Nagel-Schreckenberg Cellular Automata Model Research Articles

Spatial and temporal memory effects in the Nagel-Schreckenberg model for crowdsourced traffic property determination.

We investigate the spatial and temporal memory effects of traffic density and velocity in the Nagel-Schreckenberg cellular automaton model. We show that the two-point correlation function of vehicle occupancy provides access to spatial memory effects, such as headway, and the velocity autocovariance function to temporal memory effects such as traffic relaxation time and traffic compressibility. We develop stochasticity-density plots that permit determination of traffic density and stochasticity from the isotherms of first- and second-order velocity statistics of a randomly selected vehicle. Specifically, provided ergodicity and stationarity, these stochasticity-density plots permit a direct determination of traffic properties from crowdsourced measurements of velocities of vehicles. We illustrate the predictive prowess of the approach for crowdsourced vehicle speed data collected by anonymous smartphone measurements for the state of Massachusetts, USA, as a powerful alternative to classical traffic property estimates from spatially distributed user counts.

Development of a radiological emergency evacuation model using agent-based modeling

In order to mitigate the damage caused by accidents in nuclear power plants (NPPs), evacuation strategies are usually managed on the basis of off-site effects such as the diffusion of radioactive materials and evacuee traffic simulations. However, the interactive behavior between evacuees and the accident environment has a significant effect on the consequential gap. Agent-based modeling (ABM) is a method that can control and observe such interactions by establishing agents (i.e., the evacuees) and patches (i.e., the accident environments). In this paper, a radiological emergency evacuation model is constructed to realistically check the effectiveness of an evacuation strategy using NetLogo, an ABM toolbox. Geographic layers such as radiation sources, roads, buildings, and shelters were downloaded from an official geographic information system (GIS) of Korea, and were modified into respective patches. The dispersion model adopted from the puff equation was also modified to fit the patches on the geographic layer. The evacuees were defined as vehicle agents and a traffic model was implemented by combining the shortest path search (determined by an A ∗ algorithm) and a traffic flow model incorporated in the Nagel-Schreckenberg cellular automata model. To evaluate the radiological harm to the evacuees due to the spread of radioactive materials, a simple exposure model was established to calculate the overlap fraction between the agents and the dispersion patches. This paper aims to demonstrate that the potential of ABM can handle disaster evacuation strategies more realistically than previous approaches.

Segment travel time route guidance strategy in advanced traveler information systems

In this paper, a segment travel time route guidance strategy was proposed in advanced traveler information systems. The route guidance information provided to the vehicles is the sum of travel time on equally divided segments. To evaluate its performance, the new strategy was compared with three other strategies in three different two-route scenarios based on the Nagel–Schreckenberg cellular automaton model. First, four strategies were applied to a symmetrical two-route scenario. The simulation results show that the smaller the segment length is, the greater the average flow will be. The more vehicles that choose roads based on the new strategy, the shorter the average travel time will be. There exists a optimal segment length for each the ratio of dynamic vehicles Sdyn which makes the travel time shortest. Second, in a symmetrical two-route scenario with a permanent bottleneck, results show that zero state and oscillation state were observed. When the bottleneck length more than 1000 cells, the oscillation state disappears. Finally, in a symmetrical two-route scenario with a temporary bottleneck, results show that when the inflow is high, the traffic network with Sdyn=0.5 is better than the one with Sdyn=0. When inflow is low, the situation is just opposite.

Hybrid multilane models for highway traffic

We study effects of lane changing rules on multilane highway traffic using the Nagel-Schreckenberg cellular automaton model with different schemes for combining driving lanes (lanes used by default) and overtaking lanes. Three schemes are considered: a symmetric model, in which all lanes are driving lanes, an asymmetric model, in which the right lane is a driving lane and the other lanes are overtaking lanes, a hybrid model, in which the leftmost lane is an overtaking lane and all the other lanes are driving lanes. In a driving lane vehicles follow symmetric rules for lane changes to the left and to the right, while in an overtaking lane vehicles follow asymmetric lane changing rules. We test these schemes for three- and four-lane traffic mixed with some low-speed vehicles (having a lower maximum speed) in a closed system with periodic boundary conditions as well as in an open system with one open lane. Our results show that the asymmetric model, which reflects the "Keep Right Unless Overtaking" rule, is more efficient than the other two models. An extensible software package developed for this study is free available.

Effects of route guidance strategies on traffic emissions in intelligent transportation systems

This paper studied the effects of different route guidance strategies on traffic emissions in intelligent transportation systems. Six route guidance strategies were applied in three different two-route scenarios based on the Nagel–Schreckenberg cellular automaton model. The real data of traffic emissions under different vehicle operational modes were used. The simulations of the traffic emissions, the emissions per vehicle, the emissions per unit flux, average travel time per vehicle and the relationship between the emissions per unit flux and the ratio of dynamic vehicles by using six route guidance strategies were obtained. Results showed that mean velocity route guidance strategy (MVS) and congestion coefficient route guidance strategy (CCS) were the best ones. They can effectively reduce the traffic emissions and improve the efficiency of traffic network. In terms of the total emissions, the value of emissions on the symmetrical two-route scenario with two exits was much lower than that on the one with one exit. Finally, we drew two conclusions based on the simulation results: (i) The route guidance strategy based on traffic data of the whole road is beneficial to reduce traffic emissions. (ii) The simpler and smoother road can lead to more reduction of traffic emissions and higher efficiency of traffic network.

Ant pheromone route guidance strategy in intelligent transportation systems

Based on the cellular automaton model and the concept of ant pheromone, this paper proposes a new route guidance strategy, called the ant pheromone route guidance strategy, in which the vehicles are regarded as special types of ants and their traffic information is regarded as the ant pheromone. To evaluate its performance, the new route guidance strategy was applied and compared with other three typical route guidance strategies under three different route scenarios, respectively, with open boundary conditions based on the Nagel–Schreckenberg cellular automaton model. First, in a symmetrical two-route scenario with two exits, results showed that the new route guidance strategy and vacancy length route guidance strategy were optimal. They outperformed the other strategies in terms of the value, stability, and balance of vehicle number, and the average speed and average flux on each route. To understand the impact of the strategy on traffic states, flux–density evolution process was studied. In addition, the influence of evaporation rate was also investigated. Second, in an asymmetrical two-route scenario with one exit, the simulation results also proved that ant pheromone route guidance strategy and vacancy length route guidance strategy were the best. Finally, in a symmetrical two-route scenario with a traffic accident, we compared the new route guidance strategy with the vacancy length route guidance strategy. Results indicated that the new route guidance strategy has distinct advantages. In short, in all three route scenarios we investigated, the ant pheromone route guidance strategy performed best.

Agent-based modeling of lane discipline in heterogeneous traffic

Designating lanes for different vehicle types is ideal road safety-wise. Practical considerations, however, require road sharing. Using a modified Nagel–Schreckenberg cellular automata model for two vehicle types (cars and motorcycles), we analyzed the interplay of lane discipline, lane changing, and vehicle density. In the absence of lane changing, the transition between free flow and congested states occurs at a higher vehicle (road occupation) density when the ratio of cars to motorcycles is increased. When lane changing is allowed, the smaller motorcycles tend to fill in unused spaces, until the point when the wider cars effectively block their way at high vehicle densities. When the condition of lane discipline is not imposed, i.e. staying wholly within lane boundaries is not required, further improvement in throughput becomes possible at the cost of required driver attentiveness.

Network operation reliability in a Manhattan-like urban system with adaptive traffic lights

Traffic breakdown to global gridlock occurring in congested traffic network makes the serious traffic congestion even much worse. This paper has proposed to use Network Operation Reliability (NOR) to quantitatively depict the probabilistic feature of traffic breakdown to global gridlock. The Nagel–Schreckenberg cellular automaton model has been used to simulate the traffic flow in a Manhattan-like urban network. A simple adaptive traffic light strategy has been proposed. It has been shown that if vehicles choose to use geometric shortest path, the adaptive traffic signals are able to remarkably enhance the NOR and sometimes the average velocity and the arrival rate as well. The vehicle distribution has been investigated, which has heuristically explained the enhancement of the NOR. A simple perimeter control strategy has been shown to fail to enhance the NOR. Finally, we show that if the time shortest path information could be provided and updated timely, then the NOR can be remarkably enhanced but the adaptive traffic signals have only trivial effect on NOR.

Modeling Mixed Bicycle Traffic Flow: A Comparative Study on the Cellular Automata Approach

Simulation, as a powerful tool for evaluating transportation systems, has been widely used in transportation planning, management, and operations. Most of the simulation models are focused on motorized vehicles, and the modeling of nonmotorized vehicles is ignored. The cellular automata (CA) model is a very important simulation approach and is widely used for motorized vehicle traffic. The Nagel-Schreckenberg (NS) CA model and the multivalue CA (M-CA) model are two categories of CA model that have been used in previous studies on bicycle traffic flow. This paper improves on these two CA models and also compares their characteristics. It introduces a two-lane NS CA model and M-CA model for both regular bicycles (RBs) and electric bicycles (EBs). In the research for this paper, many cases, featuring different values for the slowing down probability, lane-changing probability, and proportion of EBs, were simulated, while the fundamental diagrams and capacities of the proposed models were analyzed and compared between the two models. Field data were collected for the evaluation of the two models. The results show that the M-CA model exhibits more stable performance than the two-lane NS model and provides results that are closer to real bicycle traffic.

Mutil-Conditions Impress Nonsingular Dimensional Cellular Automaton on Traffic Flow

This paper is based on Nagel-Schreckenberg cellular automata model as the foundation, in the open boundary conditions, the traffic vehicle redirecting probability and before lane changing rules get to intersection will produce certain effect to interference with intersection , and so as to builds up the nonsingular cellular automata model. Through the research to redirecting probability, lane changing rules and the settings of traffic lights play a part in traffic flow characteristics, and points out the influence of phase change point position ,and at the same time, traffic lights timing differences can reduce vehicle interference to increase traffic flow, at the same time, play a analysis the critical redirecting probability of traffic flow in controlling significance, and points out the relationship between the critical point of Lane changing probability and traffic flow influence ,and lane-changing rules is correspond to the basic line of vehicles running.

Mechanism of Traffic Jams at Speed Bottlenecks

In the past 20 years of complexity science, traffic has been studied as a complex system with a large amount of interacting agents. Since traffic has become an important aspect of our lives, understanding traffic system and how it interacts with various factors is essential. In this paper, the interactions between traffic flow and road topology will be studied, particularly the relationship between a sharp bend in a road segment and traffic jams. As suggested by Sugiyama[1], when car density exceeds a critical density, the fluctuations in the speed of each car will lead to greater fluctuations in speed of the cars behind it. This enhancement of fluctuation leads to the congestion of vehicles. Using a cellular automata model modified from Nagel-Schreckenberg Cellular Automata model[2], the simulation results suggest that the mechanism of traffic jam at bottlenecks is similar to this. Instead of directly causing the congestion in cars, bottleneck on roads only causes the local density of traffic to increase. The resultant congestion is still due to the enhancement of fluctuations. Results of this study opened up a large number of possible analytical studies that could be used as grounds for future works.

Cellular automata model of self-organizing traffic control in urban networks

Cellular automata model of self-organizing traffic control in urban networksA model of city traffic based on Nagel-Schreckenberg cellular automaton (CA) model is presented. Traffic control is realized at intersections with two conflicting streams each (at any time at most one stream can have "green light" assigned to it). For simple and regular lattice-like networks which are considered, it is easy to find optimal switching periods giving maximum possible flow rates. These optimal strategies are compared with a self-controlling approach proposed by [1], which has not been implemented in a CA model until now. Previous work proved that generally this method gives superior results when compared to classical methods. In this paper we show that for deterministic scenario such control leads to self-organization, and that the solution always quickly converges to the optimal solution which is known in this case. Moreover, we consider also non-deterministic case, in the sense that possibility of turning with given probability is allowed. It is shown that the self-controlling strategy always gives better results than any solution based on fixed cycles with green waves.

A stochastic cellular automaton model for traffic flow with multiple metastable states

A new stochastic cellular automaton (CA) model of traffic flow, which includes slow-to-start effects and a driver's perspective, is proposed by extending the Burgers CA and the Nagel-Schreckenberg CA model. The flow-density relation of this model shows multiple metastable branches near the transition density from free to congested traffic, which form a wide scattering area in the fundamental diagram. The stability of these branches and their velocity distributions are explicitly studied by numerical simulations.

Cellular Automation Models for Traffic Flow and Metastability

A new stochastic Lagrange model of traffic flow, which includes slow-to-start effects and a driver's perspective, is proposed by extending the Burgers cellular automaton (CA) and the Nagel-Schreckenberg CA model. The flow-density relation of this model shows multiple metastable branches near the transition density from free to congested traffic. The stability of these branches is explicitly studied by numerical simulations.

Open boundaries in a cellular automaton model for traffic flow with metastable states.

The effects of open boundaries in the velocity-dependent randomization (VDR) model, a modified version of the well-known Nagel-Schreckenberg (NaSch) cellular automaton model for traffic flow, are investigated. In contrast to the NaSch model, the VDR model exhibits metastable states and phase separation in a certain density regime. A proper insertion strategy allows us to investigate the whole spectrum of possible system states and the structure of the phase diagram by Monte Carlo simulations. We observe an interesting microscopic structure of the jammed phases, which is different from the one of the NaSch model. For finite systems, the existence of high flow states in a certain parameter regime leads to a special structure of the fundamental diagram measured in the open system. Apart from that, the results are in agreement with an extremal principle for the flow, which has been introduced for models with a unique flow-density relation. Finally, we discuss the application of our findings for a systematic flow optimization. Here some surprising results are obtained, e.g., a restriction of the inflow can lead to an improvement of the total flow through a bottleneck.

Comment on `Garden of Eden states in a traffic model revisited'

Recently, Huang and Lin suggested a combination of two successfull mean-field theories, the 2-cluster approximation and paradisical mean-field, for the Nagel-Schreckenberg cellular automaton model of traffic flow. We argue that this new approximation is inconsistent since it violates the Kolmogorov conditions.

Correlation functions in the Nagel-Schreckenberg model

We investigate the effect of the jamming transition on short-range correlation functions in the Nagel-Schreckenberg cellular automaton model of single-lane traffic. At high densities the structure of the time-dependent correlation functions is double peaked. One peak corresponds to moving cars, the other to blocked cars. The emergence of the latter peak as well as the occurrence of short-range anticorrelations behind the propagating peak is related to the jamming transition. At even higher densities the peak corresponding to moving cars disappears which is an indication of a superjamming transition.