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Cellular Automata Model for Heterogeneous Traffic
Journal of Advanced Transportation
Abstract
Cellular Automata (CA) modelling is extended to study the heterogeneous traffic observed in developing countries. In heterogeneous traffic, the physical and mechanical characteristics of different vehicles vary widely which in turn leads to complex traffic behaviour resulting in no-lane discipline. This nature of the heterogeneous traffic is modelled with the help of an improved discrete CA model. A detailed description of the methodology used in developing the basic structure of the CA model is presented and the modified methodology is used to generate different traffic scenarios. From the results, it is observed that with the help of simple updating rules along with typical heterogeneous traffic characteristics of the region, this model is able to reproduce real traffic behaviour. An added advantage is that the modified structure of the CA model can also be used to extract some basic traffic characteristics which are useful in understanding the heterogeneous traffic behaviour. The simulation model is finally validated using the flow and occupancy relationship obtained from the field.
... However, most of the South Asian and developing countries have traffic streams with weak or no lane discipline. Vehicles in such undisciplined traffic streams have different static and dynamic characteristics resulting in higher heterogeneity in streams [4,5]. Modeling the traffic flow of heterogeneous and undisciplined traffic streams is a complex procedure and still an unresolved problem. ...
... The highest flow of cars aggregated at 5 s is observed as 10,080 veh/h or 2520 veh/h/ln. Figures 2,3,4,5,6,7,8,9, and 10 show within green time dynamics of traffic flow aggregated for different time intervals for cars and motorbikes for selected signal cycles. In total, traffic videos for about six hours were recorded using UAV, which contains 175 signal cycles. ...
... The analysis of within green time flow dynamics shows that the flow of traffic is not uniform within the green time. The flow of motorbikes is the highest during the first few (1)(2)(3)(4)(5) seconds of the green time, and it is significantly lower after the initial few seconds of green time. On the contrary, the flow of cars and other modes is lower during the initial few (1-5) seconds and gets its highest value after the first few seconds. ...
This research presents an in-depth microscopic analysis of heterogeneous and undisciplined traffic at the signalized intersection. Traffic data extracted from the video recorded using an unmanned aerial vehicle (UAV) at an approach of a signalized intersection is analyzed to study the within green time dynamics of traffic flow. Various parameters of Wiedemann 74, Wiedemann 99, and lateral behavior models used in microscopic traffic simulation package, Vissim, are calibrated for the local heterogeneous traffic. This research is aimed at exploring the queue-jumping phenomenon of motorbikes at signalized intersections and its impact on the saturation flow rate, travel time, and delay. The study of within green time flow dynamics shows that the flow of traffic within green time is not uniform. Surprisingly, the results indicate that the traffic flow for the first few seconds of the green time is significantly higher than the remaining period of green time, which shows a contradiction to the fact that traffic flow for the first few seconds is lower due to accelerating vehicles. Mode-wise traffic counted per second shows that this anomaly is attributed to the presence of motorbikes in front of the queue. Consequently, the outputs of simulation results obtained from calibrated Vissim show that the simulated travel time for motorbikes is significantly lower than the field-observed travel times even though the average simulated traffic flow matches accurately with the field-observed traffic flow. The findings of this research highlight the need to incorporate the queue-jumping behavior of motorbikes in the microsimulation packages to enhance their capability to model heterogeneous and undisciplined traffic.
... Authors (Lan and Chang, 2005;Vasic and Ruskin, 2012) developed models with two modes of traffic for multilane traffic flow. Subsequently many developments have taken place with the introduction of several modes of traffic to simulate various kinds of traffic flow situations (Mathew et al., 2006;Meng and Weng, 2011;Mallikarjuna and Rao, 2009). To consider natural human behaviour in simulation model randomization parameter is used, this parameter includes situations in which driver reduces the speed for example some incidents on road that diverts drivers attention. ...
... Present model uses three different situations randomization parameter and asymmetric lane rules with work zone. Randomization parameters were calibrated with field data by Mallikarjuna and Rao (2009). As it is evident from the literature review that among all of the heterogeneous traffic models proposed, very few of them can simulate traffic on work zones. ...
... A cellular automata model developed by Mallikarjuna and Rao (2009) was adopted for the study as it was found to adequately describe multilane heterogeneous traffic in India. The model adopts cellular automata brake light model for heterogeneous traffic conditions in India. ...
Increased delays and reduced speeds in work zones leads to congestion. This can be improved by optimizing the work zone length. The focus of this study is to model work zones using cellular automata model and to find the effects of work zones on traffic flow. The methodology adopted in the study involved creating work-zone on the road by blocking some of the cells and then determining traffic characteristics such as delay and queue lengths for model validation. For this the lateral movement rules of the existing Cellular Automata model were modified in order to replicate the traffic movement near work zones. This model is calibrated and validated using data from work zone observed near a metro rail station in Delhi. From the analysis it was evident that the queue length increased with increase in the length of work zone. Several relationships were tried between delay and work zone length. Among them the rational form was found suitable.
... Many of the CA models developed for mid-blocks thus far are based on periodic (closed) boundary conditions. [39][40][41]46 The movement of vehicles in the periodic boundaries is given as Figure 1(a). Once the specific number of vehicles Influence zone of intersection for mode m ...
... Road width wise location of vehicle l 2 # Road length wise location of vehicle 14 Fouladvand et al., 15 Tian, 16 Luo et al., 17 Radhakrishnan and Mathew, 18 Chai and Wong, 19 Ren et al., 20 Li and Sun, 21 Zhao et al. 22 and Yang and Yan-Yan 23 Barlovic et al., 2 Jia and Ma, 10 Luo et al., 17 Tadaki, 24 Cheybani et al., 25 Mitarai and Nakanishi, 26 Jiang and Wu, 27 Jia and Ma 28 and Meng and Weng 29 Closed boundary studies Brockfeld et al., 9 Marzoug et al., 30 Biham et al., 31 Nagatani and Seno, 32 Chung et al., 33 Benjamin et al., 34 Feng et al., 35 Chowdhury and Schadschneider, 36 Shi et al. 37 and Huang and Huang 38 Emmerich and Rank, 39 Lárraga et al., 40 Mallikarjuna and Rao, 41 Pandey et al., 42 Singh et al., 43 Zamith et al. 44 and Raheja 45 Partly open boundary simulations ...
Cellular automata (CA) simulation models developed for traffic are either closed or open boundary type. The selection and difference of boundaries has been studied extensively for ideal and single-lane homogeneous traffic conditions. However, the effect of these on multi-lane-heterogeneous traffic still needs attention because most of the traffic observed in many parts of the world is not single-lane homogeneous traffic. It is evident from multiple studies that open and closed boundaries affect the simulation results. Moreover, these require different inputs for simulation. This study attempts to evaluate the difference in the results of open and closed boundary simulations in heterogeneous non-lane-based traffic. The methodology discussed in this study is relatable to the field conditions. The present study includes some of the common but often ignored features in the model such as seepage of small-sized vehicles. Furthermore, this study also includes some of the previously unnoticed features while modeling the non-lane-based traffic at intersections. The modeling of open boundaries simulation can be better and easy in most of the situations compared to the closed boundaries. Closed boundary simulation results for flow-density curve show a smooth trend, whereas open boundary simulation results are scattered as observed in the field. This study further concludes that the size of the vehicle does not change the fundamental diagrams except when other characteristics such as seepage, lane change, and different maximum speeds for different modes are considered. The study used field observed influence zone of intersections to decide the dimension of intersection in the simulation model.
... Furthermore, this model cannot validate the changeability in headway distance between the lead and follower vehicles regarding vehicle velocity due to the same cell size assumption. Therefore, a wide range of modifications and extensions to the CA model was performed by Incorporating many parameters such as other vehicles types, vehicle size, mechanical properties, lateral arrangement, lateral gaps between vehicles, flow, velocity, occupancy of a vehicle in a cell, cell size, and acceleration&vehicle type [353][354][355][356][357][358][359][360][361][362]. As a result, the improved CA model utilizes a cell size of 0.5 m in length, a safe gap at the front and back of vehicles, the relationship area of occupancy, interaction rate, and structure of vehicles [361,362]. ...
... As a result, the improved CA model utilizes a cell size of 0.5 m in length, a safe gap at the front and back of vehicles, the relationship area of occupancy, interaction rate, and structure of vehicles [361,362]. However, according to outcomes presented in [353][354][355][356][357][358][359][360][361][362], further validation and investigation of the model in various traffic conditions and lateral and longitudinal interactions is required to expand its application. ...
In recent years, autonomous vehicles (AVs), which observe the driving environment and lead a few or all of the driving duties, have garnered tremendous success. The field of AVs has been developing rapidly and has found many applications. As a safety requirement by policymakers, these vehicles must be evaluated before their deployment. The evaluation process for AVs is challenging because crashes are rare events, and AVs can escape passing predefined test scenarios. Therefore, capturing crashes and creating real test scenarios should be considered in order to have an evaluation approach that represents the real-world scenarios. One evaluation approach is based on the naturalistic field operational test (N-FOT), in which prototype AVs are driven by volunteers or test engineers on the roads. Unfortunately, this approach is time-consuming and costly because one needs to drive thousands of miles to experience a police-reported collision and nearly millions of miles for a fatal crash. Another approach is the Accelerated Evaluation method. The core idea of the Accelerated Evaluation approach is to modify the statistics of naturalistic driving so that safety-critical events are emphasized. This paper presents a brief survey of the advances that have occurred in the area of the evaluation of partly or fully AVs, starting with naturalistic field operational tests (N-FOTs). The review goes on to cover test matrix evaluation, worst-case scenario evaluation (WCSE), Monte Carlo simulations, and accelerated evaluation (AE). We also present all the simulation-based and agent-based modeling approaches that do not follow any evaluation protocol listed above. This study provides a scientific analysis of each of the evaluation techniques, focusing on their advantages/disadvantages, inherent restrictions, practicability, and optimality. The results reveal that the accelerated evaluation approach outperforms naturalistic field operational tests (N-FOTs), test matrix evaluation, worst-case scenario evaluation (WCSE), Monte Carlo simulations methods in some of the car-following, and lane-change studies when using specific models. Moreover, the agent-based model and augmented and virtual reality approaches show promising results in AVs evaluation. Furthermore, integrating machine and deep learning into the available AV evaluation methods can improve its performance and generate encouraging outcomes.
... A common approach in the literature for modelling area-based heterogeneous traffic is the application of a cellular automata (CA) based model. Different researchers, Lan and Chang (2005), Mathew, Gundaliya, and Dhingra (2006), and Mallikarjuna and Rao (2009) have proposed modifications to traditional CA model, 'NaSch model', from Nagel and Schreckenberg (1992) for its application in area-based traffic. Lan and Chang (2005) have proposed to consider small cell size and allow vehicles to occupy multiple cells based on its physical dimension. ...
... Mathew et al. (2006) have proposed to determine cell size based on the passenger car equivalent (PCE) value of vehicles. Mallikarjuna and Rao (2009) have proposed to consider cell size consistent with the length of the smallest vehicle. Nevertheless, the modelling requires appropriate CF and LC logics to change the position of vehicles over the spatial temporal cell grids. ...
The area-based (i.e., non-lane based) heterogeneous traffic (as in developing countries) has significant differences from the lane-based homogeneous traffic (as in developed countries). In area-based traffic, drivers generally ignore the lane markings and perceive the entire road space while progressing longitudinally. The traditional car-following and lane changing models are not directly applicable to model such driving behaviour.
This research aims to microscopically model the dynamics of the subject vehicle in area-based traffic flow. The modelling is conducted in two steps: area selection, and vehicle movement. In step-1, a multinomial logit (MNL) model is considered for selecting the area-based movement direction of the subject vehicle. The choice space of the subject vehicle is divided into numbers of realistic radial cones considering the possible moving directions of the subject vehicle in the next simulation time step. These radial cones form the alternatives for the decision of the subject vehicle. The attributes of the alternatives are defined in terms of angular deviation from the direction of the flow, spacing and relative speed. This model is calibrated and validated for both cars and motorcycles using real trajectory data, and the results demonstrate the good performance of the model. In step-2, a modified intelligent driving model (MIDM) is proposed to simulate the next position of the subject vehicle (along the selected direction as the outcome of the model in step-1). The parameters of the MIDM model are calibrated using real data for cars and motorcycles.
The deterministic parameters for MNL model and the empirical distribution of the MIDM model parameters are utilized to stochastically simulate vehicle trajectories with the initial and boundary conditions determined by the real dataset. The comparison of the macroscopic properties between the simulated and real datasets provides promising results for the simulation applicability of the proposed modelling framework.
... Table 1 summarises the modelling approaches presenting the basic assumptions, potentials of each approach and issues that need further consideration. Chang (2003, 2005), Hsu (2005, 2006), Hsu, Lin, Chiou, and Lan (2007), Meng et al. (2007), Mallikarjuna and Rao (2009) and Hsu (2009, 2010) Lee (2008), , Lämmel (2015, 2016) and Lee and Wong (2016) Nguyen, Hanaoka, and Kawasaki (2012, 2014), and Nguyen (2012) Nguyen and Hanaoka (2011) ...
... The single lane Na-Sch model is however inadequate for realistic modelling purposes. A considerable number of CA models have been modified in a later date (Bham & Benekohal, 2004;Chowdhury, Wolf, & Schreckenberg, 1997;Kerner & Rehborn, 1996;Knospe, Santen, Schadschneider, & Schreckenberg, 2000;Mallikarjuna & Rao, 2009;Nagel, 1996;Nagel, Wolf, Wagner, & Simon, 1998). Recently, CA models have gained increasing attention for its inherent capability in explicating the traffic behaviours of MTWs and other vehicle types in mixed traffic streams. ...
... Among the first microscopic models for bicyclist operations were those that used modelling paradigms developed for cars. One example are the Cellular Automata models, whose parameters have been adjusted to capture the smaller size and lower speeds of bicycles compared to cars (19)(20)(21). However, the rules that determine movements between cells have not been modified to represent cycling behavior and interactions. ...
Due to the inherent safety concerns associated with traffic movement in unconstrained two-dimensional settings, it is important that pedestrians' and other modes' movements such as bicyclists are modeled as a risk-taking stochastic dynamic process that may lead to errors and thus contacts and collisions. Among the existing models that may capture risk-taking behaviors are: 1) the social force models (through the interplay of the repulsion and the attraction force parameters); 2) and the discrete-choice models (through the rationality or the bounded rationality paradigm while weighing different alternatives). Given that the social force models may not readily capture the contact/collision dynamics through the Newtonian force framework, decision-making theories are hypothesized as a feasible approach to formulate a new model that can account for cognitive and behavioral dimensions such as uncertainty and risk. However, instead of relying on the bounded rationality theory, in this paper, a generalized Prospect Theory based microsimulation model is proposed. The model relies on the micro-economics Prospect Theory paradigm where pedestrians or bicyclists (i.e., micro-mobility users) evaluate their speed and directional alternatives while considering the possibility of colliding with other obstacles/users. A numerical analysis on the main model parameters is presented. The model is then calibrated and validated using two real-world data sets with trajectories recorded in naturalistic settings. With the calibrated parameters studied, simulation exercises and sensitivity analysis are conducted to recreate bottlenecks and lane formations in different conditions. The findings show that the proposed model's parameters reflect the risk-taking tendencies of different roadway users in mixed right-of-way's environments while showing realistic microscopic and macroscopic traffic flow characteristics.
... These were calculated on the full width of the road, that is, two lanes. The road was divided into cells with a size of 0.5 m length and 0.7 m width (49,50). ...
Intersections affect the maneuvering and driving behavior of vehicles. The present study attempts to simulate an isolated signalized intersection with the dimensions obtained through the influence zone of intersections. This model includes several unexplored traffic characteristics observed at the intersection, such as non-lane-based heterogeneity and seepage behavior. The model was calibrated and validated with the field data collected in New Delhi, India. Several measures of performance, such as GEH statistics, Theil’s coefficient, root mean square error, and so forth, were used to validate and benchmark the simulation model. After calibration and validation, the model was used to find delays. The delays obtained from the model, several manuals, and the field were compared and found to be close to the field delays. Further, delays obtained from Indonesian and Canadian manuals were comparatively closer to the delays obtained from the field, whereas delays obtained from the Indian Highway Capacity Manual (2017) and U.S. Highway Capacity Manual (2010) are overestimated. The model presented can be used to benchmark the performance of signalized intersections under a variety of traffic and environmental conditions.
... Early microscopic models such as lane-based models and most of the commercial simulation software such as VISSIM, Transmodeller, etc. pay more attention to handling the physical activities of agents based on virtual lanes [22], as shown in Fig. 2(a). Meanwhile, most mainstream models, namely Cellular Automata (CA), deal with the movements and interactions using the principle of spatial-discrete assumptions [23]. The one-on-one interaction between cells and lanes has not been adjusted to fit the operations of two-wheelers in reality [21,24]. ...
In recent years, the interest in riding in cities using the two-wheeler (e.g., bicycles, electric bicycles, electric mopeds, etc.) increases. Mixed-traffic road segments are one of the most common traffic scenes where the mixed two-wheeler flows exist. Because the movements are often not restricted by lanes, the two-wheeler uses lateral road space more freely and shows obvious multilateral interactions (i.e. multi-interaction) with others, bringing issues that endanger traffic safety. A precise estimation of its impacts on traffic operation and safety is necessary, while the microscopic simulation model can satisfy the need as a helpful tool. However, most existing simulation models of these three types of two-wheelers are essentially focusing on handling the one-on-one interaction. The capability to deal with the two-wheeler multi-interaction in mixed traffic is still rare, and the description of what endogenous tasks are contained by the multi-interaction has also not given by literature. To this end, this paper first defines what the multi-interaction entails on the operational behaviour level, claiming that it contains three intertwined processes, namely a (mental) perception, a (mental) decision, and a physical process. The (mental) perception and decision processes represent the recognition of interactions and the response to traffic conditions, while the physical process refers to the execution of these mental activities. A three-layer simulation framework has then been developed, where each layer sequentially corresponds to one of the operational behaviour tasks. Integrated component models are also proposed in each layer to cover these operational tasks. A Comfort Zone model is hence put forward to dynamically perceive the multiple interactive road users, while a Bayesian network model is developed to deal with the decision-making process under multi-interaction situations. Meanwhile, a behaviour force model is also underlied to capture the non-lane based movements following the selected behaviour and current interaction states. Finally, we face validate the proposed models by the comparison between simulation results and observations obtained from trajectory dataset. Results indicate the model performance matches the observed interaction and motion well.
... The proposed models are different from each other because of the lane-changing rules, thus producing different results about the movement of the fast and slow vehicles. In [31], the heterogeneous traffic behavior in developing countries was reproduced with a discrete cellular automata (CA) model, modeling five types of vehicles: car, bus, truck, two-wheeler, and three-wheeler. In [32], a CA model was used to simulate traffic in a two-lane system; it was demonstrated that even small densities of slow vehicles induced the formation of platoons. ...
In this work, the authors developed procedures to explain mean extra travel time (T) and extra travel time variability (V). This was carried out for situations (through simulations) where the fast vehicles’ travel time, whose speed tendency (sp1) is the permitted speed limit, is negatively affected (i.e., increasing travel time) by the presence of slow vehicles, whose speed tendency (sp2) is half the speed limit. The speed limit was set in the range of 60 km/h to 90 km/h, with seven cases, and every case had eight simulations, each with different p1 (fast vehicles’ percentage) and p2= 100% − p1 (slow vehicles’ percentage) values. p2 ranged from 10% to 80% at intervals of 10%, for a total of 56 simulations. From the simulations’ data, we calculated the fast vehicles’ extra travel time, which is the additional time to traverse an avenue segment owing to the presence of slow vehicles. The fast and slow vehicles recreate heterogenous traffic in terms of speed. We developed procedures for modeling T and V with p2, and V with T. For modeling, ~71.42% of the data from simulations was used. We find that the models’ parameters values can be used for explaining the remaining data. In addition, we discovered that the pattern of p2 vs. V, for p2 ranging from 50% to 80%, is different among sp1 cases and not linear.
... This section presents and summarizes the main behaviour models found in the literature for describing PTW behaviour. Cellular automata (Lan and Chang, 2005, Mallikarjuna & Rao, 2009, Gundaliya et al., 2008 and agent-based models are among the most popular for simulating this motorized vehicle type (Lee, 2008, Lee et al, 2009, Agatwal et al., 2015, Lee and Wong, 2016, Argawal and Lammel, 2016. Lee et al. (2009) developed an agent-based multinomial choice model for observing the motorcycle movement based on the lateral and longitudinal headway as well as the path choice model while Lee and Wong (2016) used the same type of simulation models for simulating queue formation of PTWs. The concept of safety space from the adjacent vehicle and how the acceleration and deceleration profile of the ego PTW is influenced by the speed changes of the lead PTW, the was the basis of the model of Nguyen et al. (2012Nguyen et al. ( , 2014. ...
The advent of autonomous vehicles brings major changes in the transportation systems influencing the infrastructure design, the network performance, as well as driving functions and habits. The penetration rate of this new technology highly depends on the acceptance of the automated driving services and functions, as well as on their impacts on various traffic, user oriented and environmental aspects. This research aims to present a methodological framework aiming to facilitate the modelling of the behaviour of new AV driving systems and their impacts on traffic, safety and environment. This framework introduces a stepwise approach, which will be leveraged by stakeholders in order to evaluate the new technology and its components at the design or implementation phase in order to increase acceptance and favor the adoption of the new technology. The proposed framework consists of four sequential steps: i. conceptual design, ii. data collection, processing and mining, iii. modelling and iv. autonomous vehicles impact assessment. The connection between these steps is illustrated and various Key Performance Indicators are specified for each impact area. The paper ends with highlighting some conceptual and modeling challenges that may critically affect the study of acceptance of autonomous vehicles in future mobility scenarios.
... The first microscopic models for cyclist operations used modelling paradigms developed for cars. One example are the Cellular Automata models, whose parameters have been adjusted to capture the smaller size and lower speeds of bicycles compared to cars (Mallikarjuna and Rao, 2009;Yao et al., 2009;Vasic and Ruskin, 2012). However, the rules that determine movements between cells have not been modified to represent cycling behaviour and interactions. ...
This paper presents a novel microscopic modelling framework for bicycle flow operations. The modelling principles are based on similar principles successfully applied in our previous work on pedestrian and vessel flow. The main contributions of the paper are in the extension towards modelling cyclists that has not been proposed in literature before, and in the insights gained by simulation with the model using different scenarios, showing how the model outcomes depend on the modelling choices and parameters.
The generalisation entails two major changes compared to our previous pedestrian model. First of all, the model does justice to the kinematics of cyclists. Contrary to pedestrians, cyclist are more restricted in their movement. The model approximates these restrictions by considering speed and movement direction and changes therein. Secondly, the model includes different strategies (cooperative, zero-acceleration, demon opponent) in its underlying game-theoretical framework, and allows including traffic rules. This allows us to model different attitudes towards risk representing different types of cyclists.
The (qualitative) insights gained by application of the model pertain to one-on-one interactions between cyclists and the impact of the strategy assumptions and parameter choices on those interactions as well as on the collective phenomena that occur in the cyclist flow and their sensitivity to parameters (reflecting the extent of the prediction horizon, the level of anisotropy, and the relative importance of keeping the desired path). With respect to the collective phenomena, we look at efficiency and self-organised patterns.
We conclude that the model acts in a plausible manner. While we do not aim to show empirical validity, we see that the qualitative behaviour of one-on-one interactions is plausible if compared to experimental or field data. We also observe plausible collective patterns, including forms of self-organisation under specific parameter settings. The latter is not trivial given the fundamental differences in bicycle and pedestrian flow.
... Additional factors like varying vehicle speeds, frequent intersections and merging traffic from side roads also affect traffic response. Studies on heterogeneous traffic in Indian conditions have mostly been done using microscopic models [Mallikarjuna and Rao (2009);Metkari et al. (2013)]. However, extensive data collection and estimation with associated computational expense may limit their feasibility in real-time situations. ...
Regulation of heterogeneous traffic is a challenging task on urban roads, particularly those where traffic congestion is routinely encountered. In this paper, a model based traffic signal control scheme via state feedback controller is presented. An original contribution of this study is the use of area occupancy as the measurement variable, which is apt for characterising heterogeneous and lane less traffic. An adaptive Kalman filter is used to estimate traffic density. The developed control scheme was implemented on a road stretch simulated in VISSIM, a commercial microscopic traffic simulation software, and interfaced with MATLAB using VISSIM COM interface. The implementation was shown to satisfy the objective of maintaining the desired density in the study stretch which demonstrated the effectiveness of the developed control scheme.
... However, further testing of the model in different traffic conditions was required to broaden its application. Further modifications of the CA model that involved amendment in the acceleration value as a function of vehicle type and velocity to accommodate the heterogeneous traffic conditions have been carried out [65]. Using the refined CA model, an attempt was made to incorporate the erratic motorcycle behaviour in diverse traffic conditions into the model development [63]. ...
The area of traffic flow modelling and analysis that bridges civil engineering, computer science, and mathematics has gained significant momentum in the urban areas due to increasing vehicular population causing traffic congestion and accidents. Notably, the existence of mixed traffic conditions has been proven to be a significant contributor to road accidents and congestion. The interaction of vehicles takes place in both lateral and longitudinal directions, giving rise to a two-dimensional (2D) traffic behaviour. This behaviour contradicts with the traditional car-following (CF) or one-dimensional (1D) lane-based traffic flow. Existing one-dimensional CF models did the inclusion of lane changing and overtaking behaviour of the mixed traffic stream with specific alterations. However, these parameters cannot describe the continuous lateral manoeuvre of mixed traffic flow. This review focuses on all the significant contributions made by 2D models in evaluating the lateral and longitudinal vehicle behaviour simultaneously. The accommodation of vehicle heterogeneity into the car-following models (homogeneous traffic models) is discussed in detail, along with their shortcomings and research gaps. Also, the review of commercially existing microscopic traffic simulation frameworks built to evaluate real-world traffic scenario are presented. This review identified various vehicle parameters adopted by existing CF models and whether the current 2D traffic models developed from CF models effectively captured the vehicle behaviour in mixed traffic conditions. Findings of this study are outlined at the end.
... Arasan et al. [12] and Venkatesan et al. [13] developed microscopic simulation model for heterogeneous traffic. The principles of Cellular Automata were applied to model heterogeneous traffic in [14] and [15]. Use of non-continuum macroscopic models for heterogeneous conditions based on the conservation law for vehicles and the fundamental relation of traffic flow was reported in the study by Anand et al. [16]. ...
Managing congestion in mixed traffic conditions, characterized by heterogeneous and lane-less traffic, is a challenging task. Traditionally density, defined as the number of vehicles in a road stretch, is used to quantify congestion. However, direct measurement of density is difficult and hence is usually estimated from other variables. In this paper, a relationship is derived between traffic density and area occupancy, a variable that can incorporate heterogeneity and lane-less movement. Using the derived density-area occupancy relation, a non-continuum macroscopic single state linear time varying model was developed. Estimation of density was done by using the Kalman filtering technique and corroborated with simulated density. The need for dynamic estimation is motivated by evaluating the performance of two static estimation schemes in the presence of uncertainties. Performance was tested for different traffic scenarios such as congestion and non-recurrent traffic incidents. Further, to improve the estimation accuracy in scenarios involving transitions in traffic conditions, an adaptive estimator was developed. It was found that the adaptive estimator provided the best estimation accuracy.
... More research effort has been put on modelling the bicycle control dynamics while riding and interacting with other road users, as several microscopic behavioural models have been developed. Early microscopic cyclist models made use of modelling paradigms developed for cars, such as Cellular Automata models, while adjusting their parameters to reflect the lower speeds of bicycles and their smaller size (Mallikarjuna and Rao, 2009;Yao et al., 2009;Vasic and Ruskin, 2012). However, the rules governing the movement between cells have not been adjusted to represent cycling behaviour. ...
Operational cycling behaviour is greatly understudied, even lacking a definition of what this behavioural level actually entails in terms of decision making. In this paper, we define the cyclist operational level and argue that it consists of two intertwined processes, a mental and a physical process. The mental process refers to path choices made within a route and the physical process refers to the bicycle control dynamics through pedalling and steering. We propose a novel two-layer framework, where each layer captures the tasks of one of the processes within the operational level. Discrete choice theory is proposed to model each layer. The plausibility of the framework is demonstrated through an application focusing on the queue formation process upstream of a red traffic light, including selecting a queuing position and cycling towards it. Models are estimated for the two layers using cyclist trajectory data collected at a signalised intersection in Amsterdam, the Netherlands. The models reveal the attributes that influence the decisions made in each layer and are face validated using simulation. The proposed framework and the (behavioural) findings of its application are the main scientific contributions of this paper, which pave the way for future research.
... The transitions depend on the actual states of the cell, which can be occupied or free (Helbing, 2001). Mallikarjuna and Rao (2009) give an excellent introduction to CA and literature in the application for heterogeneous traffic modeling. In Nagel and Schreckenberg' s approach (Nagel and Schreckenberg, 1992), interactions between vehicles, road and drivers were considered implicitly and applied on two lane, directional highway traffic. ...
Where multiple functions of roads interfere, conflict avoidance reaches human and
technological limits and constitutes one of the major challenges in transportation engineering. In the last two decades, several concepts of self-explaining roads have brought
versatile options to urban planning and have became valuable tools to manage heterogeneous traffic flows. Shared space and Begegnungszone (“encounter zone”) are the
most popular concepts for urban roads and squares. From a scientific and road planning perspective, there are still gaps in the understanding and predicting the complex
interaction of different road users.
Microscopic traffic flow models allow dynamic simulation of pedestrians, vehicles, driver
behavior and the interaction among each other and with infrastructure. This dissertation
structures the problem of simulating traffic flows on shared space and creates new ways
of applying agent based microscopic modeling. The underlying multi-agent social-force
model describes the impact of social and technical interaction of traffic dynamics by
establishing fields of force in analogy to physical models in Newtonian dynamics. The
infrastructure is described by a force field keep agents on their path. Agents avoid
obstacles and use their individual preferences. With bringing vehicles as non-holonomic
objects in the world of social forces, both a single-track model and a bicycle model are
introduced. To solve interaction processes on a tactical level, the conflicts are transferred
to non-cooperative games with perfect information. This approach offers the novelty
to mathematically combine social and rule-based behavior. Finally, the dissertation
describes the model calibration approach based on real world trajectories. The model is
applied to a shared space layout that is already implemented in Austria to compare the
simulated traffic flow to real world data.
The major part of empirical data for calibration is acquired at an intersection in Austria
that had been changed from a conventional design to a shared space setting and some
years later to a Begegnungszone. The calibrated parameters clearly show a plausible
contrast in social and rule-based behavior between shared space and Begegnungszone.
... The vehicle took into account the locations and speeds of the surrounding road users and selected a desired route during the lane selection process (13). Cellular automata models are a form of discrete time and space model in which a vehicle passed through the cell grids using some rules, including acceleration rule, deceleration rule, randomization rule, and movement update rule (14,15). This type of model needed to separately set different lane-changing rules and update rules for motor vehicles and non-motor vehicles, which increased the complexity of the model. ...
In many developing countries like China, many queuing electric bikes (e-bikes) passing an intersection simultaneously greatly reduces the capacity of the intersection for motor vehicles, by invading the passing area of motor vehicles. To study the invasion effect of e-bikes on the traffic flow of motor vehicles at an urban signalized intersection, this paper proposes a social force model for the heterogeneous traffic flow of motor vehicles and e-bikes. The proposed model is calibrated and validated using real data collected in Chengdu, China. The validation results show that the proposed model can replicate the heterogeneous traffic flow with low errors. Simulations based on the proposed model are conducted to investigate what strategies can reduce the invasion of e-bikes in normal motor vehicle traffic. The results show that when the number of queuing e-bikes before the stop line is more than 20, the two strategies can be applied: the stop-line-ahead strategy and the green-signal-ahead strategy. The study suggests that the 2–4 s of green signal ahead or 3–5 m of stop line ahead for non-motor vehicles can significantly reduce the interference of e-bikes on motor vehicle traffic. In addition, the combination of the two strategies can also obtain the same effect but with smaller change to the original intersection design.
... Lan et al. (2009) introduced the concept of limited deceleration capability of vehicles into their CA simulations which were seldom used in conventional CA models. Again Mallikarjuna and Rao (2009) extended the CA model by modifying the acceleration value as a function of vehicle type and vehicle speed to incorporate heterogeneous traffic flow characteristics. Based on the refined CA model, a sophisticated CA model is proposed by Lan et al. (2009) to elucidate the erratic motorcycle behaviours in mixed traffic conditions (Lan et al. 2010). ...
Indian traffic is highly heterogeneous consisting of all-inclusive vehicle characteristics, occupying any lateral position over the entire road width which results in vehicles continuous interaction with the neighbouring vehicles (in both longitudinal and lateral directions), indicating two-dimensional (2D) traffic manoeuvre, opposite to the traditional one-dimensional (1D) interaction of vehicles in lane based traffic. Certain modifications were made in the existing 1D models to describe the overtaking and lane changing manoeuvre of the mixed traffic stream. However, the continuous lateral manoeuvre of the no-lane based mixed traffic cannot be described by these parameters. This paper initially provides a brief review of different 2D behavioural models, which describe the longitudinal and lateral movements simultaneously. Also, the various existing commercially available traffic micro-simulation frameworks developed for representing the real traffic are reviewed. Different microscopic traffic parameters used in the existing simulation models to mimic the real-world traffic are identified, which can be used to understand the 2D traffic stream.
... As a result of the lack of available software options, and the increasing need for simulation methods for these rapidly developing regions, several researchers have begun examining this issue over the past decade. Several approaches have been taken, ranging from cellular automata to object-oriented car following models (Malikarjuna and Rao 2010;V Thamizh Arasan and Koshy 2005;Thankappan, Tamut, and Vanajakshi 2010;Metkari, Budhkar, and Kumar Maurya 2013;Venkatesan and Sivandan 2009). These models have shown strong reproducibility of observed traffic characteristics in research, but a coherent methodology has yet to be developed. ...
Modelling of traffic flow lacking lane-adherence, with variable vehicle sizes and speeds, is a pressing issue in the simulation field. Commercially available software is not designed for modelling such traffic, which is characteristic of developing countries. A recently developed method is to model traffic as grains of sand moving through a porous medium. This approach is explored and expanded in this work to consider multiple vehicle classes and potential uses in microsimulation. A microsimulation model is developed using an object-oriented approach and compared with existing work in the field. The developed approach, found to fit with the porous flow approach, is shown to properly reflect the traffic flow impacts associated with introducing additional vehicle classes. Fundamental flow diagrams are presented for heterogeneous traffic, which fit a Daganzo approximation. It is determined that several changes are required to the theoretical framework to accurately represent traffic characteristics before viable commercial application.
... The brake light models are widely applied in various traffic flow analysis. For example, Hafstein et al. (2003) simulated traffic flow on the autobahn network in North Rhine-Westphalia; Li et al. (2007) constructed a complex network from the evolution process of traffic flow; Jiang et al. (2008) studied the effects of adaptive cruise control vehicles in a mixture with manually controlled vehicles); Mallikarjuna and Rao (2009) investigated the heterogeneous traffic in developing countries; Meng and Weng (2011) studied the heterogeneous traffic in work zone area; Appert-Rolland and Du Boisberranger (2013) tested lane-changing rules; Lin et al. (2013) investigated traffic patterns and the associated phase transitions for pure and mixed traffic; Yao and Yao (2016) surveyed the inter-vehicle communication strategy; and Zhao et al. (2016) studied the driver psychological characteristics in mixed traffic and the lateral influence between vehicles on adjacent lanes. However, these models cannot simulate the empirically consistent synchronized flow. ...
The moving synchronized pattern (MSP) is an important traffic pattern that can emerge when traffic breakdown occurs. However, up to now most models cannot reproduce a realistic propagation speed of downstream front of the MSP, which significantly weakens their applications in traffic breakdown prediction and control. In this paper, a new brake light cellular automaton model is proposed, which assumes that: (i) the drivers would be sensitive to the brake light only when their speeds are larger than a critical speed; (ii) the anticipated deceleration of a preceding vehicle increases with the increase of the speed of the following vehicle. Simulation analysis shows that the new model can depict traffic breakdown and related synchronized traffic flow patterns. Importantly, it can realistically reproduce the propagation speed of downstream front of the MSP. Finally, the new model is calibrated and validated by NGSIM detector data.
Priority and sign-controlled intersections under heterogeneous and mixed traffic conditions behave in an uncontrolled manner with drivers and other road users neglecting right-of-way and priority rules. Microscopic traffic flow simulation is an effective way to explain such complex vehicular interactions without much effort and cost in shortage of specific video-image data. This research aims at enhancing potential capacity of priority-controlled (unsignalized in nature) intersections using grid-based cellular automata (GBCA) models in context of agent-based computer simulations. The grid-based cellular automata (GBCA) model proposed considers three-dimensional visualizations of road objects like links, nodes, connectors with vehicles in OpenGL environment inside the NetLogo and Java platform. Twenty-three unsignalized (both four-legged and three-legged) intersection traffic and geometric data collected from different regions of India have been utilized to create the GBCA models. Various intersection dimensions with several vehicle types and maximum velocities are considered for validating the proposed GBCA model. Four uncontrolled intersection vehicle entering and leaving rules based on virtual priority abstract of Indian driving behaviour are also included as traffic operating scenarios within the proposed GBCA model simulation framework in NetLogo. Findings from the study suggests sign and priority-controlled intersections in India need re-modification in terms of driver turning rules. According to the GBCA simulations in NetLogo and Java, the fourth traffic rule re-modification proposed in this study helps reduce service delays by 17% but increases potential intersection capacity by 20% at priority-controlled intersections. The average potential capacities for right turning traffic as obtained from the proposed model are 2478 vehicles/h/lane and 1289 vehicles/h/lane for major and minor roads, respectively, which showed perfect correlations with field estimated gap acceptance capacities.
Bicycle motion simulation is fundamental to urban transportation planning, virtual reality and other areas. This article proposes a data‐driven based double‐layer bicycle simulation model to consider the cyclist's decision‐making process and the bicycle's kinematic structure. This proposed model consists of two layers, the decision‐making layer and the motion layer. First, the decision‐making layer using machine learning algorithms models the decision‐making process as a regression problem to output the cyclist's decision. Then, the motion layer applies a bicycle kinematics model to output bicycle motion under physical constraints. In addition, a solution to calculate bicycles' dynamic information is proposed for the data‐driven method. Quantitative and qualitative experiments have been conducted, and results show that the double‐layer model and the parameter calculation solution can generate realistic bicycle motion simulations. This article proposes a data‐driven based double‐layer bicycle simulation model. The model consists a decision‐making layer using machine learning and a motion layer using double‐wheel kinematic model. The proposed model can generate realistic bicycle motion simulations.
In this chapter, we focus on the modeling of the behavior of cyclists. This behavior encompasses different types of interconnected decisions: from the split-second decisions that cyclists make when they are riding their bike and are interacting with the road and other traffic participants to choices pertaining to the activities they want to perform and the locations where they can perform these activities. These different decisions are often related to different temporal (and spatial) scales. The detail in which these decisions need to be accurately modeled is often dependent on what the model is applied for, as will be explained in the ensuing of this chapter. Therefore, different (types of) models have been developed, as introduced in the last part of this chapter.
Infrastructure support capability is one of the key parameters toward the success in Smart City. Past research presented several intelligent transportation systems (ITS) to efficiently manage the traffic congestion and enhance system efficiency. Among several others, several simple solutions with Cellular Automata (CA) were presented by researchers to simulate and study the road-traffic scenarios. In this regard, we presented a systematic study toward CA-based road traffic modelling targeting truly cost-effective physical modelling in view of Smart City applications. Presented study examines several CA rules with respect to its dynamics observed at different CA boundary conditions and efficiently identify the compatible CA rules toward the modelling for a true cost-effective road-traffic simulation in Smart City scenario.KeywordsSmart cityRoad-traffic modellingCellular automata (CA)CA dynamicsCost-effective modellingGreen computing
This article explores the state estimation problem for heterogeneous traffic (a multi-class flow composed of vehicles with distinct sizes and driving behaviours) using particle filtering (PF) approaches. We consider three enhanced variations of the bootstrap PF to improve estimation. The benchmark PF utilises a deterministic partial differential equation and an additive process noise that is state-independent. For the enhanced variations we first consider a parameter-adaptive PF that also allows model parameters to be adjusted. The second variation is a standard PF with spatially-correlated noise. The last variation combines parameter-adaptive and the spatially-correlated-noise approaches. We compare the four filters in numerical experiments that represent complex heterogeneous traffic scenarios, as well as on real-world heterogeneous traffic data. The results show that the enhanced filters can achieve up to an 80% and 46% of accuracy improvement as compared to an open loop simulation without measurement correction, with the synthetic settings and with real traffic data, respectively. Moreover, the enhanced filters outperform the standard PF in all the traffic scenarios based on accuracy.
This paper comprehensively reviews driving behaviour in the context of heterogeneous traffic and poor lane discipline condition. Organizing such driving behaviour models into two main groups (lateral movement model and longitudinal movement model), the systematic review primarily focusses on chronological development of the studies, intricate components of modelling framework (input and output variables, their selection procedure, methodology, calibration and validation) and strength and limitations of each model. In addition, the models are also scrutinized to determine to what extent they are applicable to capture the complex interaction of various vehicle types in poor or no lane discipline condition. Finally, the state-of-the-art is compared with the universal modelling requirement to pinpoint the research gap, provide appropriate direction to bridge the gap and develop a comprehensive model of driving behaviour in heterogeneous and non-lane-based traffic condition.
Hydropower operation of multi-reservoir systems is very difficult to solve mostly due to their nonlinear, nonconvex and large-scale nature. While conventional methods are long known to be incapable of solving these types of problems, evolutionary algorithms are shown to successfully handle the complexity of these problems at the expense of very large computational cost, particularly when population-based methods are used. A novel hybrid cellular automata-simulated annealing (CA-SA) method is proposed in this study which avoids the shortcomings of the existing conventional and evolutionary methods for the optimal hydropower operation of multi-reservoir systems. The start and the end instances of time at each operation period is considered as the CA cells with the reservoir storages at these instances are taken as the cell state which leads to a cell neighborhood defined by the two adjacent periods. The local updating rule of the proposed CA is derived by projecting the objective function and the constraints of the original problem on the cell neighborhoods represented by an optimization sub-problem with the number of decision variables equal to the number of reservoirs in the system. These sub-problems are subsequently solved by a modified simulated annealing approach to finding the updated values of the cell states. Once all the cells are covered, the cell states are updated and the process is iterated until the convergence is achieved. The proposed method is first used for hydropower operation of two well-known benchmark problems, namely the well-known four- and ten-reservoir problems. The results are compared with the existing results obtained from cellular automata. Genetic algorithm and particle swarm optimization indicating that the proposed method is much more efficient than existing algorithms. The proposed method is then applied for long-term hydropower operation of a real-world three-reservoir system in the USA, and the results are presented and compared with the existing results.
This paper is to discuss different simulation models that are used to measure traffic flow, their structure, assumptions, limitations and insights gained from them.
In multi-class disordered traffic conditions, the presence of numerous classes of vehicles having different size and operational characteristics invalidates the behaviour of lane discipline. Each vehicle traverses through a series of both viable as well as accessible gaps created by other vehicles, thus defining a permeable medium. In this paper a plausible way to incorporate the disordered behaviour on macroscopic traffic stream modelling is discussed. A new metric termed as traversable distance has been formulated for characterising this behaviour, based on field observations. Based on class-specific traversable distances that correspond to a set of incommensurate density measures, equilibrium speed functions have been redefined. Disordered stream behaviour significantly affects the scatter in the equilibrium speed-density relationship which is a key input to macroscopic traffic flow models. Results from the modified speed functions based on traversable distance proved that the proposed methodology could considerably explain the scatter observed in the fundamental diagram.
The traffic flow prediction using cellular automata (CA) is a trendy research domain that identified the potential of CA in modelling the traffic flow. CA is a technique, which utilizes the basic units for describing the overall behaviour of complicated systems. The CA model poses a benefit for defining the characteristics of traffic flow. This paper proposes a modified CA model to reveal the prediction of traffic flows at the signalised intersection. Based on the CA model, the traffic density and the average speed are computed for studying the characteristics and spatial evolution of traffic flow in signalised intersection. Moreover, a CA model with a self-organizing traffic signal system is devised by proposing a new optimization model for controlling the traffic rules. The Sunflower Cat Optimization (SCO) algorithm is employed for efficiently predicting traffic. The SCO is designed by integrating the Sunflower optimization algorithm (SFO) and Cat swarm optimization (CSO) algorithm. Also, the fitness function is devised, which helps to guide the control rules evaluated by traffic simulation using the CA model. Thus, the cellular automaton is optimized using the SCO algorithm for predicting the traffic flows. The proposed Sunflower Cat Optimization-based cellular automata (SCO-CA) outperformed other methods with minimal travel time, distance, average traffic density, and maximal average speed.
Disorderly traffic streams are those that, simply stated, do not have parallel lines (or lanes) of vehicles but have vehicles distributed more haphazardly in the road space. Vehicles in such streams, while moving longitudinally, change their lateral positions frequently. Their trajectories have a more pronounced wander along the width or the lateral dimension as opposed to those vehicles that primarily move in lanes. This property of disorderly streams dictates that its mathematical models must admit two spatial dimensions (the longitudinal and the lateral). Further, the observed impact of road geometry features like width, curvature, etc., on stream behavior, irrespective of whether the stream is disorderly, also suggests that realistic models of traffic streams must describe the streams using two spatial dimensions. Unfortunately, most of the theories of traffic dynamics are one-dimensional—they only consider the longitudinal dimension. This paper, while describing many of the existing approaches to modelling vehicular traffic behavior builds a case for strengthening two-dimensional modelling approaches that are all, still in their infancy. Given the (1) large increase in computation and data handling capabilities over the last decade and (2) significant strides made in developing tools for observing traffic dynamics at scales and accuracy levels that were previously unimaginable, the authors believe the time has come to develop, calibrate and validate reasonable two-dimensional models of traffic dynamics.
In today’s time, there is a growing concern over managing the traffic on Indian roads. From smaller two or three-tier cities to big metropolitan cities, the traffic problem is prevalent. It is especially becoming more challenging day by day as there has been a vast shift of interest of people from public transit or non-motorized modes to private automobiles; the reason of this momentous change could be urbanization, economic growth of the country or the ease in the affordability of vehicle by an individual, nowadays. Recently, this concern has grabbed many researchers’ attention. From the pool of many possibilities, one solution could be to discourage the use of private automobiles through imposing some restrictions or providing such kind of neighborhood where a person feels constrained to use the private vehicle. There are plenty of studies available which have analyzed the correlation between land use parameters and trip length before; nonetheless, due to the peculiarity of land use development and mixed traffic conditions in India, it is not viable to implement those procedures without inculcating India’s characteristics. Through this study, we are making our best efforts, while keeping the Indian traits in mind, to find the impact of the built environment on the travel behavior of the people. Agartala capital of Tripura, a city in the northeastern part of India, has been selected for this case study. Models have been prepared with slightly modified indices, which encompass the anomaly of Indian land use development, for studying the effect of land use parameter in explaining the variability of trip length as well as the behavioral mode choice. The correlations unfolded through these models were found to be significant and could be used for planning of efficient urban transportation system. The modified indices, to no small extent, were satisfactory in explaining the pattern of the household travel behavior based on their neighborhood development.
Cellular automata (CA) being a simple and powerful analytical tool has been used in the present study for the analysis of heterogeneous traffic. Heterogeneous traffic comprises different types of vehicles having a wide range of static and dynamic characteristics. Moreover, the driving pattern in developing countries is without lane discipline. These factors added together make the analysis of heterogeneous traffic a cumbersome task. Hence, CA being a simple tool is used to analyse complex scenario. The concept of actual gap and perceived gap and movement according to perceived gap are proposed in the present study. It can be observed from the results that with the introduction of heterogeneity, the capacity value reduces drastically. Moreover, the introduction of slow moving vehicles reduces the stream speed to a great extent. The proposed model is validated using the flow and density data obtained from field.
Heterogeneous traffic as observed in several south Asian countries is characterized by complex interactions of widely varying vehicle types that do not follow lanes and with smaller vehicles filling any gaps available. This paper discusses on four main components of macroscopic simulation of traffic flow in the Indian traffic context. One of the prime component, namely the traffic flow model, is discussed in detail with respect to the continuum modelling approach.
As many inland waterways are becoming increasingly busy, it is important and useful to study the vessel traffic flow characteristics to improve inland waterborne transport efficiency and safety by means of traffic simulation. In this study, cellular automata (CA) were adopted to establish a vessel traffic flow model of a variable two-way inland waterway according to inland vessel characteristics, driving behavior, safety requirement, etc. Evolution rules for vessel movement, such as following, overtaking, and accelerating, in the waterway were discussed, where the minimum safe distance between vessels related to their speeds was taken into account. The CA simulation model was validated according to field data regarding the Grand Canal. Based on the simulation, the traffic characteristics of vessel traffic flow are similar to those of vehicles on the road, although there are some differences. The practical simulation model contributes to the understanding of inland waterway traffic flow.
Vehicles moving in a heterogeneous traffic stream with no-lane-discipline maintain certain lateral gaps with the adjacent vehicles/objects. These gaps vary due to the static and dynamic behavior of vehicles, and the stochastic nature of the driver behavior. Majority of the studies consider the lateral gaps to be either constant or linearly varying . However, empirical observations suggest that the logistic curve model can suitably represents this behavior. Besides, it was also observed that the gaps vary based on the speed and type of the passing/overtaking vehicles and the overtaken/passed vehicles. Therefore, the present study analyzed the implications of different lateral gap models with the help of a cellular automata (CA) based traffic simulation model. The results indicate that, the logistically distributed lateral gap model closely represents the field observed macroscopic traffic relations and the selection of the lateral gap model has a significant impact on the estimated capacities.
This paper aims to develop a simulation model for heterogeneous traffic using cellular automata (CA). A detailed description of the developed CA model used to simulate heterogeneous traffic is presented. Heterogeneous traffic comprises of vehicles of different static and dynamic characteristics. Therefore, the developed model should be capable enough to include the characteristics of different types of vehicles. The results of simulation depict that not only the model includes heterogeneous traffic characteristics but real traffic behavior is also taken care of. The developed model is calibrated and validated using distance headway–speed relationship obtained from field data.
The maneuvering of powered two-wheelers (PTWs) is non-lane-based, and the interactions between PTWs and other vehicles in mixed traffic are complex. The behavior of PTWs, particularly in developing countries, is not the same as that of passenger cars, which has been studied for several decades. This study contributes to the existing literature on PTWs in several ways. A real-world microscopic vehicle trajectory database has been digitalized from a video clip for a four-lane urban arterial in Taipei (Taiwan). From a modeling perspective, a dynamic discrete choice model is proposed to capture the lateral-shifting behaviors of PTWs in mixed traffic conditions. The model considers not only the positions of all surrounding vehicles but also riders’ perception of expected traffic conditions. The behavioral model is able to describe the sequential non-lane-based maneuvers of PTWs, including not following lane discipline, filtering, moving abreast of other vehicles in the same lane, oblique following, swerving, and overtaking from the same lane. The results indicate that a better model fit is obtained when taking into account the dynamic nature of the problem. The data and methods proposed have the potential to improve microscopic traffic simulation of mixed traffic with a large amount of PTWs. Practical applications are concerned with the improvement of road geometries and the definition of control strategies for mixed traffic flows. © National Academy of Sciences: Transportation Research Board 2019.
As more attention is focused on bicycles as a mode of transportation, there is a strong need to understand microscopic behaviors of bicyclists within urban traffic systems. To respond to these needs, a new approach to simulate bicyclists' riding behaviors on bike paths has been developed. This approach uses the concept of reactive and perceptive ranges to depict the behaviors of bicycle flows. A series of riding strategies widely adopted by bike riders is proposed. Using these strategies or rules, this study applies a continuous psychological-physiological force (PPF) model to simulate the bicycle riding patterns and the reactive and perceptive interactions of bicyclists. A set of controlled experiments and field observations is carried out to calibrate the simulated interactions derived from the PPF model. After validation, the PPF model is used further to produce simulated trajectories of bicyclists, and a fundamental diagram is developed. The fundamental diagram is consistent with that in field investigations and previous research reports. A sensitivity analysis is also carried out based on the simulated trajectories of bicyclists (going through a series of bike paths with different widths). The analysis demonstrates that the width of a bike path directly impacts the capacity of the path.With the increasing width of a bike path, the capacity (per unit width of the bike path) decreases. This is a result of the psychological and physiological interactions of bicyclists in response to bike paths with different widths. This result provides a good insight for the design of bike paths in the future.
In developing nations like India, majority of the urban roads are bi-directional in nature consisting of wide varieties of vehicles which follow weak lane discipline. The vehicular manoeuvers on such roads are complex due to higher lateral interaction between the vehicles moving in both directions. Analysis of such behaviour with the help of mathematical or analytical approach may not be so efficient. Hence, simulation has become an inevitable tool for analysis and interpretation of such complex vehicular interactions. Only few attempts have been made to model such traffic flow considering both longitudinal and lateral behaviour of vehicles. In the present study, an attempt has been made to develop a microscopic simulation model for mixed traffic on urban undivided roads using object oriented programming concepts. Influence area concept is used to identify the most influencing surrounding vehicles which affect the vehicular manoeuvers on these roads. The developed model is calibrated and validated using real world traffic data collected from two different cities located in Southern India. The developed model will be helpful for traffic engineers to experiment with different design configurations, control strategies and traffic flow conditions, and determine their impacts on the system.
Resumen Haciendo un análisis estadístico, este artículo muestra cómo se han aumentado las fatalidades por accidentes de tránsito en Colombia, reflejando un incremento año tras año. Se puede verificar que la población más vulnerable se encuentra en el rango de los 21 a los 30 años, tanto de hombres como de mujeres. Es importante analizar estas estadísticas para buscar una solución y lograr una disminución de fatalidades que actualmente tienen un costo muy alto para la sociedad y la economía colombiana. En los resultados analizados se ha evidenciado el aumento de la accidentalidad y fallecimiento de personas, lo que conduce a concluir que posiblemente no han sido efectivas las políticas gubernamentales para tratar de mitigar los elevados índices en cuestión. Palabras clave: Accidentalidad, Seguridad Vial, Tránsito. Abstract Through a detailed statistical analysis, this article show how is increasing the fatalities due to traffic accidents in Colombia. The loss of life, both men and women is reflected year after year and the most vulnerable population is in the range of 21 to 30 years. It is important to analyze these statistics to find the decrease in fatalities that currently have a very high cost for society and the Colombian economy. The results showed an increase in accidents and deaths, leading to the conclusion that government policies may have been ineffective in trying to mitigate the high rates in question.
El estudio de la frecuencia y la causalidad de los choques de tránsito en las vías públicas es un tema prominente debido a su impacto y costo a la sociedad. Cada año, de acuerdo con las estadísticas del extinto Fondo de Prevención Vial de Colombia, reemplazado por la Agencia Nacional de Seguridad Vial, en un promedio de 2 minutos y medio ocurre un accidente de tránsito, cada 10 minutos hay un herido y cada hora hay una víctima fatal, debido a la pobre seguridad vial que se presenta en el país. Los grupos de la población (son) especialmente vulnerables son: los jóvenes de 15 a 30 años, los peatones, los ciclistas y en los últimos 5 años, los motociclistas. Para Ferrer et al., (2013) no coinciden las cifras de accidentes y fatalidades que se manejan en Colombia por parte de la Policía Nacional, el Dane, y el Instituto de Medicina Legal
El exceso de velocidad, es la principal causa en la accidentalidad vial. El 89% de los accidentes de tránsito ocurren por falla humana, el 11% restante, ocurren por problemas mecánicos, factores climáticos y defectos en la carretera entre otros (Arias, 2006). La mayoría de accidentes de conductores, ocurren en un promedio de 5 minutos antes de llegar a su destino, ya que el conductor se relaja y por ende, disminuye la atención en la conducción del vehículo. (Arias, W., Colucci B. 2006)
Este artículo muestra el aumento en las fatalidades por accidentes de tránsito en Colombia, donde se refleja el incremento año tras año y la población más vulnerable se encuentra en el rango de los 21 a los 30 años, tanto de hombres como de mujeres. Es importante analizar estas estadísticas para hallar la disminución de fatalidades que tienen un costo muy alto para la sociedad colombiana.
Measurements on real traffic have revealed the existence of metastable states with very high flow. Such states have not been observed in the Nagel-Schreckenberg (NaSch) model which is the basic cellular automaton for the description of traffic. Here we propose a simple generalization of the NaSch model by introducing a velocity-dependent randomization. We investigate a special case which belongs to the so-called slow-to-start rules. It is shown that this model exhibits metastable states, thus sheding some light on the prerequisites for the occurance of hysteresis effects in the flow-density relation.
This paper proposes refined cellular automata (CA) rules, including anticipation effect, slow-to-start, lane change, and interaction among vehicles to explore the fundamental traffic features. Generalized definitions of traffic variables, in spatiotemporal sense, and a new concept of common unit (CU) for gauging non-identical vehicle sizes and various lane widths are presented. The simulation experiments are tested on a two-lane highway context. The effects of both stationary and slow-moving bottlenecks on global traffic are also examined. Vehicular trajectories, flow-occupancy, and spatiotemporal traffic patterns under deterministic and stochastic conditions are displayed. The results reveal noticeable traffic patterns with free flow, wide moving jam and synchronized flow phases. This study has demonstrated that the proposed refined CA models are capable of capturing the essential features of traffic flows.
Key Words: cellular automata (CA), moving bottleneck, stationary bottleneck, traffic patterns
We introduce a stochastic discrete automaton model to freeway traffic. Monte-Carlo simulations of the model show a transition from laminar traffic flow to start-stop-waves with increasing vehicle density, as is observed in real freeway traffic. For special cases analytical results can be obtained.
A model for one-dimensional traffic flow is developed, which is discrete in space and time. Like the cellular automaton model by Nagel and Schreckenberg [J. Phys. I 2, 2221 (1992)], it is simple, fast, and can describe stop-and-go traffic. Due to its relation to the optimal velocity model by Bando et al. [Phys. Rev. E 51, 1035 (1995)], its instability mechanism is of deterministic nature. The model can be easily calibrated to empirical data and displays the experimental features of traffic data recently reported by Kerner and Rehborn [Phys. Rev. E 53, R1297 (1996)].
One-dimensional traffic flow is simulated by a cellular-automaton-type discrete model. As we increase the car density, the model shows a phase transition between a jam phase and a non-jam phase. By adding random perturbations, we found a 1/f power spectrum in the jam phase, whereas a white noise is observed in the non-jam phase.
Increasing congestion due to rapid urbanization in developing countries like India necessitates the study of traffic flow for effective traffic management. Most of the traffic studies conducted in this regard were on the lines of methods used in developed countries. These studies were able to represent the traffic behavior only in a very limited manner. In developing countries traffic is composed of several types of vehicles ranging from cars with high speeds to low speed non-motorized vehicles. Microscopic traffic characteristics such as time headway and space headway are difficult to measure due to the heterogeneous nature (no lane discipline, and two or three small vehicles occupying one lane in lateral direction) of the traffic. Even using some of the macroscopic traffic characteristics such as density or occupancy, to study this kind of traffic may lead to erroneous results. Thus it is desirable to have a metric that can represent the heterogeneous nature of traffic in these conditions. Since varying vehicle dimensions are attributed to the lack of lane discipline, a modified measure of occupancy termed as Area occupancy is proposed in this paper. Like occupancy, area occupancy is also measured over time. This measure would also be able to consider the varying vehicle dimensions of the traffic. Based on field observations it is shown that area occupancy is more meaningful in representing the heterogeneous traffic when compared to occupancy.
Simple cellular automata models are able to reproduce the basic
properties of highway traffic. The comparison with empirical data for
microscopic quantities requires a more detailed description of the
elementary dynamics.
Based on existing cellular automata models, we propose an improved discrete
model incorporating anticipation effects, reduced acceleration capabilities
and an enhanced interaction horizon for braking. The modified model is
able to reproduce the three phases (free-flow, synchronized, and
stop-and-go) observed in real traffic. Furthermore we find a good
agreement with detailed empirical single-vehicle data in all phases.
This paper attempts to develop a particle-hopping model with pre-assigned cellular automata rules to describe the motorbikes' moving behaviors in a mixed traffic flow with cars and motorbikes on 2.5-meter (case I) and 3.75-meter (case II) lanes. Based on the field observation, possible relative positions for a motorbike (or car) and its surrounding vehicles are identified. Given the initial conditions and rules to updating the vehicles' speeds and positions, we use the proposed model to simulate the vehicles' moving trajectories over time. It is found that our model can reasonably describe the motorbike behaviors interacted with other vehicles (cars and motorbikes) in the mixed traffic. The maximum flow rates correspond to the cell occupancy (a proxy of density) of 0.17 to 0.3. Under pure motorbike condition, the maximum flow rates for cases I and II are 5,600 and 8,300 vph, respectively. We also find that the motorbike equivalents (me) range from 2.63 to 5.27 for 10%~100% of car mixes. For pure car flows, the average (me) values are 3.12 (pce= 0.33) and 4.5 (pce=0.22) for case I and case II, respectively.
Microscopic modeling of multi-lane traffic is usually done by applying heuristic lane changing rules, and often with unsatisfying results. Recently, a cellular automaton model for two-lane traffic was able to overcome some of these problems and to produce a correct density inversion at densities somewhat below the maximum flow density. In this paper, we summarize different approaches to lane changing and their results, and propose a general scheme, according to which realistic lane changing rules can be developed. We test this scheme by applying it to several different lane changing rules, which, in spite of their differences, generate similar and realistic results. We thus conclude that, for producing realistic results, the logical structure of the lane changing rules, as proposed here, is at least as important as the microscopic details of the rules.
The cellular automata (CA) approach to traffic modeling is extended to allow for spatially homogeneous steady state solutions that cover a two dimensional region in the flow-density plane. Hence these models fulfill a basic postulate of a three-phase traffic theory proposed by Kerner. This is achieved by a synchronization distance, within which a vehicle always tries to adjust its speed to the one of the vehicle in front. In the CA models presented, the modelling of the free and safe speeds, the slow-to-start rules as well as some contributions to noise are based on the ideas of the Nagel-Schreckenberg type modelling. It is shown that the proposed CA models can be very transparent and still reproduce the two main types of congested patterns (the general pattern and the synchronized flow pattern) as well as their dependence on the flows near an on-ramp, in qualitative agreement with the recently developed continuum version of the three-phase traffic theory [B. S. Kerner and S. L. Klenov. 2002. J. Phys. A: Math. Gen. 35, L31]. These features are qualitatively different than in previously considered CA traffic models. The probability of the breakdown phenomenon (i.e., of the phase transition from free flow to synchronized flow) as function of the flow rate to the on-ramp and of the flow rate on the road upstream of the on-ramp is investigated. The capacity drops at the on-ramp which occur due to the formation of different congested patterns are calculated. Comment: 55 pages, 24 figures
Mixed-traffic streams that contain motorized and nonmotorized vehicles are becoming more common in urban areas. These streams contain standard vehicle types such as private cars, buses, and trucks, as well as nonstandard vehicles such as bicycles, motorcycles, and other vehicular forms. Models suitable for analysis of such streams hardly exist, and most available models are limited in scope and effectiveness. Analysis of mixed streams that use traditional approaches has achieved limited success and has involved much recalibration effort and significant model modifications. Effective analysis of these streams therefore inevitably requires new models to be developed that use different approaches. Aspects of a model developed specifically for mixed streams are presented. This model covers different vehicle types, including nonmotorized ones, and allows for some special behaviors, such as seepage to fronts of queues by two-wheeled vehicles and simultaneous use of two lanes. In addition to nor. mal car-following rules, the model incorporates lateral movement with a gradual lane change maneuver (as opposed to an instantaneous one), the decisions of which are governed by fuzzy logic rules. The model was calibrated and tested with data from Nairobi, Kenya, and its predictions were found to be in close agreement with the field data. In addition to its being a normal traffic management tool, the model makes a significant contribution to the study of the influence of nonstandard vehicle types or behavior on traffic performance.
In order to study mixed traffic in a comprehensive manner, a computer simulation model has been developed and tested. The model was run a number of times for different traffic volumes and a varying percentage mix of the different types of vehicles which make up the stream. Speed-flow models have been developed on the basis of these results and these help in understanding the problems of interactions between vehicles in the stream. Finally, service volumes for three different levels of service have been derived and from these it has been possible to derive Passenger Car Units (PCU) relative to a Western passenger car which is considered as the Design Vehicle Unit (DVU). -from AuthorEnglish
We investigate two models for traffic flow with modified acceleration (‘slow-to-start’) rules. Even in the simplest case vmax = 1 these rules break the ‘particle-hole’ symmetry of the model. We determine the fundamental diagram (flow-density relationship) using the so-called car-oriented mean-field approach (COMF) which yields the exact solution of the basic model with vmax = 1. Here we find that this is no longer true for the models with modified acceleration rules, but the results are still in good agreement with simulations. We also compare the effects of the two different slow-to-start rules and discuss their relevance for real traffic. In addition, in one of these models we find a new phase transition to a completely jammed state.
A Cellular Automaton is a extremely simplified program for the simulation of complex transportation systems, where the performance velocity is more important than the detailed model accuracy. The first application of the Cellular Automaton for simulation of traffic flows on streets and highways was introduced by Nagel and Schreckenberg [7]. The basic Cellular Automaton model from Nagel-Schreckenberg has been checked against measurements of realistic traffic flow on urban streets and motorways in Germany. It was found that the measured capacities on German motorways cannot be reproduced very well. On urban streets, however, it was very well possible to represent traffic patterns at intersections. The paper describes a completely new concept for the cellular automaton principle to model highway traffic flow. This model uses a time-oriented car-following model. This model accounts for the real driving behavior more precisely than the model from Nagel and Schreckenberg. This paper shows that a Cellular Automaton is generally applicable for simulation of traffic flows. The degree of correspondence with reality depends on the applied car-following model. The new model concept combines realistic modeling with fast computational performance.
This paper describes a modeling methodology adopted to simulate the flow of heterogeneous traffic with vehicles of wide ranging static and dynamic characteristics. The simulation framework for the traffic-flow model was prepared in such a way that the absence of lane discipline in mixed traffic flow conditions is taken into account. A detailed structure of the proposed model is presented. Common issues related to traffic simulation such as vehicle generation, logics for vehicular movement, etc., are described in detail in the context of heterogeneous traffic conditions. The paper also discusses the procedures adopted for validation of the proposed model and their outcomes. Finally, the details of application of the model to study the traffic flow characteristics on urban roads are also presented. Journal of Transportation Engineering
Mixed-traffic streams that contain motorized and nonmotorized vehicles are becoming more common in urban areas. These streams contain standard vehicle types such as private cars, buses, and trucks, as well as nonstandard vehicles such as bicycles, motorcycles, and other vehicular forms. Model suitable for analysis of such streams hardly exist, and most available models are limited in scope and effectiveness. Analysis of mixed streams that use traditional approaches has achieved limited success and has involved much recalibration effort and significant model modifications. Effective analysis of these streams therefore inevitably requires new models to be developed that use different approaches. Aspects of a model developed specifically for mixed streams are presented. This model covers different vehicle types, including nonmotorized ones, and allows for some special behaviors, such as seepage to fronts of queues by two-wheeled vehicles and simultaneous use of two lanes. In addition to normal car-following rules, the model incorporates lateral movement with a gradual lane change maneuver (as opposed to an instantaneous one), the decisions of which are governed by fuzzy logic rules. The model was calibrated and tested with data from Nairobi, Kenya, and its predictions were found to be in close agreement with the field data. In addition to its being a normal traffic management tool, the model makes a significant contribution to the study of the influence of nonstandard vehicle types or behavior on traffic performance.
A microscopic theory of spatial–temporal congested traffic patterns in heterogeneous traffic flow with a variety of driver behavioural characteristics and vehicle parameters is presented. A microscopic model for heterogeneous traffic flow is developed based on three-phase traffic theory. Diverse congested pattern features at a freeway bottleneck due to an on-ramp in heterogeneous traffic flow on a two-lane freeway are found. A numerical study of these specific pattern features and their comparison with empirical results are performed. A comparison of congested patterns in heterogeneous traffic flow with congested patterns in traffic flow with identical vehicles is made.
Heterogeneous traffic streams containing motorized and non-motorized vehicles are becoming more common in urban areas all over the world. These streams contain both conventional vehicle types such as private cars, buses and trucks as well as non-conventional types namely, bicycles, motorcycles and other vehicular forms, some of which also exhibit peculiar traffic behavior. In order to plan for such traffic it is important to understand the roles the vehicle types plays either individually or collectively on the traffic performance. Using a special model developed by author and aspects of which have been previously published in the TRR series, this study investigates the effects of various non-conventional vehicles on stream performance including lane capacity and saturation flows. It was found that such heterogeneous streams had reduced link capacities and lane saturation flows in comparison to homogenous flows with private cars only, although the trends were not always consistent. Moreover, it was found that the presence of some of these vehicles resulted in a highly scattered volume, speed density plots, which hardly corresponded with the known fundamental traffic relationships. It was therefore concluded that such heterogeneous streams have peculiar flows that may not conform fully to the basic traffic theories and hence may require further research to characterize.
This paper develops inhomogeneous cellular automata models to elucidate the interacting movements of cars and motorcycles in mixed traffic contexts. The car and motorcycle are represented by non-identical particle sizes that respectively occupy 6×2 and 2×1 cell units, each of which is 1.25×1.25 meters. Based on the field survey, we establish deterministic cellular automata (CA) rules to govern the particle movements in a two-dimensional space. The instantaneous positions and speeds for all particles are updated in parallel per second accordingly. The deterministic CA models have been validated by another set of field observed data. To account for the deviations of particles’ maximum speeds, we further modify the models with stochastic CA rules. The relationships between flow, cell occupancy (a proxy of density) and speed under different traffic mixtures and road (lane) widths are then elaborated.
Keywords: Car; Inhomogeneous cellular automata; Mixed traffic; Motorcycle
A set of lane changing rules for cellular automata simulating multi-lane traffic is proposed. It reproduces qualitatively that the passing lane becomes more crowded than the one for slower cars if the flux is high enough, which is true for motorways in countries like Germany where passing should be done on a specified lane as a rule. The rules have two parameters allowing to adjust the inversion point of the lane usage distribution and to calibrate the model. 1 Introduction It is an interesting and intriguing question in physics how microscopic and macroscopic description of a given system are related to each other. Often, one has a correct microscopic description of the system under consideration. However, in order to get a macroscopic description one has to make some compromises due to the 1 enormous number of degrees of freedom one has microscopically. The best example of this can be found in the realm of statistical mechanics, where the laws of motion of the atoms and molec...
A fast simulation model for the dynamic process of traffic flow through urban networks is presented. The model simulates the progression of cars on a street by moving 1 bit variables through binary positions of bytes in the storage which are arranged to copy the topology of a specified network. Skillful application of boolean operations enable the model to perform diverse movements of a vehicle like driving at a constant speed, lane changing, passing, decelerating and accelerating, queueing and turning at intersections. The model simulates accurately macroscopic phenomena of traffic flow while at the same time reproducing the main mechanisms of microscopic models. The computational requirements are rather low with respect to both storage and computation time making it possible to simulate large traffic networks on personal computers.
We develop particle-hopping models of two-lane traffic with two different types of vehicles (characterized by two different values of the maximum allowed speed Vmax) generalizing the Nagel-Schrecknnberg stochastic cellular-automata model for single-lane traffic with a single Vmax. The simplest of the two models is symmetric with respect to the two lanes as well as with respect to the two types of vehicles. In the asymmetric model, different rules govern the changing from the the “fast” lanes to the “slow” one and the reverse process. Moreover, in the asymmetric model, the drivers of fast vehicles can anticipate, often well in advance, the possibility of getting trapped behind a slow vehicle and tend to avoid such possibilities.
For single-lane traffic models it is well known that particle disorder leads
to platoon formation at low densities. Here we discuss the effect of slow cars
in two-lane systems. Surprisingly, even a small number of slow cars can
initiate the formation of platoons at low densities. The robustness of this
phenomenon is investigated for different variants of the lane-changing rules as
well as for different variants on the single-lane dynamics. It is shown that
anticipation of drivers reduces the influence of slow cars drastically.
We examine a simple two lane cellular automaton based upon the single lane CA
introduced by Nagel and Schreckenberg. We point out important parameters
defining the shape of the fundamental diagram. Moreover we investigate the
importance of stochastic elements with respect to real life traffic.
Experimental investigations of a complexity in traffic flow are presented. It is shown that this complexity is linked to space-time transitions between three qualitative different kinds of traffic: ``free'' traffic flow, ``synchronized'' traffic flow, and traffic jams. Peculiarities of ``synchronized'' traffic flow and jams that are responsible for a complex behavior of traffic are found.
We systematically investigate the effect of blockage sites in a cellular automaton model for traffic flow. Different scheduling schemes for the blockage sites are considered. None of them returns a linear relationship between the fraction of ``green'' time and the throughput. We use this information for a fast implementation of traffic in Dallas. Comment: 12 pages, 18 figures. submitted to Phys Rev E
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