# Optimization of Cellular Automata Model for Moving Bottlenecks in Urban Roads
## 1 Introduction
[PERSON] [14] established a moving bottleneck model for heavy-duty trucks, which is based on the two-lane NaSch model and takes into account the differences in power performance and braking capabilities between trucks and cars. [PERSON] et al. [15] investigated the energy dissipation (ED) rate and particulate matter emission (PME) rate based on local measurements between the warning sign and the traffic bottleneck based on a two-lane NaSch cellular automaton model. [PERSON] [16] conducted a simulation study to investigate the impact of different vehicle lane-changing behaviors on the evolution process of traffic flow and their underlying mechanisms in specific scenarios, based on system methodology and system evolution theory. [PERSON] et al. [17] developed a novel cellular automata model for mixed traffic considering the limited visual distance and exploring the influence of visibility levels and CAV market penetration on traffic efficiency. These literature design acceleration, deceleration, and randomization are rules for different car-following scenes. [PERSON] et al. [18], based on the two-lane cellular automaton model with a safe distance, introduced a forced lane-changing rule to establish a highway vehicle congestion model that takes vehicle heterogeneity into account. [PERSON] et al. [19] established a cellular automata model comprising CAVs and two types of HVs, cooperative and defective HVs. A social dilemma is explored by quantifying the social efficiency deficit (SED). [PERSON] et al. [20] delved into the distinct characteristics of various vehicles within a mixed traffic environment, particularly focusing on HDVs and CAVs, and proposed a cellular automaton model for single-lane mixed traffic flow that accounts for the CAV platoon length. There is limited research on the moving bottlenecks in urban roads and the modeling of cellular automata for urban roads: [PERSON] et al. (2018) proposed Jam-absorption driving (JAD), which is a novel connected and automated vehicle-based (CAV-based) control strategy that uses either a single or several absorbing cars to clear moving jams. [PERSON] et al. (2018) proposed the recognition rules of moving bottleneck and explored the impact of L2 AVs on heterogeneous traffic flow involving heavy trucks and human-driven vehicles. [PERSON] et al. (2018) studied vehicle priority rules at signalized intersections and vehicle update rules at different times within a signal cycle and constructed a cellular automata model for a signalized intersection with a four-way stop to simulate and analyze the intersection's capacity. [PERSON] et al. (2018) examined the impact of vehicles executing a full turn or U-turn in a single-lane roundabout system using a cellular automaton model. Currently, research and applications of the moving bottleneck theory primarily focus on highways and expressways, while there is a notable lack of theoretical research on moving bottlenecks specific to urban roads. Traffic flow on highways and expressways exhibits continuous characteristics, whereas urban roads, due to the presence of signalized intersections, experience interrupted and complex traffic flow. This complexity makes the moving bottleneck phenomenon on urban roads more prominent, and its traffic impact mechanisms are more profound. The cellular automata model is one of the common methods to solve the problem of moving bottlenecks. However, there are currently several deficiencies in the application of cellular automaton models to moving bottlenecks, which include the following. The first issue is that most research focuses on continuous traffic flow on highways and expressways, with a lack of research on moving bottlenecks in intermittent traffic flow on urban roads that include intersections. The second issue is the inadequate application of cellular automaton models in modeling intermittent traffic flow on urban roads that include intersections.