a small time window, a multi-phase bus signal priority （MPBSP） strategy is developed. The proximity principle is brought fo...To satisfy the multiple priority requests from buses that arrive at different phases within a small time window, a multi-phase bus signal priority （MPBSP） strategy is developed. The proximity principle is brought forward to settle the conflicts among multiple priority requests and arrange the optimal priority sequence. To avoid over saturation of the intersection, a conditional MPBSP algorithm that adopts early green and green extension strategies is developed to give priority to the bus with the highest priority level when green time that each phase runs makes its saturation degree not larger than 0. 95. Finally, the algorithm is tested in the VISSIM environment and compared with the normal signal timing algorithm. Sensitive analysis of the number of priority phases, bus demand, and volume to capacity ratios are conducted to quantify their impacts on the benefits of the MPBSP. Results show that the MPBSP strategy can effectively reduce bus delays, and with the increase in the number of priority phases, the reduction range of bus delays also increases.展开更多
The steady-state or cyclic control problem for a simplified isolated traffic intersection is considered. The optimization problem for the green-red switching sequence is formulated with the help of a discrete-event ma...The steady-state or cyclic control problem for a simplified isolated traffic intersection is considered. The optimization problem for the green-red switching sequence is formulated with the help of a discrete-event max-plus model. Two steady-state control problems are formulated： optimal steady-state with green duration constraints, and optimal steady-state control with lost time. In the case when the criterion is a strictly increasing, linear function of the queue lengths, the steady-state control problems can be solved analytically. The structure of constrained optimal steady-state traffic control is revealed, and the effect of the lost time on the optimal solution is illustrated.展开更多
基金The National High Technology Research and Development Program of China(863 Program)(No.2011AA110304)the National Natural Science Foundation of China(No.50908100)Graduate Innovation Fund of Jilin University(No.20111044)
文摘To satisfy the multiple priority requests from buses that arrive at different phases within a small time window, a multi-phase bus signal priority （MPBSP） strategy is developed. The proximity principle is brought forward to settle the conflicts among multiple priority requests and arrange the optimal priority sequence. To avoid over saturation of the intersection, a conditional MPBSP algorithm that adopts early green and green extension strategies is developed to give priority to the bus with the highest priority level when green time that each phase runs makes its saturation degree not larger than 0. 95. Finally, the algorithm is tested in the VISSIM environment and compared with the normal signal timing algorithm. Sensitive analysis of the number of priority phases, bus demand, and volume to capacity ratios are conducted to quantify their impacts on the benefits of the MPBSP. Results show that the MPBSP strategy can effectively reduce bus delays, and with the increase in the number of priority phases, the reduction range of bus delays also increases.
文摘The steady-state or cyclic control problem for a simplified isolated traffic intersection is considered. The optimization problem for the green-red switching sequence is formulated with the help of a discrete-event max-plus model. Two steady-state control problems are formulated： optimal steady-state with green duration constraints, and optimal steady-state control with lost time. In the case when the criterion is a strictly increasing, linear function of the queue lengths, the steady-state control problems can be solved analytically. The structure of constrained optimal steady-state traffic control is revealed, and the effect of the lost time on the optimal solution is illustrated.
