Limits...
Optimization of the design of pre-signal system using improved cellular automaton.

Li Y, Li K, Tao S, Wan X, Chen K - Comput Intell Neurosci (2014)

Bottom Line: The simulation results of the proposed model indicate that the length of sorting area, traffic demand, signal timing, and lane allocation are the most important influence factors.The recommendations of these design parameters are demonstrated.The findings of this paper can be foundations for the design of pre-signal system and show promising improvement in traffic mobility.

View Article: PubMed Central - PubMed

Affiliation: Highway School, Chang'an University, The Middle Section of the Second Ring Road (South Part), Xi'an 710064, China.

ABSTRACT
The pre-signal system can improve the efficiency of intersection approach under rational design. One of the main obstacles in optimizing the design of pre-signal system is that driving behaviors in the sorting area cannot be well evaluated. The NaSch model was modified by considering slow probability, turning-deceleration rules, and lane changing rules. It was calibrated with field observed data to explore the interactions among design parameters. The simulation results of the proposed model indicate that the length of sorting area, traffic demand, signal timing, and lane allocation are the most important influence factors. The recommendations of these design parameters are demonstrated. The findings of this paper can be foundations for the design of pre-signal system and show promising improvement in traffic mobility.

Show MeSH
Lane changing logic.
© Copyright Policy - open-access
Related In: Results  -  Collection


getmorefigures.php?uid=PMC4236971&req=5

fig10: Lane changing logic.

Mentions: The lane changing object can either be acquiring higher speed or moving to specific lane for turning purpose. As such, the lane changing action can be classified into “target type” or “efficiency type.” The lane changing demand will increase as the vehicle moves forward. The probability will continually increase until the lane changing action finished, or the probability will be 1 after passing a specific point. Nevertheless, the probability of efficiency type lane changing behavior will not change at phase 2. Two parameters Pl1 and Pl2 are utilized to describe the lane changing probability of the two types of lane changing actions in cellular automaton. The lane changing logic is shown in Figure 10. A in Figure 10 means the current lane, and B represents the target lane.


Optimization of the design of pre-signal system using improved cellular automaton.

Li Y, Li K, Tao S, Wan X, Chen K - Comput Intell Neurosci (2014)

Lane changing logic.
© Copyright Policy - open-access
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC4236971&req=5

fig10: Lane changing logic.
Mentions: The lane changing object can either be acquiring higher speed or moving to specific lane for turning purpose. As such, the lane changing action can be classified into “target type” or “efficiency type.” The lane changing demand will increase as the vehicle moves forward. The probability will continually increase until the lane changing action finished, or the probability will be 1 after passing a specific point. Nevertheless, the probability of efficiency type lane changing behavior will not change at phase 2. Two parameters Pl1 and Pl2 are utilized to describe the lane changing probability of the two types of lane changing actions in cellular automaton. The lane changing logic is shown in Figure 10. A in Figure 10 means the current lane, and B represents the target lane.

Bottom Line: The simulation results of the proposed model indicate that the length of sorting area, traffic demand, signal timing, and lane allocation are the most important influence factors.The recommendations of these design parameters are demonstrated.The findings of this paper can be foundations for the design of pre-signal system and show promising improvement in traffic mobility.

View Article: PubMed Central - PubMed

Affiliation: Highway School, Chang'an University, The Middle Section of the Second Ring Road (South Part), Xi'an 710064, China.

ABSTRACT
The pre-signal system can improve the efficiency of intersection approach under rational design. One of the main obstacles in optimizing the design of pre-signal system is that driving behaviors in the sorting area cannot be well evaluated. The NaSch model was modified by considering slow probability, turning-deceleration rules, and lane changing rules. It was calibrated with field observed data to explore the interactions among design parameters. The simulation results of the proposed model indicate that the length of sorting area, traffic demand, signal timing, and lane allocation are the most important influence factors. The recommendations of these design parameters are demonstrated. The findings of this paper can be foundations for the design of pre-signal system and show promising improvement in traffic mobility.

Show MeSH