1. College of Transportation, Jilin University, Changchun 130022, China 2. School of Traffic and Transportation, Changsha University of Science and Technology, Changsha 410114, China
A multi-lane cellular automata model was established to study the influence of long-distance interweaving zones on traffic flow in urban expressways. Considering the lane-changing behavior and the intensity of lane-changing needs of vehicles at different positions within the long-distance weaving section, three distinct lane-changing rules were introduced and the long-distance weaving area was segmented accordingly. Cellular models under different traffic management strategies were constructed, considering factors such as dynamic safety distances and traffic flow management. Simulation revealed that mandatory lane-changing behavior within long-distance weaving sections easily led to localized congestion, forming bottlenecks at entrances and exits. Although the double dashed-line strategy provided more opportunities for lane-changing vehicles to exit, this advantage gradually diminished with an increasing occupancy rate. In comparison, the dashed-solid line strategy appeared more reasonable. The dashed-solid line strategy with a main road priority, while maintaining the right of way for vehicles exiting from the main road, inevitably sacrificed some efficiency in the movement of vehicles on the secondary road. However, considering the intermittent traffic flow characteristics of the secondary road, the solid-dashed line strategy 1 (the main road exits first, then followed by the secondary road) still held certain practical value.
Yongheng CHEN,Suicheng YANG,Shihao LI,Shiyu KOU. Operation simulation of urban expressway long-distance interweaving zones based on cellular automata. Journal of ZheJiang University (Engineering Science), 2024, 58(12): 2575-2585.
Fig.1Schematic diagram of entrance and exit of typical expressway
Fig.2Schematic diagram of long-distance weaving zones on expressway
Fig.3Schematic diagram of management strategies for long-distance weaving zones on urban expressway
Fig.4Schematic diagram of model scenario division
Fig.5Schematic diagram of application of lane change rule
Fig.6Real scene image of research subject
参数
定义
数值
单位
参数
定义
数值
单位
$ l_{{\rm{lv}}} $
大型车辆所占元胞长度
3
$ {\rm{cell}} $
$\Delta t$
时间步长
1
${\rm{s}}$
$ l_{\rm{sv}} $
小型车辆所占元胞长度
1
${\rm{ cell}} $
$ a_{\rm{1}} $
舒适加速度
1
$ {\rm{cell}}/{{\rm{s}}^2} $
$ P_{\rm{outm}} $
快速路驶出车辆比例
0.4
—
$ a_2 $
舒适减速度
1
$ {\rm{cell}}/{{\rm{s}}^2} $
$P_{\rm{outs}}$
辅路驶出车辆比例
0.5
—
$ v_{\rm{s}} $
最小速度
略大于0
$ {\rm{cell}}/{\rm{s}} $
$P_{\rm{lvm}}$
快速路大型车辆比例
0
—
$ p_{\rm{s}} $
减速概率参数
0.1
—
$P_{\rm{lvs}}$
辅路大型车辆比例
0.15
—
$ p_{\rm{d}} $
线性插值最大值
1
—
$ v_{\max 1} $
快速路最大行驶速度
5
$ {\rm{cell}}/{\rm{s}} $
$ p_0 $
线性插值最小值
0.8
—
$ v_{\max 2} $
辅路最大行驶速度
3
$ {\rm{cell/s}} $
—
—
—
—
Tab.1Key parameters of simulation
Fig.7Illustration of relationship between changeover frequency and occupancy rate
Fig.8Illustration of relationship between average flow rate and occupancy rate
Fig.9Comparison of primary and secondary road flows under different lane allocation strategies
Fig.10Illustration of relationship between average speed and occupancy rate
车道
双虚线型策略
虚实线策略1
虚实线策略2
车道1
车道2
车道3
车道4
车道5
车道6
Tab.2Spatiotemporal trajectory diagrams for different lane management strategies
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