Traffic congestion in urban areas presents a significant challenge to efficient transportation and sustainable urban development. This paper introduces a Neural Network based Route Guidance Strategy ...to address the non-linear complexities of urban traffic flow. The strategy demonstrates its capability to optimize traffic flow in real-time by predicting the travel times of candidate routes. A comprehensive simulation study compares the performance of the Neural Network Strategy with traditional traffic management strategies, focusing on traffic flow efficiency, vehicle count stability, and route choice optimization. The results indicate that the Neural Network Strategy significantly enhances traffic management by stabilizing vehicle counts, reducing fluctuations in traffic flux, and achieving a more uniform distribution of vehicles. The paper concludes with an analysis of the experimental results, highlighting the integration of neural networks into traffic management systems as a promising approach to mitigating urban traffic congestion. Future research directions are discussed, emphasizing the potential for real-world implementation and the exploration of advanced neural network models.
•Introduction of a Neural Network based Route Guidance Strategy for intelligent transportation systems.•Comprehensive simulation study comparing NNS with traditional traffic management strategies.•Significant improvements in traffic flow efficiency, vehicle count stability, and route choice optimization demonstrated.
Cooperative Intersection Management: A Survey Lei Chen; Englund, Cristofer
IEEE transactions on intelligent transportation systems,
02/2016, Letnik:
17, Številka:
2
Journal Article
Recenzirano
Intersection management is one of the most challenging problems within the transport system. Traffic light-based methods have been efficient but are not able to deal with the growing mobility and ...social challenges. On the other hand, the advancements of automation and communications have enabled cooperative intersection management, where road users, infrastructure, and traffic control centers are able to communicate and coordinate the traffic safely and efficiently. Major techniques and solutions for cooperative intersections are surveyed in this paper for both signalized and nonsignalized intersections, whereas focuses are put on the latter. Cooperative methods, including time slots and space reservation, trajectory planning, and virtual traffic lights, are discussed in detail. Vehicle collision warning and avoidance methods are discussed to deal with uncertainties. Concerning vulnerable road users, pedestrian collision avoidance methods are discussed. In addition, an introduction to major projects related to cooperative intersection management is presented. A further discussion of the presented works is given with highlights of future research topics. This paper serves as a comprehensive survey of the field, aiming at stimulating new methods and accelerating the advancement of automated and cooperative intersections.
Information extraction using distributed sensors has been widely used to obtain information knowledge from various regions or areas. Vehicle traffic data extraction is one of the ways to gather ...information in order to get the traffic condition information. This research intends to predict and visualize the traffic conditions in a particular road region. Traffic data was obtained from Department of Transport UK. These data are collected using hundreds of sensors for 24 h. Thus, the size of data is very huge. In order to get the behavior of the traffic condition, we need to analyze the huge dataset which was obtained from the sensors. The uses of conventional data mining methods are not sufficient to use, due to the process of knowledge building that should store data temporary in the memory. The fact that data is continuously becoming larger over time, therefore we need to find a method that could automatically adapt to process data in the form of streams. We use method called FIMT-DD (Fast Incremental Model Trees-Drift Detection) to analyze and predict the very large traffic dataset. Based on the prediction system that we have developed, we also visualize the prediction of traffic flow condition within generated sensor point in the real map simulation.
As autonomous vehicles and the other supporting infrastructures (e.g., smart cities and intelligent transportation systems) become more commonplace, the Internet of Vehicles (IoV) is getting ...increasingly prevalent. There have been attempts to utilize Digital Twins (DTs) to facilitate the design, evaluation, and deployment of IoV-based systems, for example by supporting high-fidelity modeling, real-time monitoring, and advanced predictive capabilities. However, the literature review undertaken in this paper suggests that integrating DTs into IoV-based system design and deployment remains an understudied topic. In addition, this paper explains how DTs can benefit IoV system designers and implementers, as well as describes several challenges and opportunities for future researchers.
Capturing the evolution mechanism of traffic dynamics is of great significance when alleviating traffic congestion and improving traffic efficiency. While several studies have presented stability ...analyses of various traffic systems, most have relied on linear analysis methods, which cannot capture the complex nonlinear dynamic behavior of heterogeneous traffic flow. To address this shortcoming, this paper derives a generic Hopf bifurcation structure that can be applied to multiclass traffic models. The proposed bifurcation structure is investigated to understand the characteristics of heterogeneous traffic flow in a connected and autonomous environment as case studies. The results, based on selected on-field calibrated traffic models, show that (1) the linear analysis results deviate significantly from the actual instability of the mixed traffic system, which illustrates the necessity of a bifurcation analysis; and (2) connected human-driven vehicles and connected autonomous vehicles have the ability to alleviate the formation and propagation of traffic oscillations. Finally, the theoretical analysis results are verified through simulation experiments.
•125 simulation tools for modeling electric vehicles and associated infrastructure are reviewed.•The tools’ capabilities are summarized and tabulated by source, availability, and ...application.•Applications considered include modeling of vehicles, traffic, and power distribution systems.•The advantages and limitations of particular tools in each application are summarized.
This paper presents a review of the many simulation tools that have been reported for modeling and managing the impact of electric vehicles on power distribution networks, and associated applications. One hundred and twenty-five simulation tools have been identified and among them sixty-seven tools have been summarized to facilitate selection of the most appropriate tools for specific tasks. Typical applications of the tools include vehicle system analysis and control, renewable energy and vehicle-to-grid integration and impact analysis, energy market behavior and charge scheduling, vehicle energy management, and traffic system simulation. No single tool covers all areas of these applications, however sufficient information is provided to enable researchers to select the most appropriate combination of tools to meet specific research objectives.
In this paper, we study mixed traffic systems that move along a single-lane ring-road or open-road. The traffic flow forms a platoon, which includes a number of heterogeneous human-driven vehicles ...(HDVs) together with only one connected and automated vehicle (CAV) that receives information from a subset of neighbors. The dynamics of HDVs are assumed to follow a general continuous-time nonlinear car-following model, which is a function of their velocity, spacing, and the relative velocity. The acceleration of the single CAV is also directly controlled by a dynamical output-feedback controller. The ultimate goal of this work is to present a robust control strategy that can smoothen the traffic flow in the presence of undesired disturbances (e.g. abrupt deceleration) and parametric uncertainties. A prerequisite for synthesizing a dynamical output controller is the stabilizability and detectability of the underlying system. Accordingly, a theoretical analysis is presented first to prove the stabilizability and detectability of the mixed traffic flow system. Then, two <inline-formula> <tex-math notation="LaTeX">H_\infty </tex-math></inline-formula> control strategies, with and without considering uncertainties in the system dynamics, are designed. The efficiency of the two control methods is subsequently illustrated through numerical simulations, and various experimental results are presented to demonstrate the effectiveness of the proposed controller to mitigate disturbance amplification and achieve platoon stability.
•We analyze the resilience of weighted networks.•We propose a measure of resilience based on shock propagation along network paths.•We introduce a condition for shock propagation based on the weights ...of the network.•We test the theoretical proposal on two real-world instances of air traffic systems.
Networks are at the core of modeling many engineering contexts, mainly in the case of infrastructures and communication systems. The resilience of a network, which is the property of the system capable of absorbing external shocks, is then of paramount relevance in the applications. This paper deals with this topic by advancing a theoretical proposal for measuring the resilience of a network. The proposal is based on the study of the shocks propagation along the patterns of connections among nodes. The theoretical model is tested on the real-world instances of two important airport systems in the US air traffic network: Illinois (including the hub of Chicago) and New York states (with JFK airport).
This paper discusses the application of coalitional model predictive control (MPC) to freeways traffic networks, where the goal is reducing the time spent by the drivers through a dynamic setting of ...variable speed limits (VSL) and ramp metering. The prediction model METANET is used to represent the traffic flows evolution. The system behavior and objective function lead to a non-convex and non-linear optimization problem, which can only be solved in a centralized fashion for small networks. The underlying motivation of this paper is the continued advance of clustering methods in the control of large-scale and spatially distributed systems. The global freeway system is partitioned into a set of coupled sub-stretches, which in turn are assigned to the different agents involved in the control problem. These local controllers can dynamically assemble into coalitions to take coordinated measures. In this work, a top-down approach is considered: the bottom layer consists of the set of controllers that compute the VSL and ramp-metering across time; and the supervisory layer changes periodically the information exchange structure to promote coalitions of those controllers that bring greater performance to the global system. In this way, a balance is sought between optimality and efficiency. Finally, the coalitional approach is simulated on a stretch of traffic freeway where cooperation with adjacent sub-stretches is allowed.
Open, irreversible, dynamically routed, zone-controlled guidepath-based transport systems model the operation of many automated unit-load material handling systems that are used in various production ...and distribution facilities. An important requirement for these systems is to preserve the system liveness-i.e., the ability of each system agent to reach any location of the underlying guidepath network-by blocking those traffic states that will result in deadlock and/or livelock. The remaining set of traffic states are characterized as "live." The worst-case computational complexity of the decision problem of assessing the state liveness in the considered class of transport systems is an open issue. As a first contribution of this paper, we identify an extensive subclass of these traffic states, defined through the topology of an abstracting graphical representation of the "traffic state" concept, for which the corresponding problem of liveness assessment admits a polynomial solution, and we present the relevant algorithm for this assessment. But the development of the aforementioned results has also led to a new methodological framework for representing and analyzing the qualitative dynamics of the considered transport systems with respect to the reachability and the liveness problems that are the focus of this paper. This framework can enable an effective and efficient (but maybe not polynomial-complexity) resolution of the state liveness even for those traffic states that do not belong in the primary state class that is considered in this paper; we highlight this additional possibility in the closing part of this paper.
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