Cellular Automaton Traffic Model Research Articles

A new microscopic traffic-flow model based on the spatiotemporal continuous system concept considering nonlinear human response

A brand-new traffic model is introduced to precisely simulate the individual movement of vehicles, departing from the traditional macroscopic perspective (Eulerian scope or fluid dynamics concept) to adopt a microscopic approach (Lagrangian scope). This model is built on the first principle of Newton’s kinetic equation, explicitly incorporating nonlinear relations to represent human responses to a physical stimulus (observed information), such as the velocity gap between one’s own vehicle and a certain targeted one or the gap to a preceding vehicle, unlike the conventional car-following concept. The model posits that a driver’s recognition occurs intermittently rather than continuously, following specific probabilistic distributions of which the formulation is physically justified. Overall, the model can be described as a spatiotemporally continuous formulation unlike cellular automaton (CA) traffic models, crucial for capturing traffic dynamics at the micro and macro levels. The model is validated using a real traffic-flow dataset from a highway, and the results of the conventional CA traffic model are compared with those of the present one” along with a note for authorial verification. Animated simulations confirm that the present model can reproduce realistic flow dynamics characterized by smoother acceleration and deceleration compared to the conventional CA traffic model. The complete simulation source code for replicating the model is made publicly available.

Characterizing Heterogeneous Traffic Flow at a Slope Bottleneck via Cellular Automaton Model

This paper considers the unique attributes of autonomous vehicles, the characteristics of expressways’ minor actual slope grade, and the speed update integer requirements of discrete cellular automata (CA). The continuous deceleration efficiency of the uphill is discretized by introducing variable parameters connected to the vehicle position and gradient, and the hybrid traffic flow CA model suitable for slope bottlenecks based on the principle of the safety distance is further improved. The simulation results show that the improved model can simulate the unique traffic flow phenomenon caused by the change in slope conditions. There is a critical mutation in the traffic flow phase on the slope road section. Secondly, according to the different main factors influencing traffic flow, free flow, terrain jams, and homogeneous congested flow coexist on the slope section. The traffic flow in the crowded terrain area is significantly negatively correlated with the length and longitudinal gradient of the slope, and increasing the longitudinal angle of the hill will extend the congested terrain area. In addition, the influence of the change in slope conditions on mixed traffic flow has a critical longitudinal gradient of 3% and a fixed critical slope length. In non-free flow areas, autonomous vehicles can significantly alleviate traffic congestion on upslopes.

A cellular automaton traffic model by mechanical restriction and the slow-to-start rules in the framework of Kerner’s three-phase traffic theory

Most of the conventional cellular automaton (CA) traffic flow models have two shortcomings: unlimited deceleration capabilities and incapability of reproducing the synchronized flow in the three-phase traffic flow theory. Based on an original deceleration CA model that emphasizes limited mechanical capabilities and human overreaction as the origin of congested traffic states, this paper proposes a new deceleration CA model where the slow-to-start rules are incorporated. For periodic boundary conditions, one also finds that the present model can reproduce well the three different phases of traffic flow (free flow, synchronized traffic flow, wide moving jam) as well as two first-order phase transitions (the transitions from free flow to synchronized flow and from synchronized flow to wide moving jam) among them. Compared to the original deceleration CA model, one notes that the phase transition from the synchronized flow to wide moving jam becomes distinguishable. Furthermore, the present model can reliably reproduce most empirical findings including synchronized flow with different slopes, the so-called pinch effect, and the time-headway distribution of free flow and so on. Importantly, the synchronized flow with different slopes is supported by spatiotemporal diagrams and the statistical distribution of velocity and so on. For open boundary conditions, the present model can reproduce the spatiotemporal diagrams of well-known five patterns including moving synchronized flow pattern, localized synchronized flow pattern, widening synchronized flow pattern, dissolving general pattern and general pattern.

Analyzing the effect of fixed and moving bottlenecks on traffic flow and car accidents in a two-lane cellular automaton model

Traffic bottleneck is considered as one of the major causes of the disturbance in traffic flow. The understanding the dynamics between vehicles and bottlenecks is crucial for enhancing traffic flow and ensuring road safety. This research examines a two-lane traffic cellular automaton model to understand the effects of static (e.g., lane reductions) and dynamic (e.g., slow-moving vehicles) bottlenecks on traffic flow and road safety. We found that at low vehicle densities, slow vehicles gravitate towards the open lane, while faster vehicles switch lanes to overtake, returning to their original lane post-bottleneck. At high densities, traffic flow near static bottlenecks ceases, independent of bottleneck length. Safety analysis shows that extended static bottlenecks reduce rear-end collision risk due to fewer lane changes and increased vehicle stationarity. At maximum density, gridlock nullifies the chance of such collisions. Our findings provide actionable insights for traffic planning focused on bottleneck management to improve road safety.

Analysis of construction area’s impacts on traffic flow: A case study on Hangzhou Bay Bridge in China

Modeling impacts of the construction area on the mixed traffic flow would be a challenge. It needs to figure out the traffic regulations near the construction area, which vehicles must comply with. Meanwhile it requires depicting the different driving behaviors of cars and trucks when they run into the construction area. To deal with these problems, we present a three-lane cellular automaton traffic model with a construction area, taking the traffic flow on Hangzhou Bay Bridge with the third lane closed as a case study. The different longitudinal position updating rules and the lateral lane-changing rules are proposed for cars and trucks respectively, which are driven by aggressive drivers and cautious drivers. The simulation results show that the traffic flow will reach the maximum value when the length of the work zone, i.e., the main part of the construction area, is appropriate. On the other hand, the construction area has a great negative impact on the traffic flow when the injection rate is high, and cause the serious traffic congestions. In order to optimize the traffic flow, the variation tendency of the total traffic flow and the delay time with the increasing length of the work zone and the injection rate are analyzed. And the recommended values of the work zone’s length under different injection rates are obtained. In addition, according to the variation trend of the merging rate with the increasing length of the merging area and the injection rate, the recommended values of the merging area’s length under different injection rate are obtained. The results are meaningful and expected to be applied in the traffic management during the period of highway construction.

Modeling impacts of the tunnel section on the mixed traffic flow: A case study of Jiaodong’ao Tunnel in China

Modeling impacts of the tunnel section on the mixed traffic flow would be a challenge. It needs to figure out the traffic regulations of the tunnel section that vehicles must comply with. Also it requires depicting the different driving behaviors of cars and trucks when they run into the tunnel. To deal with these problems, we propose a two-lane cellular automaton (CA) traffic model with a tunnel section based on the single-lane CA model proposed by Guzmán (LAI-E model). The asymmetric lane-changing rules with right-lane preference are adopted for trucks, and the symmetrical lane-changing rules are adopted for cars. Especially, the impact of trucks on cars’ driving pattern is taken into account. The drivers’ individual character difference, i.e., cautious and radical, are also considered. The results indicate that the time series of traffic flow, vehicles’ speed in different tunnel sections and trucks’ proportions obtained from the numerical simulation are in good agreement with those obtained from the measured data. The phenomena of the speed fluctuation at the entrance and the exit of the tunnel are reproduced. Besides, the driving pattern of cars’ keeping away from trucks is captured from the spatial–temporal diagrams, and the unbalanced utilization of two lanes, i.e., large usage in the left lane and small usage in the right lane, is revealed. The further simulation indicates that the unbalanced utilization of two lanes will be improved if the trucks’ blocking influence could be neglected. The results will provide a theoretical reference for the optimization of traffic flow in the highway tunnel sections.

An Improved Cellular Automaton Traffic Model Based on STCA Model Considering Variable Direction Lanes in I-VICS

In this paper, we propose an improved cellular automaton model for the traffic operation characteristics of variable direction lanes in an Intelligent Vehicle Infrastructure Cooperation System (I-VICS). According to the proposed flow of variable oriented lane operation in the I-VICS environment, the idea for the improved model has been determined. According to an analysis of different signal states, an improved STCA model is proposed, in combination with the speed induction method of I-VICS and the variable direction lane switching strategy. In the assumed regular simulation environment, the STCA and STCA-V models are simulated under different vehicular densities. The results indicated that traffic parameters such as traffic flow and average speed of the variable direction lanes in the I-VICS environment are better than those in the conventional environment according to the operating rules of the proposed model. Moreover, lane utilization increased for the same density.

Modelling and evaluation of a novel intermittent bus lane with time-division multiplexing

As a promising bus priority technique, intermittent bus lanes (IBLs) can effectively utilise the idle road resources in dedicated bus lanes (DBLs). Existing IBL systems still have certain limitations in practice, so the authors propose a novel intermittent bus lane with time-division multiplexing (BLTDM) for lane sharing and bus prioritisation. To explore the benefits and applicable traffic conditions of BLTDM operation, cellular automaton traffic models are constructed with different bus priority strategies and a simulation analysis is conducted. In particular, a new model of fuzzy logic lane-change probability is developed. Comparing the traffic flow characteristics with DBL, IBL and BLTDM in the three cases, the operational effects and the applicable traffic conditions for each strategy are quantitatively evaluated. Results show that IBL and BLTDM are beneficial just within the certain traffic conditions. BLTDM has a wider applicable range of input car flow and a stronger adaptability to the bus operation frequency, and can balance the stability of traffic flow, in the sense that the BLTDM strategy has great advantages and provides a new direction for the development of intermittent bus lanes.

Study on fuel consumption in the Kerner–Klenov–Wolf three-phase cellular automaton traffic flow model

Based on the Kerner–Klenov–Wolf three-phase cellular automaton traffic model, we study fuel consumption of vehicles on one-way lanes under open boundary conditions. The difference in the appearance of the phase diagram is found to be related to the length of the vehicle. Phase diagram is divided into free flow, congested phase I, congested phase II and maximum current (MC) phase for the 15 cells of vehicle length and lacks the maximum current (MC) phase for 5 cells of vehicle length. By analysis of the cross-correlation between local density and flow and the spatial–temporal patterns, synchronized flow (SF) on the area upstream of the road is determined. The numerical computations for fuel consumption on free flow, congested phase I, synchronous flow (SF) and maximum current (MC) are carried out. The results indicate that the injection rate and the removal rate have great impacts on fuel consumption in the open boundary traffic system. The maximum current (MC) phase and congested phase I maximize fuel consumption. The fuel consumption of synchronized flow (SF) exceeds that of the free flow, but lower than that of the congested phase I and the maximum current (MC).

Modeling traffic flow mixed with automated vehicles considering drivers ’ character difference

Modeling impact of drivers’ character difference on the traffic flow mixed with automated vehicles would be a challenge. It needs to understand the character property of drivers who steer ACC or CACC vehicles, and figure out the different behaviors due to character difference during the formation and disengagement of CACC strings when the manually driven vehicles are mixed. Also it requires depicting the different behaviors of manually driven vehicles due to character difference under the influence of CACC cooperative strategy. To deal with these problems, we propose a four-lane cellular automaton traffic model to simulate the interaction between automated vehicles and manually driven vehicles, in which the drivers who control automated vehicles are classified into adaptive and inadaptive drivers, and the drivers of manual vehicles are classified into aggressive and cautious drivers. Numerical results show that increasing of CACC penetration could effectively alleviate the traffic congestion and improve the traffic capacity. And the cooperative driving strategy of CACC would work better and the traffic capacity enhances with the increasing of the adaptive drivers. On the other hand, with the increasing of the aggressive drivers, the vehicle clusters and stop-and-go waves occurred more frequently, thus the traffic capacity decreases. It indicates that the mixed traffic flow has different properties in terms of capacity and traffic congestion when different components of drivers’ character are involved.

基于交通流元胞自动机模型的小区开放问题研究

基于交通流元胞自动机模型的小区开放问题研究

Exact solution of the facilitated totally asymmetric simple exclusion process

We obtain the exact solution of the facilitated totally asymmetric simple exclusion process (F-TASEP) in 1D. The model is closely related to the conserved lattice gas (CLG) model and to some cellular automaton traffic models. In the F-TASEP a particle at site j in jumps, at integer times, to site j + 1, provided site j − 1 is occupied and site j + 1 is empty. When started with a Bernoulli product measure at density , the system approaches a stationary state. This non-equilibrium steady state (NESS) has phase transitions at and . The different density regimes , , and exhibit many surprising properties; for example, the pair correlation satisfies, for all , , with k = 2 when , k = 6 when , and k = 3 when . The quantity , where is the variance in the number of particles in an interval of length L, jumps discontinuously from to 0 when and when .

Data Anomaly Detection for Internet of Vehicles Based on Traffic Cellular Automata and Driving Style.

The data validity of safe driving in the Internet of Vehicles (IoV) is the basis of improving the safety of vehicles. Different from a traditional information systems, the data anomaly analysis of vehicle safety driving faces the diversity of data anomaly and the randomness and subjectivity of the driver’s driving behavior. How to combine the characteristics of the IOV data with the driving style analysis to provide effective real-time anomaly data detection has become an important issue in the IOV applications. This paper aims at the critical safety data analysis, considering the large computing cost generated by the real-time anomaly detection of all data in the data package. We preprocess it through the traffic cellular automata model which is built to achieve the ideal abnormal detection effect with limited computing resources. On the basis of this model, the Anomaly Detection based on Driving style (ADD) algorithm is proposed to realize real-time and online detection of anomaly data related to safe driving. Firstly, this paper designs the driving coefficient and proposes a driving style quantization model to represent the driving style of the driver. Then, based on driving style quantization model and vehicle driving state information, a data anomaly detection algorithm is developed by using Gaussian mixture model (GMM). Finally, combining with the application scenarios of multi-vehicle collaboration in the Internet of Vehicles, this paper uses real data sets and simulation data sets to analyze the effectiveness of the proposed ADD algorithm.

Analysis of traffic flow with micro-cars with respect to safety and environmental impact

This study analyzes the characteristics of traffic flow in the presence of micro-cars in a vehicle mix. A two-lane multi-cell traffic cellular automaton (TCA) model is formulated to simulate mixed traffic flow comprising conventional passenger cars and micro-cars. The segments of an urban highway and arterial road, both with two lanes and measuring 700 m in length, are simulated; the latter includes an intersection delay with a signal cycle at the midpoint. Traffic flows with different proportions of micro-cars are investigated in the simulation. Four aspects of traffic conditions are calculated: the number of lane changes, the number of decelerations, the coefficient of speed variation (which may be indicative of safety performance), and the HC, CO, and NOx emissions (as a measure of environmental impact). The simulation results suggest that mixed flow with micro-cars leads to higher frequencies of lane-changing on both highways and arterial roads, although the incremental change on the latter is smaller. With the introduction of micro-cars on the highway, the frequency of decelerations increases in free flow and decreases in congested flow; however, on the arterial road, it decreases the frequency of decelerations and has an insignificant impact on free flow. The introduction of micro-cars has a similar impact on the coefficient of speed variation. Under free flow conditions on highways, the introduction of micro-cars has a negative influence on the three aforementioned parameters related to safety. However, for free flow on arterial roads or congested flow on highways and arterial roads, the results are inconclusive because the effect of micro-cars is contradictory in terms of the three parameters. Vehicle emissions, such as HC, CO, and NOx, increase during free flow on highways, but are always lower on arterial roads.

An improved two-lane cellular automaton traffic model based on BL-STCA model considering the dynamic lane-changing probability

Based on the brake light (BL) model, Knospe et al. proposed a symmetric two-lane cellular automaton (BL-STCA) model, which could reproduce various empirically observed two-lane phenomena. In real traffic, the effect of brake light on the lane-changing behavior cannot be ignored. Therefore, BL-STCA model is interesting. However, there are two problems with BL-STCA model, too strong exchange of vehicles between lanes and unreasonable phenomenon in some special scenarios, such as a broken-down vehicle parked on one lane due to traffic accident. In order to solve the problems, we introduce the dynamic lane-changing probability and proposed an improved BL-STCA model with modification of lane-changing rules. The simulation results show as below. (1) Our new model effectively solves the above two problems of BL-STCA model. In addition, the lane-changing frequency is consistent with the real traffic data, which means the validity of our new model. (2) Compared with single-lane scenario, the lane-changing behaviors in two-lane scenario can effectively suppress the emergence of wide moving jam. (3) From the microcosmic level, the lane-changing behaviors can well explain the moving blank phenomenon within wide moving jam.

Expressway traffic flow model study based on different traffic rules

In this paper, two cellular automata traffic models are proposed to simulate the operation of expressway. The results show that the flow rate and the average velocity are generally equal in the same density which is different among the lanes. The analysis of lane changing times and the velocity total deviation show some characteristics which are difficult to be explained by the phase transitions under the fundamental diagram theory. Therefore, the concept of lane changing probability is introduced, and it is concluded that the speed-limit rule can reduce the motivation of lane changing effectively.

Bus stop setting problem based on cellular automaton traffic model

Nowadays, traffic jam becomes a big problem for cities with large population. Bus is a main component of public transportation, and then the design of bus stop position and size should improve efficiency of public transportation. This research focuses on a certain bus stop between two intersections. The target of this research is to work out a best plan for the bus stop type, position and size. To solve the problem of bus stop setting, a mixed traffic flow model including buses, cars and trucks is established by CA (cellular automaton) model. And then the best bus stop settings plans can be determined through the simulation with a traffic simulator.

Cellular automaton traffic model considering driver’s reaction to velocity and headway distance with variable possibility of randomization

Because of its simplicity and flexibility, cellular automaton model is widely used to simulate traffic flows. Based upon the NS (Nagel and Schreckenberg) Model, the paper proposes a cellular automaton model to simulate drivers’ reaction to velocity and headway distance in single lane traffic flow by modification of deceleration and randomization of the rules. Analysis of average velocity is performed to study the state and stability of traffic flow in various situations. For low densities, traffic is in free flow state, with average velocity fluctuating around the mathematical expectation stably. With the increasing of density, traffic becomes unstable and goes into jammed flow state. The behaviours of the model are very similar to those of the real traffic flows observed in the field. It is potential that the model can be used to predict traffic state for the engineering practice of traffic control and management.

Study on the influence of bus front-end intrusion-free distance to the bus moving characteristics

Buses are usually loaded with many passengers and cannot start and turn around flexibly while cars are light and maneuverable. Sometimes, cars may cut in front of a bus as long as the gap is available, and buses have to reduce their speed, which affects the traveling speed and smoothness of buses. In order to improve the bus riding quality, this paper proposes a model of setting front-end intrusion-free distance, in which social vehicles are not allowed to cut in. If buses accelerate, the distance from front vehicles can be smaller than the intrusion-free distance. With open boundary conditions, social vehicles and bus departure mechanism were reenacted, and a two-lane mixed traffic cellular automaton model based on different lane changing conditions and whistle effect was established respectively. Simulation results demonstrated that the model reproduced the operation rules of mixed flow on driveways, with good performance in describing lane changing rules. According to numerical simulation, the suggested vehicle changing lane regulation not only accelerated buses, but also increased the average speed of overall passengers, with improved smoothness of road vehicles, and reduced lane changing times and vehicle acceleration and deceleration frequency. It was demonstrated that the front-end intrusion-free distance for public buses can optimize bus operation efficiency.

Effect of directional migration on Lotka-Volterra system with desert

Migration is observed across many species. Several authors have studied ecological migration by applying cellular automaton (CA). In this paper, we present a directional migration model with desert on a one-dimensional lattice where a traffic CA model and a lattice Lotka-Volterra system are connected. Here predators correspond to locomotive animals while prey is immobile plants. Predators migrate between deserts and fertile lands repeatedly. Computer simulations reveal the two types of phase transition: coexistence of both species and prey dominance, which is caused by both benefit and cost of migration. In the coexistence phase, the steady-state density of predators usually increases by migration as long as the desert size is small and their mortality rate is low. In contrast, the prey density increases, even if the desert size becomes large. Such a paradox comes from the indirect effect: predators go extinct by the increase of desert size, so that the plant density can increase. Moreover, we find several self-organized spatial patterns: 1) predators form a stripe pattern; namely swarms. 2) The velocity of predators is high on deserts, but very low on fertile land. 3) Predators give birth only on fertile lands.