184 research outputs found

    LimSim: A Long-term Interactive Multi-scenario Traffic Simulator

    Full text link
    With the growing popularity of digital twin and autonomous driving in transportation, the demand for simulation systems capable of generating high-fidelity and reliable scenarios is increasing. Existing simulation systems suffer from a lack of support for different types of scenarios, and the vehicle models used in these systems are too simplistic. Thus, such systems fail to represent driving styles and multi-vehicle interactions, and struggle to handle corner cases in the dataset. In this paper, we propose LimSim, the Long-term Interactive Multi-scenario traffic Simulator, which aims to provide a long-term continuous simulation capability under the urban road network. LimSim can simulate fine-grained dynamic scenarios and focus on the diverse interactions between multiple vehicles in the traffic flow. This paper provides a detailed introduction to the framework and features of the LimSim, and demonstrates its performance through case studies and experiments. LimSim is now open source on GitHub: https://www.github.com/PJLab-ADG/LimSim .Comment: Accepted by 26th IEEE International Conference on Intelligent Transportation Systems (ITSC 2023

    Assessing the Impact of Active Signage Systems on Driving Behavior and Traffic Safety

    Get PDF
    Unsignalized Stop-Controlled Intersections (SCI) are widely used in North America, and account for one out of every ten collisions. Understanding how drivers and pedestrians behave at unsignalized intersections is critical for public safety. Drivers who do not obey the stop-sign’s indication by not coming to a complete stop or miss or fail to stop at SCI create a substantial safety risk. For decades, visibility and placement of road alignments and signage at intersections have been a concern among transportation safety specialists. Deployment of backlit Light-Emitting Diode (LED) or other illuminated signs (also known as active road signs) has been increased especially at hot-spots and locations with known safety problems, or potential collision risks. While these signs are expected to improve safety measures by regulating safe travelers’ passage, their performance is not yet fully understood. Although environmental factors such as intersection type, location, and road design are playing a major role, compositional variables such as driver behaviour, which can be explained in terms of carelessness, lack of attention, or overconfidence, is resulting in a failure to comply with the law of making a complete stop at SCI. Previous empirical research demonstrated some correlation between several variables such as traveller compliance with road signs and alignments, direct and indirect road safety measures, collision/conflict frequency, and road/traffic characteristics. These studies commonly employ before-after or cross-reference analyses to determine the long-term effects of various countermeasures at SCI. A few studies also utilized calibrated micro-simulations models to evaluate the surrogate safety measures at SCI. This thesis defines a methodology to evaluate the safety performance of a new and untested signage without putting traffic at long risk. To evaluate the performance of the signs, the suggested methodology investigates multiple parameters and identifies influencing variables in a conflict-based collision-prediction model at SCI. The proposed methodology is applied to a real-world network in the city of Montreal, with several three-leg SCI equipped with different countermeasures. The experiment was designed in a fashion which isolates the influence of several variables, allowing the focus to be on the impact of the target variable (signage type). Field experiments have been performed to study the driver’s behavior in terms of approaching speed as well as quantitative analysis on reactions to various signs, using different sample groups from the same population. This research sets up a microsimulation model that captures drivers’ behaviour with respect to signage according to the observed data. A genetic algorithm was deployed to calibrate the microsimulation model in terms of turning movement counts and the critical conflicts were calculated at each intersection using vehicle trajectories. Collision-prediction regression models was then developed for the intersections under investigation, using traffic volume and conflict. The results demonstrated a high correlation among countermeasures and drivers’ speed and compliance. The relationship between critical conflicts computed in microsimulation models and actual collisions was found to be statistically significant. The model which includes drivers' compliance in collision-prediction regression was also found to fit the collision data better. However, the results of this study do not support the previous assumption that the conflict-based collision-prediction models fit the collision data better than the volume-based collision-prediction models at SCI, especially with drivers’ compliance supplementary data. Finally, while the backlit signs’ performance was marginally better than that of a normal LED active sign, the difference was not statistically significant. The methodology suggested in this thesis has the potential to be implemented in safety performance evaluation of a countermeasure without placing traffic at danger for an extended period. For instance, when there is apprehension about an adverse effect. Future research could investigate leveraging drivers’ behaviour to countermeasures, to improve the performance of collision-prediction regression models like the one proposed in this thesis. Finally, the results from the performance assessment of the LED active signs can assist transportation specialists in deciding whether or not to deploy these countermeasures

    Advances in Automated Driving Systems

    Get PDF
    Electrification, automation of vehicle control, digitalization and new mobility are the mega-trends in automotive engineering, and they are strongly connected. While many demonstrations for highly automated vehicles have been made worldwide, many challenges remain in bringing automated vehicles to the market for private and commercial use. The main challenges are as follows: reliable machine perception; accepted standards for vehicle-type approval and homologation; verification and validation of the functional safety, especially at SAE level 3+ systems; legal and ethical implications; acceptance of vehicle automation by occupants and society; interaction between automated and human-controlled vehicles in mixed traffic; human–machine interaction and usability; manipulation, misuse and cyber-security; the system costs of hard- and software and development efforts. This Special Issue was prepared in the years 2021 and 2022 and includes 15 papers with original research related to recent advances in the aforementioned challenges. The topics of this Special Issue cover: Machine perception for SAE L3+ driving automation; Trajectory planning and decision-making in complex traffic situations; X-by-Wire system components; Verification and validation of SAE L3+ systems; Misuse, manipulation and cybersecurity; Human–machine interactions, driver monitoring and driver-intention recognition; Road infrastructure measures for the introduction of SAE L3+ systems; Solutions for interactions between human- and machine-controlled vehicles in mixed traffic

    The Real Deal: A Review of Challenges and Opportunities in Moving Reinforcement Learning-Based Traffic Signal Control Systems Towards Reality

    Full text link
    Traffic signal control (TSC) is a high-stakes domain that is growing in importance as traffic volume grows globally. An increasing number of works are applying reinforcement learning (RL) to TSC; RL can draw on an abundance of traffic data to improve signalling efficiency. However, RL-based signal controllers have never been deployed. In this work, we provide the first review of challenges that must be addressed before RL can be deployed for TSC. We focus on four challenges involving (1) uncertainty in detection, (2) reliability of communications, (3) compliance and interpretability, and (4) heterogeneous road users. We show that the literature on RL-based TSC has made some progress towards addressing each challenge. However, more work should take a systems thinking approach that considers the impacts of other pipeline components on RL.Comment: 26 pages; accepted version, with shortened version published at the 12th International Workshop on Agents in Traffic and Transportation (ATT '22) at IJCAI 202

    Transport Systems: Safety Modeling, Visions and Strategies

    Get PDF
    This reprint includes papers describing the synthesis of current theory and practice of planning, design, operation, and safety of modern transport, with special focus on future visions and strategies of transport sustainability, which will be of interest to scientists dealing with transport problems and generally involved in traffic engineering as well as design, traffic networks, and maintenance engineers

    Optimización del diseño estructural de pavimentos asfálticos para calles y carreteras

    Get PDF
    gráficos, tablasThe construction of asphalt pavements in streets and highways is an activity that requires optimizing the consumption of significant economic and natural resources. Pavement design optimization meets contradictory objectives according to the availability of resources and users’ needs. This dissertation explores the application of metaheuristics to optimize the design of asphalt pavements using an incremental design based on the prediction of damage and vehicle operating costs (VOC). The costs are proportional to energy and resource consumption and polluting emissions. The evolution of asphalt pavement design and metaheuristic optimization techniques on this topic were reviewed. Four computer programs were developed: (1) UNLEA, a program for the structural analysis of multilayer systems. (2) PSO-UNLEA, a program that uses particle swarm optimization metaheuristic (PSO) for the backcalculation of pavement moduli. (3) UNPAVE, an incremental pavement design program based on the equations of the North American MEPDG and includes the computation of vehicle operating costs based on IRI. (4) PSO-PAVE, a PSO program to search for thicknesses that optimize the design considering construction and vehicle operating costs. The case studies show that the backcalculation and structural design of pavements can be optimized by PSO considering restrictions in the thickness and the selection of materials. Future developments should reduce the computational cost and calibrate the pavement performance and VOC models. (Texto tomado de la fuente)La construcción de pavimentos asfálticos en calles y carreteras es una actividad que requiere la optimización del consumo de cuantiosos recursos económicos y naturales. La optimización del diseño de pavimentos atiende objetivos contradictorios de acuerdo con la disponibilidad de recursos y las necesidades de los usuarios. Este trabajo explora el empleo de metaheurísticas para optimizar el diseño de pavimentos asfálticos empleando el diseño incremental basado en la predicción del deterioro y los costos de operación vehicular (COV). Los costos son proporcionales al consumo energético y de recursos y las emisiones contaminantes. Se revisó la evolución del diseño de pavimentos asfálticos y el desarrollo de técnicas metaheurísticas de optimización en este tema. Se desarrollaron cuatro programas de computador: (1) UNLEA, programa para el análisis estructural de sistemas multicapa. (2) PSO-UNLEA, programa que emplea la metaheurística de optimización con enjambre de partículas (PSO) para el cálculo inverso de módulos de pavimentos. (3) UNPAVE, programa de diseño incremental de pavimentos basado en las ecuaciones de la MEPDG norteamericana, y el cálculo de costos de construcción y operación vehicular basados en el IRI. (4) PSO-PAVE, programa que emplea la PSO en la búsqueda de espesores que permitan optimizar el diseño considerando los costos de construcción y de operación vehicular. Los estudios de caso muestran que el cálculo inverso y el diseño estructural de pavimentos pueden optimizarse mediante PSO considerando restricciones en los espesores y la selección de materiales. Los desarrollos futuros deben enfocarse en reducir el costo computacional y calibrar los modelos de deterioro y COV.DoctoradoDoctor en Ingeniería - Ingeniería AutomáticaDiseño incremental de pavimentosEléctrica, Electrónica, Automatización Y Telecomunicacione

    Evaluating Risks Associated With Automated Driving Systems

    Full text link
    Many countries are already testing automated driving systems (ADS) on public roads. Since original equipment manufacturers (OEMs) and technology firms invest billions of dollars in research and development, technology evolution is expeditious. However, the uptake is not as rapid as was forecasted five years ago. One reason is that the fundamental concern is still unresolved: Are Autonomous Vehicles (AVs) safe enough? This unresolved question adds urgency and the necessity to understand when AVs can be considered acceptably safe. Contrary to manual-driven vehicles (MVs), the safety of AVs cannot be solely determined by design specifications. Instead, safety incorporates the AV’s brain and behaviour. Thus, it expands into a realm formerly concerning not to the vehicle but to the proficiency of human drivers to drive safely in mixed traffic. Moreover, the road transport ecosystem will include other vehicles-primarily human-driven and pedestrians, bicyclists, and other road users in the foreseeable future. Hence, AVs must be proficient at interacting with elements of traffic safely. To put it simply, AVs will be considered safe when they can drive safely (without mishap) in mixed traffic on public roads. This thesis aims to explore different frameworks and approaches to evaluate risks associated with automated driving systems. The aims of the research are fulfilled through three objectives: understanding AV data and identifying the safety-related features from the data, exploring and developing methodologies for investigating the safety, and recognising the limitations of AV data for examining safety. Chapters 1 and 2 are introduction and literature review, respectively. Chapter 3 of this thesis analyses disengagement and crash data from the California Department of Motor Vehicles (CA DMV) and develops a crash severity model. Chapter 4 and 5 conducts a comprehensive safety assessment of the connected automated vehicle (CAV) deployed mixed Freeway and Urban traffic network, respectively. Results indicate that CAVs can improve safety and network performance. However, Pareto-optimality between network performance and traffic safety is identified using various CAV behaviours. Finally, chapter 6 explores AV field data (Waymo Open Dataset) to investigate AV behaviour. The results suggest that the mere presence of AVs could help reduce sudden braking and improve overall stability in the traffic flow due to higher variance in reaction times. Finally, the last chapter summarises significant findings, prospects of future research and final remarks

    Semi-Automated Microscopic Traffic Flow Simulation Development Using Smart City Data

    Get PDF
    Microscopic traffic simulation models have been widely used by transportation planners and engineers for conducting various road network planning and traffic engineering tasks. Due to data limitations, traffic simulation models are often calibrated based on macroscopic traffic measures. Recently, emerging smart city sensor technologies are enabling continuous collection of large volume, high-resolution trajectory data of road users, making it possible to estimate some behavioral parameters of traffic simulation models directly from these data. This research is intended to explore this opportunity with the objective of developing a methodology to estimate traffic simulation model parameters from smart city data with semi-automated calibration procedures. A comprehensive set of calibration procedures are proposed, including both direct methods of estimating parameters from data and indirect methods of estimating some parameters using an optimization algorithm. Most of the proposed procedures are designed in such a way that they can be completed in a semi-automated way using simple Python scripts. The developed methodology is illustrated in a case study involving the calibration of a VISSIM model using an available dataset of vehicle trajectories - NGSIM (Next Generation Simulation) traffic data. While most parameters can be estimated directly from the dataset, some parameters from the selected parameter set are determined using a neutral neural network. The modelling results suggest that the best performing parameter set generates less than 10% error relative to the field measurements in term of travel time and speed

    Mobile Ad Hoc Networks

    Get PDF
    Guiding readers through the basics of these rapidly emerging networks to more advanced concepts and future expectations, Mobile Ad hoc Networks: Current Status and Future Trends identifies and examines the most pressing research issues in Mobile Ad hoc Networks (MANETs). Containing the contributions of leading researchers, industry professionals, and academics, this forward-looking reference provides an authoritative perspective of the state of the art in MANETs. The book includes surveys of recent publications that investigate key areas of interest such as limited resources and the mobility of mobile nodes. It considers routing, multicast, energy, security, channel assignment, and ensuring quality of service. Also suitable as a text for graduate students, the book is organized into three sections: Fundamentals of MANET Modeling and Simulation—Describes how MANETs operate and perform through simulations and models Communication Protocols of MANETs—Presents cutting-edge research on key issues, including MAC layer issues and routing in high mobility Future Networks Inspired By MANETs—Tackles open research issues and emerging trends Illustrating the role MANETs are likely to play in future networks, this book supplies the foundation and insight you will need to make your own contributions to the field. It includes coverage of routing protocols, modeling and simulations tools, intelligent optimization techniques to multicriteria routing, security issues in FHAMIPv6, connecting moving smart objects to the Internet, underwater sensor networks, wireless mesh network architecture and protocols, adaptive routing provision using Bayesian inference, and adaptive flow control in transport layer using genetic algorithms
    corecore