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Urban traffic emissions have significant environmental and health implications. Diverging from traditional research that primarily aims to improve traffic flow and efficiency, this study specifically focuses on the environmental impact on traffic emissions, conducting a comprehensive analysis within the Manhattan urban network through four route guidance strategies. The performance of these strategies is examined across various vehicle densities, and their impact on four traffic pollutant emissions (Carbon-dioxide, Nitrogen Oxides, Volatile Organic Compounds and Particulate Matter) is assessed. Moreover, our innovative approach analyzes emissions from the perspectives of both travel distance and trip frequency, placing special emphasis on trip frequency to provide practical insights with high real-world applicability. The results highlight the potential and limitation of the Congestion Coefficient Strategy. Under equal travel demands, the Congestion Coefficient Strategy showed promise in reducing carbon emissions. However, at lower vehicle densities, it led to a significant increase in emissions. This revelation pointed to the need for modifications to the strategy when applied in scenarios with lower traffic density. Recognizing this limitation, we introduced a modified strategy that achieved remarkable reductions in emissions across diverse vehicle densities, effectively overcoming the challenges posed by the original Congestion Coefficient Strategy. These findings offer valuable insights for policymakers and transportation planners in selecting optimal route guidance strategies to reduce pollutant emissions. Future studies will explore the efficacy of these strategies in road networks characterized by different topological configurations.

Traffic network design is a pivotal aspect of urban planning, necessitating a harmonious blend of theoretical and practical approaches. In this paper, we propose a novel network design methodology utilizing Delaunay triangulation. We address the limitations of raw Delaunay networks, particularly their triangular configurations, by introducing edge-reduction techniques guided by a newly developed metric, detour redundancy. This metric is instrumental in assessing edge importance, facilitating the transformation of the network to better mirror real-world traffic scenarios. The efficacy and practical application of the designed networks are then evaluated through traffic simulations using the principles of cellular automata. Our findings underscore the potential of this approach in enriching traffic network design and pave the way for future investigations into diverse network characteristics and their implications in urban environments.

This paper presents a day-to-day re-routing relaxation approach for traffic simulations. Starting from an initial planset for the routes, the route- based microsimulation is executed. The result of the microsimulation is fed into a re-router, which re-routes a certain percentage of all trips. This approach makes the traffic patterns in the microsimulation much more reasonable. Further, it is shown that the method described in this paper can lead to strong oscillations in the solutions.

An iterative algorithm to determine the dynamic user equilibrium with respect to link costs defined by a traffic simulation model is presented. Each driver's route choice is modeled by a discrete probability distribution which is used to select a route in the simulation. After each simulation run, the probability distribution is adapted to minimize the travel costs. Although the algorithm does not depend on the simulation model, a queuing model is used for performance reasons. The stability of the algorithm is analyzed for a simple example network. As an application example, a dynamic version of Braess's paradox is studied.

The variable speed limit (VSL) is a kind of active traffic management method. Most of the strategies are used in the expressway traffic flow control in order to ensure traffic safety. However, the urban expressway system is the main artery, carrying most traffic pressure. It has similar traffic characteristics with the expressways between cities. In this paper, the improved link transmission model (LTM) combined with VSL strategies is proposed, based on the urban expressway network. The model can simulate the movement of the vehicles and the shock wave, and well balance the relationship between the amount of calculation and accuracy. Furthermore, the optimal VSL strategy can be proposed based on the simulation method. It can provide management strategies for managers. Finally, a simple example is given to illustrate the model and method. The selected indexes are the average density, the average speed and the average flow on the traffic network in the simulation. The simulation results show that the proposed model and method are feasible. The VSL strategy can effectively alleviate traffic congestion in some cases, and greatly promote the efficiency of the transportation system.

The long-range dependence of Internet traffic has been experimentally observed. One issue in handling long-range dependent traffic is how to simulate random traffic data with long-range dependence. The authors discuss a correlation-based simulator with a white noise input for generating long-range dependent traffic data. With the real TCP traffic traces, a simulation model of TCP arrival traffic is empirically developed and the experimental results are satisfactory.

The rise of socio-technical systems in which humans interact with various forms of Artificial Intelligence, including assistants and recommenders, multiplies the possibility for the emergence of large-scale social behavior, possibly with unintended negative consequences. In this work, we discuss a particularly interesting case, i.e., navigation services’ impact on urban emissions, showing through simulations that the sum of many individually “optimal” choices may have unintended negative outcomes because such choices influence and interfere with each other on top of shared resources. To prove this point, we demonstrate how the introduction of a random component in the path suggestion phase may help to relieve the effect of collective and individual choices on the urban environment in terms of urban emissions.

This paper provides an introduction to multiagent traffic simulation. It includes some description of where we are with respect to the implementation of a real-world Berlin scenario. It turns out that the difficulties there, because of data availability and because of the special situation of Berlin after the reunification, are considerably larger than in previous scenarios that we have treated.

Recently, Chinese megacities have suffered serious air pollution. Previous studies have pointed out that transportation systems have become one of the major sources of air pollution and on-road pollutant concentrations are significantly higher than off-road. Electric vehicle (EV) introduction is proposed as a method to alleviate the current situation. In order to better understand the benefit of the use of EVs in Beijing, a simulation platform has been developed to evaluate the improvement of air quality with the use of EVs quantitatively within the selected area. Four scenarios with different EV penetration rates are proposed and the results revealed 5%, 10%, 15% EV penetration rates which will bring about improvement of 0.86%, 9.01% and 12.23% for PM2.5, 0.92%, 9.01% and 13.32% for nitrogen oxides (NO_x), 0.95%, 8.86% and 13.73% for CO, respectively. The results revealed a promising improvement of air quality with the introduction of EVs.

In this paper, two problems that exist in parking spot layout of bike-sharing which need to be solved are addressed. One is the size of parking spot, while another is the location of parking spot. First, the generation and attraction model of traffic travel is used to predict the usage requirements of bike-sharing, to acquire the parking requirements of bike-sharing. Then, we establish the best station spacing model to calculate the optimal quantity of parking spots. Moreover, the method of shortest distance clustering is applied to cluster the parking demand spots. Finally, the location optimization of bike-sharing parking spot is carried out by using gravity location model. In summary, the layout of bike-sharing parking spot is finished based on the abovementioned four steps.

This paper presents a simulation method of self-similar traffic and a type of TCP traffic simulators based on autocorrelation sequences. The impulse function of a simulator is carried out. The parameter estimations for modeling the impulse function of the simulator are determined by multidimensional nonlinear least squares fitting. The existence and the uniqueness of solutions for the multidimensional nonlinear least squares are proved based on convex analysis.

The urban expressway network is one of the city’s major traffic arteries. However, the urban road network near the overpass is the most congested area. Improving the traffic situation in this area has become an important issue. This paper presents a new real-time traffic estimation and prediction system, i.e., DynaCHINA which reproduces the traffic propagation by simulating the vehicle movement on the network. The improved mesoscopic traffic flow models are the key technologies that include some models such as static queuing model and the vehicle movement model. Moreover, a coordinated control approach is proposed to determine the traffic states by maximizing the total traffic flow of the network in the simulation period. Also, the variable speed limits can be implemented near the overpass area. The results demonstrated the feasibility of the models. In some cases, the proposed variable speed limits is an effective way to alleviate the traffic congestion in urban road networks.