Urban Traffic Model Research Articles

Including congestion effects in urban road traffic CO2 emissions modelling: Do Local Government Authorities have the right options?

Tailpipe emissions from vehicles on urban road networks have damaging impacts, with the problem exacerbated by the common occurrence of congestion. This article focuses on carbon dioxide because it is the largest constituent of road traffic greenhouse gas emissions. Local Government Authorities (LGAs) are typically responsible for facilitating mitigation of these emissions, and critical to this task is the ability to assess the impact of transport interventions on road traffic emissions for a whole network.This article presents a contemporary review of literature concerning road traffic data and its use by LGAs in emissions models (EMs). Emphasis on the practicalities of using data readily available to LGAs to estimate network level emissions and inform effective policy is a relatively new research area, and this article summarises achievements so far. Results of the literature review indicate that readily available data are aggregated at traffic level rather than disaggregated at individual vehicle level. Hence, a hypothesis is put forward that optimal EM complexity is one using traffic variables as inputs, allowing LGAs to capture the influence of congestion whilst avoiding the complexity of detailed EMs that estimate emissions at vehicle level.Existing methodologies for estimating network emissions based on traffic variables typically have limitations. Conclusions are that LGAs do not necessarily have the right options, and that more research in this domain is required, both to quantify accuracy and to further develop EMs that explicitly include congestion, whilst remaining within LGA resource constraints.

Outer Synchronization between Two Coupled Complex Networks and Its Application in Public Traffic Supernetwork

The paper presents a new urban public traffic supernetwork model by using the existing bus network modeling method, consisting of the conventional bus traffic network and the urban rail traffic network. We investigate the synchronization problem of urban public traffic supernetwork model by using the coupled complex network’s outer synchronization theory. Analytical and numerical simulations are given to illustrate the impact of traffic dispatching frequency and traffic lines optimization to the urban public traffic supernetwork balance.

Research on constructing urban green traffic system: the case of Shenzhen City

Traffic jam is a big problem, which influences people's normal travel, and causes environmental pollution. Green traffic can solve traffic problem effectively. By analysing the factors that affect traffic jams, the article builds cause-and-effect relation diagram and then builds stock-flow diagram. Then taking Shenzhen city as an example, make a simulation of the urban green traffic model system. The result shows that the number of private cars ownership and the increase of vehicle exhaust stock are important driving factors of traffic congestion and environmental pollution. By influencing the total of the private cars ownership, auto purchase limit policy, restrictions and congestion pricing policy control motor vehicle trips, reduce vehicle emissions, and balance automobile exhaust gas pollution problem. At the same time, adopt new energy vehicle subsidy policy to advocate the residents to buy new energy vehicles and improve public transport infrastructure to advocate people to take public traffic vehicle.

Research on constructing urban green traffic system: the case of Shenzhen City

Traffic jam is a big problem, which influences people's normal travel, and causes environmental pollution. Green traffic can solve traffic problem effectively. By analysing the factors that affect traffic jams, the article builds cause-and-effect relation diagram and then builds stock-flow diagram. Then taking Shenzhen city as an example, make a simulation of the urban green traffic model system. The result shows that the number of private cars ownership and the increase of vehicle exhaust stock are important driving factors of traffic congestion and environmental pollution. By influencing the total of the private cars ownership, auto purchase limit policy, restrictions and congestion pricing policy control motor vehicle trips, reduce vehicle emissions, and balance automobile exhaust gas pollution problem. At the same time, adopt new energy vehicle subsidy policy to advocate the residents to buy new energy vehicles and improve public transport infrastructure to advocate people to take public traffic vehicle.

Bilevel Programming Model for City Logistics Distribution Optimization under Time Restriction Caused by Traffic Organization

For the optimization of city logistics distribution under time restriction caused by traffic organization, a bilevel programming model considering the distribution cost, environment cost, and distribution time of enterprises is developed. The primary function of this upper-level model is to minimize the general cost of distribution enterprises and determine the scheme to optimize city logistics distribution. The lower-level model is the urban traffic equilibrium distribution model for analyzing the distribution route determined by choice behavior for the optimization scheme of city logistics distribution given by the upper-level model. Results indicate that the distribution time, distribution cost, and environment cost of distribution enterprises increased significantly, and that the income of distribution enterprises was reduced because of the traffic organization time window in the process of city logistics distribution. When a distribution task was required to be completed within the formulary time win...

Distance-Based Stable Routing Decision Scheme in Urban Vehicular Ad Hoc Networks

A number of ad hoc routing protocols of vehicular ad hoc network (VANET) have been proposed and evaluated based on mobile ad hoc network (MANET) routing protocols. Although a large number of routing protocols have been developed in MANET, the VANET has different environments such as highly dynamic topology, frequently disconnected network, hard delay constraints for safety-related application, and various communications environments (e.g., highway or urban traffic scenarios). Therefore, development of a suitable routing protocol that considers these characteristics of VANET should be needed. In this paper we suggest the improved distance-based VANET routing protocol compared with the previous researches on urban traffic environments. We apply approaches to packet-collisions avoidance scheme in the intersection and to stable route decision scheme based on the adaptive waiting time. The performance is then evaluated under simulation which is implemented with the Manhattan urban traffic model. The results show the improved performance as compared with the previous researches.

Research on urban public traffic network with multi-weights based on single bus transfer junction

Regarding single bus transfer junction as a research object, this paper constructs the urban traffic network models with multi-weights taking different bus lines in bus transfer junction as the network nodes, that is, the urban traffic network with multi-weights is given different properties weights at every edge. According to the method of network split, the complex network with multi-weights is split into several different single weighted complex networks. Then, we study the global synchronization of the new network model by changing congestion degrees, transfers coefficient and passenger flow density between different bus lines. Finally, analytical and simulated results are given to show the impact of different properties weights to the public traffic network balance.

Modelling urban traffic dynamics based upon the variational formulation of kinematic waves

This paper presents a dynamic traffic modelling framework based on the variational formulation of kinematic waves. We compare the effectiveness of this relatively recent numerical method with the traditional Godunov-based cell transmission method on various aspects including modelling shocks, dispersion of vehicle platoons, moving bottlenecks, and traffic characteristics with respect to real-world observations made in Central London, UK. The results suggest that the variational method is able to produce high-quality estimates both theoretically and empirically. This study opens up a new research direction in the area of urban traffic modelling and optimisation.

Research on Congestion Pricing in Multimode Traffic considering Delay and Emission

Rapid development of urbanization and automation has resulted in serious urban traffic congestion and air pollution problems in many Chinese cities recently. As a traffic demand management strategy, congestion pricing is acknowledged to be effective in alleviating the traffic congestion and improving the efficiency of traffic system. This paper proposes an urban traffic congestion pricing model based on the consideration of transportation network efficiency and environment effects. First, the congestion pricing problem under multimode (i.e., car mode and bus mode) urban traffic network condition is investigated. Second, a traffic congestion pricing model based on bilevel programming is formulated for a dual-mode urban transportation network, in which the delay and emission of vehicles are considered. Third, an improved mathematical algorithm combining successive average method with the genetic algorithm is proposed to solve the bilevel programming problem. Finally, a numerical experiment based on a hypothetical network is performed to validate the proposed congestion pricing model and algorithm.

Review of the Urban Traffic Modeling

Nowadays, the urban traffic modeling, which is helpful in planning and controlling the traffic system, has becoming a research hotspot of traffic engineering. After decades of research and development, there now exists hundreds of models choosing different modeling methods to simulate the traffic flow. It is important for us to understand these models by classifying them and analyzing their features. The features of traffic models, including the scalability, accuracy and computability, are becoming important indicators to measure their performance. In this paper, we introduce and compare some grounded models. In particular, we analyze the advantages and disadvantages of existing models, and classify them into three categories according their granularity: macroscopic, mesoscopic and microscopic models. http://dx.doi.org/10.11591/telkomnika.v12i11.6128

Traffic Demand Model to Study Urban Agglomeration Transportation System

The determination of traffic demand for urban transportation system is one of the core content of urban traffic planning, it is the basis for the traffic demand management strategy. First of all, the paper expounds the concept of urban agglomeration and features, on this basis, the traffic supply and traffic demand of urban agglomeration transportation system is analyzed. Second, according to land area for urban residents travel demand, according to the classification of goods transport industry production requirements were determined, thus to construct a system of urban agglomeration transportation traffic demand model.

Real-time urban traffic amount prediction models for dynamic route guidance systems

The route guidance system (RGS) has been considered an important technology to mitigate urban traffic congestion. However, existing RGSs provide only route guidance after congestion happens. This reactive strategy imposes a strong limitation on the potential contribution of current RGS to the performance improvement of a traffic network. Thus, a proactive RGS based on congestion prediction is considered essential to improve the effectiveness of RGS. The problem of congestion prediction is translated into traffic amount (i.e. the number of vehicles on the individual roads) prediction, as the latter is a straightforward indicator of the former. We thereby propose two urban traffic prediction models using different modeling approaches. Model-1 is based on the traffic flow propagation in the network, while Model-2 is based on the time-varied spare flow capacity on the concerned road links. These two models are then applied to construct a centralized proactive RGS. Evaluation results show that (1) both of the proposed models reduce the prediction error up to 52% and 30% in the best cases compared to the existing Shift Model, (2) providing proactive route guidance helps reduce average travel time by up to 70% compared to providing reactive one and (3) non-rerouted vehicles could benefit more from route guidance than rerouted vehicles do.

On a spatiotemporally discrete urban traffic model

In order to control urban traffic with model-based control methods, a proper traffic model is very important. This traffic control model needs to have enough descriptive power to reproduce relevant traffic phenomena, and it also has to be fast enough to be used in practice. Consequently, macroscopic urban traffic flow models are usually applied as control models. In this study, a macroscopic spatiotemporally discrete urban traffic model with a variable sampling time interval is proposed for model-based control strategies. By selecting proper sampling time intervals and sampling space distances, it allows us to balance modelling accuracy and computational complexity of the spatiotemporally discrete model. In addition, an urban traffic Courant-Friedrichs-Lewy (CFL) condition is deduced for spatiotemporally discrete urban traffic models, which is a sufficient condition to guarantee the discrete model to bear enough descriptive modelling power to reproduce necessary traffic phenomena. The model is analysed and evaluated based on the model requirements for control purposes. The simulation results are compared for the situations where the CFL condition is violated and not violated.

Measuring the Complexity of Self-Organizing Traffic Lights

We apply measures of complexity, emergence, and self-organization to an urban traffic model for comparing a traditional traffic-light coordination method with a self-organizing method in two scenarios: cyclic boundaries and non-orientable boundaries. We show that the measures are useful to identify and characterize different dynamical phases. It becomes clear that different operation regimes are required for different traffic demands. Thus, not only is traffic a non-stationary problem, requiring controllers to adapt constantly; controllers must also change drastically the complexity of their behavior depending on the demand. Based on our measures and extending Ashby’s law of requisite variety, we can say that the self-organizing method achieves an adaptability level comparable to that of a living system.

An Urban Traffic Flow Model to Capture Complex Flow Interactions among Lane Groups for Signalized Intersections

This paper presents a traffic flow model, based on cell transmission concept, to capture urban traffic dynamics taking into account complex flow interactions among lane groups at upstream of signalized intersections. This model is a simple and versatile simulation framework designed to simulate, at macroscopic level, more realistically the dynamic interaction of queues among neighboring lanes and intersections for large scale urban network. Model validation has been undertaken by comparing with Vissim results obtained in different scenarios that have been tested.

Evaluation of Urban Public Transportation Measures Considering the Reorganization of Existing Public Transport Network Using the Urban Traffic Simulation Model

When introducing a new transport system, the existing public transport network generally will be reorganized. However, in its planning stage, it may not be considered to reorganize the existing public transport network enough. Therefore, there is some possibility of not exactly measuring the benefits of the new transport system. In this study, the authors built an urban traffic simulation model which can reproduce the movement of cars, buses and trains, and the behavior of the passengers. Using this model, targeting the introduction of light rail transit (LRT) system in Kyoto, the authors make clear the differences of the general cost and social benefit by considering the reorganization of existing public transport network as well as the fare system.新たに都市内交通を整備する際、その区間と経路が重複する既存交通は、運行経路の短縮や変更などの路線再編がなされることが多い。しかし、計画評価段階においては、既存交通の再編が十分に考慮されず、新しい交通施策の導入による利用者の便益が正しく評価されていない可能性がある。本研究では、新規交通施策の事例として京都市におけるLRTの導入を考え、その際の既存交通再編の有無による社会的便益の違いを比較した。なお、分析をする際には、時々刻々と変化する、自動車、公共交通機関、公共交通利用者の動きを逐次再現したシミュレーションモデルを構築することにより、乗り換え回数の増加が利便性に与える影響などについても詳細に考慮した。分析の結果，新規交通施策の導入に合わせて、新たな運賃制度の導入を含めた既存路線の再編を行う場合において、最も大きな社会的便益が得られることを明らかにした。

Integrated Urban Traffic Control for the Reduction of Travel Delays and Emissions

Refining transportation mobility and improving the living environment are two important issues that need to be addressed in urban traffic. To reduce traffic delays and traffic emissions for urban traffic networks, this paper first proposes an integrated macroscopic traffic model that integrates a macroscopic urban traffic flow model with a microscopic traffic emission model for individual vehicles. This integrated model is able to predict the traffic flow states and the emissions released by every vehicle at different operational conditions, i.e., the speed and the acceleration. Then, model predictive control (MPC) is applied to control urban traffic networks based on this integrated traffic model, aiming at reducing both travel delays and traffic emissions of different gases. Finally, simulations are performed to assess this multiobjective control approach. The obtained simulation results illustrate the control effects of the model predictive controller.

Following Car Algorithm With Multi Agent Randomized System

We present a new Following Car Algorithm in Microscopic Urban Traffic Models which integrates some real-life factors that need to be considered, such as the effect of random distributions in the car speed, acceleration, entry of lane… Our architecture is based on Multi-Agent Randomized Systems (MARS) developed in earlier publications.

Privacy protection method for fine-grained urban traffic modeling using mobile sensors

With the ubiquitous nature of mobile sensing technologies, privacy issues are becoming increasingly important, and need to be carefully addressed. Data needs for transportation modeling and privacy protection should be deliberately balanced for different applications. This paper focuses on developing privacy mechanisms that would simultaneously satisfy privacy protection and data needs for fine-grained urban traffic modeling applications using mobile sensors. To accomplish this, a virtual trip lines (VTLs) zone-based system and related filtering approaches are developed. Traffic-knowledge-based adversary models are proposed and tested to evaluate the effectiveness of such a privacy protection system by making privacy attacks. The results show that in addition to ensuring an acceptable level of privacy, the released datasets from the privacy-enhancing system can also be applied to urban traffic modeling with satisfactory results. Albeit application-specific, such a “Privacy-by-Design” approach would hopefully shed some light on other transportation applications using mobile sensors.

Using Mobile Probe Data and the Macroscopic Fundamental Diagram to Estimate Network Densities

Recent advances in urban traffic network modeling have led to the proposal of several large-scale control strategies aimed at improving network efficiency, including metering vehicle entry, pricing network use, and allocating limited street space between multiple modes. However, these strategies typically require accurate real-time predictions of networkwide traffic conditions to be implemented, and it is often taken for granted that this information is available. In practice, this is not a trivial issue, because measuring traffic conditions across a large urban network in real time is not straightforward. For that purpose, this paper presents a method of indirectly estimating average vehicle densities across a network in real time by combining travel speed information from a few circulating probe vehicles with the macroscopic fundamental diagram (MFD) of urban traffic. The proposed method is advantageous because it requires relatively little data and involves few calculations. Tests of this methodology on a simulated network showed that the results were not accurate when the network was uncongested, but reliable density estimates could be obtained when the network was congested or approaching congestion, even if only a small fraction of vehicles served as probes. This result is promising because congested states are the most critical. Therefore, this methodology seems useful as a traffic-monitoring scheme to complement networkwide control strategies, provided that the network exhibits a well-defined and reproducible MFD.