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In urban transportation network,traffic congestion is likely to occur at traffic bottlenecks.The signal timing at intersections together with static properties of left-turn and straight-through lanes of roads are two significant factors causing traffic bottlenecks. A discrete-time model of traffic bottleneck is hence developed to analyze these two factors,and a bottleneck indicator is introduced to estimate the comprehensive bottleneck degree of individual road in regional transportation networks universally,the identification approaches are presented to identify traffic bottlenecks,bottleneck-free roads,and bottleneck-prone roads. Based on above work,the optimization method applies ant colony algorithmwith effective green time as decision variables to find out an optimal coordinated signal timing plan for a regional network. In addition,a real experimental transportation network is chosen to verify the validation of bottleneck identification. The bottleneck identification approaches can explain the features of occurrence and dissipation of traffic congestion in a certain extent,and the bottleneck optimization method provides a newway to coordinate signal timing at intersections to mitigate traffic congestion.
In urban transportation network, traffic congestion is likely to occur at traffic bottlenecks. The signal timing at intersections together with static properties of left-turn and straight-through lanes of roads are two significant factors causing traffic bottlenecks. A discrete-time model of traffic bottleneck is therefore developed to analyze these two factors, and a bottleneck indicator is introduced to estimate the comprehensive bottleneck degree of individual road in regional transportation networks universally, the identification approaches are presented to identify traffic bottlenecks, bottleneck-free roads, and bottleneck-prone roads. Based on above work, the optimization method applies ant colony algorithm with effective green time as decision variables to find out an optimal coordinated signal timing plan for a regional network. In addition, a real experimental transportation network is chosen to verify the validation of bottleneck identification. The bottleneck identification approaches c an explain the features of occurrence and dissipation of traffic congestion in a certain extent, and the bottleneck optimization method provides a new way to coordinate signal timing at intersections to mitigate traffic congestion.