Abstract
The urban traffic signal control system is complex, non-linear and non-equilibrium in real conditions. The existing methods could not satisfy the requirement of real-time and dynamic control. In order to solve these difficulties and challenges, this paper proposes a novel Multi-Intersection Model (MIM) based on Cellular Automata (CA) and a Multi-Intersection Signal Timing Plan Algorithm (MISTPA), which can reduce the delay time at each intersection and effectively alleviate the traffic pressure on each intersection in the urban traffic network. Our work is divided into several parts: (1) a multi-intersection model based on CA is defined to build the dynamic urban traffic network; (2) MISTPA is proposed, which truly reflects the real-time demand degree to green time of the traffic flow at each intersection. The MISTPA is composed Single Intersection Volume Algorithm (SIVA), Single-Lane Volume Algorithm (SLVA) and single intersection signal timing plan algorithm (SISTPA). Extensive experiments show that when the saturation is greater than 0.3, the MIM and the MISTPA achieve good performance, and can significantly reduce the vehicle delay time at each intersection. The average delay time of the traffic flow at each intersection can obviously be reduced. Finally, a practical case study demonstrates that the proposed model and the corresponding algorithm are correct and effective.
Highlights
Nowadays many cities are suffering from severe daily urban traffic congestion, which causes the enormous social and economic problems (Triantis et al 2011)
In order to solve the above problems of existing urban traffic signal control systems, this paper proposes a novel macroscopic Multi-Intersection Model (MIM) based on Cellular Automata (CA) and a Multi-Intersection Signal Timing Plan Algorithm (MISTPA)
This paper proposes a multi-intersection model based on CA and a novel multi-intersection signal timing plan algorithm to solve the problem
Summary
Nowadays many cities are suffering from severe daily urban traffic congestion, which causes the enormous social and economic problems (Triantis et al 2011). Christofa et al (2013) presents a person-based traffic responsive signal control system for transit signal priority on conflicting transit routes He proposed a mixed-integer nonlinear program is formulated, which minimizes the total person delay at an intersection while assigning priority to the transit vehicles based on their passenger occupancy. –– many optimization-based methods are based on off-line models, using historical data to optimize traffic signal within the urban road network. We propose a novel Multi-Intersection Model (MIM) and a Multi-Intersection Signal Timing Plan Algorithm (MISTPA), which can reduce the vehicle delay time at each intersection and effectively alleviate the traffic pressure at each intersection of the urban traffic network.
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