Search

Automated Vehicles (AVs) are designed and programmed to follow traffic rules. However, there is no separate and comprehensive regulatory framework dedicated to AVs. The current Queensland traffic rules were designed for humans. These rules often contain open texture expressions, exceptions, and potential conflicts (conflict arises when exceptions cannot be handled in rules), which makes it hard for AVs to follow. This paper presents an automatic compliance checking framework to assess AVs behaviour against current traffic rules by addressing these issues. Specifically, it proposes a framework to determine which traffic rules and open texture expressions need some additional interpretation. Essentially this enables AVs to have a suitable and executable formalization of the traffic rules. Defeasible Deontic Logic (DDL) is used to formalize traffic rules and reasoning with AV information (behaviour and environment). The representation of rules in DDL helps effectively in handling and resolving exceptions, potential conflicts, and open textures in rules. 40 experiments were conducted on eight realistic traffic scenarios to evaluate the framework. The evaluation was undertaken both quantitatively and qualitatively. The evaluation result shows that the proposed framework is a promising system for checking Automated Vehicle interpretation and compliance with current traffic rules. [ABSTRACT FROM AUTHOR]

The article describes the problem of excessive traffic concentration at signalized pedestrian crossings. The main drawback of such crossings is the inappropriate duration of green signals for vehicles. Too long green times for vehicular traffic significantly increase time lost by pedestrians, while too short ones cause short-term congestion, resulting in long queues of vehicles and a deteriorated level of service. The negative effects of both of these situations also include dangerous behavior of road users, such as red light running or crossing. Recent (June 2021) changes in the road traffic law in Poland have privileged unprotected road users at pedestrian crossings. New models and technical and design standards proposed in this country (March 2021) recommend the installation of pedestrian priority crossings at particularly dangerous spots and in urban areas with a high proportion of pedestrian traffic. All this is done mainly for traffic-calming purposes. However, previously these measures were not a common practice in Poland. Therefore, the objective of this article was to develop a simple method of green signal timing, ensuring, firstly, priority to pedestrian traffic at such places, and, secondly, sustained capacity of vehicular traffic lanes. The developed models are practical, universal and easy to adapt in other countries. They ensure a very good or good quality of vehicle traffic service, with average lost time not exceeding 25 s in a vast majority of analyzed traffic level cases. The article also describes a traffic control algorithm dependent on traffic detection. [ABSTRACT FROM AUTHOR]

The article presents the initial experience (spring-summer 2023) of using artificial neural networks (ANN) in improving traffic management in the large Russian city of Tyumen. Using the example of one of the intersections of the city's road network, it is shown how much transport delays are reduced when the duration of the traffic light cycle phases is quickly adjusted to the actual traffic intensity when compared with the usual previously used traffic light predictive mode. For the specific intersection of Odesskaya and Kotovskogo streets in Tyumen, considered in this article, the traffic light control mode using an ANN can significantly (by 20.6 ... 22.4%) reduce the average delay time of vehicles. It is also important that the reduction in traffic delays, which is possible with the regulation of traffic using ANN, helps to reduce stress for road users and improve road safety. The article presents historical data illustrating the dynamics of changes in the field of traffic management and road safety in Tyumen. This information well confirms the thesis about the dialectic of systemic development and the need for a gradual increase in the intellectual component in traffic management in large cities. The Applications (Appendix A and Appendix B) present the code of the auxiliary procedures and functions module and the code of the main data collection module used to optimize the traffic light control mode at the experimental intersection of the Tyumen road network. The main conclusion of the study is that use of an ANN allows taking into account a much larger number of factors and optimizing the control of the entire object, consisting of several intersections, which is not achievable using predictive modes and local adaptive control. [ABSTRACT FROM AUTHOR]

Macroscopic traffic flow modeling is essential for describing and forecasting the characteristics of traffic flow. However, the classic Lighthill–Whitham–Richards (LWR) model only provides equilibrium values for steady‐state conditions and fails to capture common stochastic variabilities, which are a necessary component of accurate modeling of real‐time traffic management and control. In this paper, a stochastic LWR (SLWR) model that randomizes free‐flow speed is developed to account for the stochasticity incurred by the heterogeneity of drivers, while holding individual drivers' behavior constant. The SLWR model follows a conservation law of stochastic traffic density and flow and is formulated as a time‐dependent stochastic partial differential equation. The model is solved using a dynamically bi‐orthogonal (DyBO) method based on a spatial basis and stochastic basis. Various scenarios are simulated and compared with the Monte Carlo (MC) method, and the results show that the SLWR model can effectively describe dynamic traffic evolutions and reproduce some commonly observed traffic phenomena. Furthermore, the DyBO method shows significant computational advantages over the MC method. [ABSTRACT FROM AUTHOR]

Despite the fact that agent technologies have widely gained popularity in distributed systems, their potential for advanced management of vehicle traffic has not been sufficiently explored. This paper presents a traffic simulation framework based on agent technology and fuzzy logic. The objective of this framework is to act on the phase layouts represented by its sequences and length to maximize throughput and fluidize traffic at an isolated intersection and for the whole multi-intersection network, through both inter- and intra-intersection collaboration and coordination. The optimizing of signal layouts is done in real time, and it is not only based on local stream factors but also on traffic stream conditions in surrounding intersections. The system profits from agent communication and collaboration as well as coordination features, along with decentralized organization, to decompose the traffic control optimization into subproblems and enable the distributed resolution. Thus, the separate parts can be resolved rapidly by parallel tasking. It also uses fuzzy technology to handle the uncertainty of traffic conditions. An instance of the proposed framework was validated and designed in the ANYLOGIC simulator. Instantiation results and analysis denote that the designed system can significantly develop the efficiency at an individual intersection as well as in the multi-intersection network. It reduces the average travel delay and the time spent in the network compared to multi-agent-based adaptative signal control systems. [ABSTRACT FROM AUTHOR]

Congestion is an important issue in Internet of Things (IoT) networks with constrained devices and a growing number of applications. This paper investigated the problem of congestion control for burst traffic in such networks. We highlight the shortcomings of the current constrained application protocol (CoAP) in its inability to support burst traffic and rate control. Subsequently, we propose an analytical model for CoAP burst traffic and a new rate-control algorithm for CoAP to avoid congestion. A CoAP sender increases or decreases the transmission rate depending on the congestion detection. Using simulations, we compared the performance of the proposed algorithm with the current CoAP in various traffic scenarios. Experimental results show that the proposed algorithm is efficient for burst traffic and provides better performance in terms of delay, throughput, retransmission, packet duplication, and packet loss compared to CoAP. [ABSTRACT FROM AUTHOR]

In this paper, a new method is proposed to detect traffic regulations at intersections using GPS traces. The knowledge of traffic rules for regulated locations can help various location-based applications in the context of Smart Cities, such as the accurate estimation of travel time and fuel consumption from a starting point to a destination. Traffic regulations as map features, however, are surprisingly still largely absent from maps, although they do affect traffic flow which, in turn, affects vehicle idling time at intersections, fuel consumption, CO 2 emissions, and arrival time. In addition, mapping them using surveying equipment is costly and any update process has severe time constraints. This fact is precisely the motivation for this study. Therefore, its objective is to propose an automatic, fast, scalable, and inexpensive way to identify the type of intersection control (e.g., traffic lights, stop signs). A new method based on summarizing the collective behavior of vehicle crossing intersections is proposed. A modification of a well-known clustering algorithm is used to detect stopping and deceleration episodes. These episodes are then used to categorize vehicle crossing of intersections into four possible traffic categories (p1: free flow, p2: deceleration without stopping events, p3: only one stopping event, p4: more than one stopping event). The percentages of crossings of each class per intersection arm, together with other speed/stop/deceleration features, extracted from trajectories, are then used as features to classify the intersection arms according to their traffic control type (dynamic model). The classification results of the dynamic model are compared with those of the static model, where the classification features are extracted from OpenStreetMap. Finally, a hybrid model is also tested, where a combination of dynamic and static features is used, which outperforms the other two models. For each of the three models, two variants of the feature vector are tested: one where only features associated with a single intersection arm are used (one-arm model) and another where features also from neighboring intersection arms of the same intersection are used to classify an arm (all-arm model). The methodology was tested on three datasets and the results show that all-arm models perform better than single-arm models with an accuracy of 95% to 97%. [ABSTRACT FROM AUTHOR]

Context: From the perspective of marine traffic engineering, a system of port waterways is composed of a set of waterways (port areas), such as approach channels, port entrance, inner fairways (port channels, rivers, lakes), turning basins and port basins of various terminals. The sea waterway must be adjusted to the navigation of specific types of ships, characterized by length, breadth, draft and airdraft. The primary requirement for shipping in sea waterways is the safety of navigation. Each sea waterway has traffic restrictions for the ships using it. These restrictions are called conditions of sea waterway operation or conditions of ship operation in the sea waterway. Problem: There are a number of empirical, deterministic or probabilistic methods to determine the safe width of maneuvering areas on port waterways. The direct application of empirical methods to determine the conditions for the safe operation of ships on the complex waterway, such as the Świnoujście–Szczecin fairway, was impossible due to the complexity of the waterway and various restrictions on its individual parts. Method: The paper presents the assumptions and calculation procedure of a method allowing for the determination of maximum safe parameters of ships in existing complex waterways. Results: The proposed method was used in the preparation of port regulations for the dredged and widened Świnoujście–Szczecin waterway. The results of these calculations are presented as a practical application of the method. Conclusions: This article defines conditions for the safe operation of ships in complex port waterways systems and presents the methodology for determining maximum safe parameters of ships in existing complex port waterways systems. [ABSTRACT FROM AUTHOR]