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Journal of ZheJiang University (Engineering Science)  2024, Vol. 58 Issue (12): 2575-2585    DOI: 10.3785/j.issn.1008-973X.2024.12.017
    
Operation simulation of urban expressway long-distance interweaving zones based on cellular automata
Yongheng CHEN1(),Suicheng YANG1,Shihao LI1,Shiyu KOU2
1. College of Transportation, Jilin University, Changchun 130022, China
2. School of Traffic and Transportation, Changsha University of Science and Technology, Changsha 410114, China
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Abstract  

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.



Key wordsurban traffic      microscopic simulation      urban expressway      long-distance interweaving zone      cellular automata     
Received: 07 November 2023      Published: 25 November 2024
CLC:  U 491  
Fund:  国家自然科学基金重点资助项目(52131202).
Cite this article:

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.

URL:

https://www.zjujournals.com/eng/10.3785/j.issn.1008-973X.2024.12.017     OR     https://www.zjujournals.com/eng/Y2024/V58/I12/2575


基于元胞自动机的城市快速路长距离交织区运行仿真

为了研究城市快速路长距离交织区对交通流运行特性的影响,建立多车道元胞自动机模型. 根据长距离交织区内不同位置的换道车辆,考虑其各自换道行为和换道需求强度,引入3种不同换道规则,并对长距离交织区进行分段设定. 基于动态安全间距、车流管理策略双重要素,构建不同管理策略下的多车道元胞模型. 仿真结果表明,长距离交织区内的强制性驶出换道行为容易引发局部拥堵,形成出入口瓶颈. 虽然双虚线型策略能够提供更多驶出车辆换道机会,但随着占有率的增加,这种优势逐渐减弱,相比之下,虚实线型策略更加合理. 虚实线型策略-主路优先机制保证主路驶出车辆换道路权,不可避免会牺牲部分辅路通行效率. 考虑到辅路的间断交通流特性,虚实线型策略1(先出后入)仍具备一定的实施价值.


关键词: 城市交通,  微观仿真,  城市快速路,  长距离交织区,  元胞自动机 
Fig.1 Schematic diagram of entrance and exit of typical expressway
Fig.2 Schematic diagram of long-distance weaving zones on expressway
Fig.3 Schematic diagram of management strategies for long-distance weaving zones on urban expressway
Fig.4 Schematic diagram of model scenario division
Fig.5 Schematic diagram of application of lane change rule
Fig.6 Real 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.1 Key parameters of simulation
Fig.7 Illustration of relationship between changeover frequency and occupancy rate
Fig.8 Illustration of relationship between average flow rate and occupancy rate
Fig.9 Comparison of primary and secondary road flows under different lane allocation strategies
Fig.10 Illustration 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.2 Spatiotemporal trajectory diagrams for different lane management strategies
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