Browse Topic: Urban mobility
The road network is a critical component of modern urban mobility systems, with signalized traffic intersections playing a pivotal role. Traditionally, traffic light phase timings and durations at intersections are designed by transportation engineers using historical traffic data. Some modern intersections employ trigger-based mechanisms to improve traffic flow; however, these systems often lack global awareness of traffic conditions across multiple intersections within a network. With the increasing availability of traffic data and advancements in machine learning, traffic light systems can be enhanced by modeling them as agents operating in an environment. This paper proposes a Reinforcement Learning (RL) based approach for multi-agent traffic light systems within a simulation environment. The simulation is calibrated using real-world traffic data, enabling RL agents to learn effective control strategies based on realistic scenarios. A key advantage of using a calibrated simulation
The U-Shift IV represents the latest evolution in modular urban mobility solutions, offering significant advancements over its predecessors. This innovative vehicle concept introduces a distinct separation between the drive module, known as the driveboard, and the transport capsules. The driveboard contains all the necessary components for autonomous driving, allowing it to operate independently. This separation not only enables versatile applications - such as easily swapping capsules for passenger or goods transportation - but also significantly improves the utilization of the driveboard. By allowing a single driveboard to be paired with different capsules, operational efficiency is maximized, enabling continuous deployment of driveboards while the individual capsules are in use. The primary focus of U-Shift IV was to obtain a permit for operating at the Federal Garden Show 2023. To achieve this goal, we built the vehicle around the specific requirements for semi-public road
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This project presents the development of an advanced Autonomous Mobile Robot (AMR) designed to autonomously lift and maneuver four-wheel drive vehicles into parking spaces without human intervention. By leveraging cutting-edge camera and sensor technologies, the AMR integrates LIDAR for precise distance measurements and obstacle detection, high-resolution cameras for capturing detailed images of the parking environment, and object recognition algorithms for accurately identifying and selecting available parking spaces. These integrated technologies enable the AMR to navigate complex parking lots, optimize space utilization, and provide seamless automated parking. The AMR autonomously detects free parking spaces, lifts the vehicle, and parks it with high precision, making the entire parking process autonomous and highly efficient. This project pushes the boundaries of autonomous vehicle technology, aiming to contribute significantly to smarter and more efficient urban mobility systems.
Artificial Intelligence (AI) has emerged as a transformative force across various industries, revolutionizing processes and enhancing efficiency. In the automotive domain, AI's adaption has ushered in a new era of innovation and driving advancements across manufacturing, safety, and user experience. By leveraging AI technologies, the automotive industry is undergoing a significant transformation that is reshaping the way vehicles are manufactured, operated, and experienced. The benefits of AI-powered vehicles are not limited to their manufacturing, operation, and enhancing the user experience but also by integrating AI-powered vehicles with smart city infrastructure can unlock much more potential of the technology and can offer numerous advantages such as enhanced safety, efficiency, growth, and sustainability. Smart cities aim to create more livable, resilient, and inclusive communities by harnessing innovation through technologies like Internet of Things (IoT), devices, data
The deployment of autonomous urban buses brings with it the hope of addressing concerns associated with safety and aging drivers. However, issues related autonomous vehicle (AV) positioning and interactions with road users pose challenges to realizing these benefits. This report covers unsettled issues and potential solutions related to the operation of autonomous urban buses, including the crucial need for all-weather localization capabilities to ensure reliable navigation in diverse environmental conditions. Additionally, minimizing the gap between AVs and platforms during designated parking requires precise localization. Next-gen Urban Buses: Autonomy and Connectivity addresses the challenge of predicting the intentions of pedestrians, vehicles, and obstacles for appropriate responses, the detection of traffic police gestures to ensure compliance with traffic signals, and the optimization of traffic performance through urban platooning—including the need for advanced communication
Ultrafine particles, in particular solid sub-100 nm particles pose high risks to human health due to their high lung deposition efficiency, translocation to all organs including the brain and their harmful chemical composition; due to dense traffic, the population in urban environments is exposed to high concentrations of those toxic air contaminants, despite these facts, they are still widely neglected. Therefore, the EU-Commission set up a program for clean and competitive solutions for different problem areas which are regarded to be hotspots of such particles. HORIZON AeroSolfd is an EU project, co-funded by Switzerland that will deliver affordable, adaptable, and sustainable retrofit solutions to reduce exhaust tailpipe emissions from petrol engines, brake emissions and pollution in semi-closed environments. VERT, a Swiss based international industry organization, has a long research history in the field of nanoparticle filtration and it is in charge of reducing tailpipe emissions
Electrification of transport, together with the decarbonization of energy production are suggested by the European Union for the future quality of air. However, in the medium period, propulsion systems will continue to dominate urban mobility, making mandatory the retrofitting of thermal engines by applying combustion modes able to reduce NOx and PM emissions while maintaining engine performances. Low Temperature Combustion (LTC) is an attractive process to meet this target. This mode relies on premixed mixture and fuel lean in-cylinder charge whatever the fuel type: from conventional through alternative fuels with a minimum carbon footprint. This combustion mode has been subject of numerous modelling approaches in the engine research community. This study provides a theoretical comparative analysis between multi-zone (MZ) and Transported probability density function (TPDF) models applied to LTC combustion process. The generic thermo-kinetic balances for both approaches have been
One-way car-sharing services (CSSs) are believed to be a promising transportation mode for urban mobility. Due to the disparity of city functional areas and population, travel demand and vehicle supply in a CSS may inevitably tend to be imbalanced as well. Therefore, an essential requirement of one-way CSSs is the capability of providing fleet management solutions to improve quality of service and system performance. In other words, a CSS depends heavily on technologies that offer strategic decisions on topics like Fleet sizing Location and capacity of depots and charging stations Matching of travelers with vehicles Relocation of vehicles and dispatchers for fleet rebalancing Balancing and charging schedules of electric vehicles Car-sharing Mobility-on-Demand Systems addresses trending CSS technologies and outlines some insights into the existing unsettled issues and potential solutions. The discussions and outlook are presented as a collection of key points encountered in system
This paper explores the efficacy and efficiency of a system for the effective location of electric gridlines during daytime and night-time by the onboard and offboard transceivers of UAV through vehicle to infrastructure communication. The usage of electric gridlines in urban areas helps to extend the range of the UAVs by charging the onboard battery using an extended arm. The same arm can also be used for direct propulsion of the motors onboard UAV, thereby minimizing the reliance on battery. UAVs with advanced Image processing algorithms are utilized in the inspection of the electric grid lines themselves in the Power industry. The camera based algorithms are not effective during night-time when the gridlines are near invisible. This can be mitigated by evaluating light in other spectral ranges, but this would add to the load of the UAV. We propose a system which combines multiple information sources and helps locate the gridlines for range extension, specifically for the delivery of
Urban air mobility (UAM) refers to urban transportation systems that move people by air. UAM offers the potential for reducing traffic congestion in cities and providing an integrated approach to urban mobility. With the emergence of electric vertical takeoff and landing (eVTOL) aircraft, drone technology, and the possibility of automated aircraft, interest in this topic has grown considerably for private sector solution providers—including aerospace and technology companies—as well as urban planners and transportation professionals. Unsettled Issues Concerning Urban Air Mobility Infrastructure discusses the infrastructure requirements to effectively integrate UAM services into the overarching urban transportation system to enable multimodal trips and complete origin to destination travel. Click here to access the full SAE EDGETM Research Report portfolio.
It has been predicted that the prevailing COVID-19 situation would result in increased demand for personal vehicles. There is a renewed interest in the 3 wheeled vehicles for short urban mobility in western countries due to their inherent cost advantages which will make it affordable for the common man. As the world is moving towards electric vehicle technology, a light 3 wheeled vehicle option will also help in reducing battery weight and thereby help in addressing the range concerns. In addition, slow speed 3-wheelers need not pass extensive safety regulation tests in many western countries including the USA. Three-wheeled vehicles are not new to developing countries like India as three-wheeled auto-rickshaws are quite popular for short distance shared travel. The existing single front wheel design known as delta design may have a stigma attached to it due to historic reasons in India. There is also a perception that the three-wheeled vehicles are highly unstable. Therefore, the
Advanced air mobility (AAM) refers to urban transportation systems that move people and goods by air. This has significant implications for reducing traffic congestion in cities and for providing an integrated approach to urban mobility. With the emergence of drone technology and the possibility of more autonomous aircraft, interest has grown considerably in AAM. Unsettled Issues in Advanced Air Mobility Certification discusses the impact of AAM on private sector solution providers including aerospace and technology companies and goes into solutions for urban planners and transportation professionals for better integration across all AAM modes. Click here to access the full SAE EDGETM Research Report portfolio.
Due to the infeasibility of exhaustive on-road testing of Automated Vehicles (AVs) and vehicles with Advanced Driver Assistance Systems (ADAS), virtual methods for verification and validation of such vehicles have gained prominence. In order to incorporate the variability in the characteristics of test scenarios such as surrounding traffic, weather, obstacles, road network, infrastructure features, etc., as well as provide the option of varying the fidelities of subsystem models, this study discusses a modular software block-set for virtual testing of AV/ADAS controllers based on open source tools. The core concept is to co-simulate the traffic, vehicle dynamics, sensors, and the 3D scenes required for perception. This is achieved using SUMO (Simulation of Urban MObility, a microscopic road-network-based traffic generation tool) and Unreal Engine (for 3D traffic flow generation). Due to the difference in the simulation timestep sizes of SUMO and Unreal Engine, as well as some of the
With the enhancements in vehicle electrification and autonomous vehicles, Traffic systems are also being improved at an accelerated rate to aid the development of improving fuel economy standards. For this to be possible, it is essential that traffic can be accurately modeled and predicted. The existing toolsets are proprietary and expensive and traffic modeling is not a trivial task due to its dependence on various factors such as place, time, and weather. To address these issues, an entirely open-source Software-In-Loop (SIL) fleet-focused traffic modeling toolset has been developed with the ability to take environmental factors with powertrain-in-the-loop into account leveraging Simulation of Urban Mobility (SUMO) and python. The proposed SIL toolset encompasses the creation of a microscopic traffic distribution which accounts for the usual traffic trends of a typical day. Parameters such as the number of vehicles entering the network and the speed of all the vehicles at a time of a
Urban mobility represents one of the most critical global challenges nowadays. Several options regarding design and power sources technologies were recently proposed; among which electric and hybrid vehicles are quite successful to meet the increasingly restrictive environmental targets. This significant goal may affect the perceived vehicle comfort and drivability, especially in everyday urban scenarios. The purpose of this paper is to carry out a comparison in terms of comfort between vehicles belonging to different categories, but all designed for urban mobility: an electric 2-passenger quadricycle used during the demonstration phase of the European project STEVE, an internal combustion engine 2-passenger car (Smart Fortwo), an electric 4-passenger car (Bolloré Bluecar) and an internal combustion engine 4-passenger car (Fiat 500). Leading European car-sharing services use the last three car models. Onboard accelerations at the seat, the feet and the steering wheel are recorded, as
Society sees itself in an era in which ecological and sustainability issues have assumed great importance, and with that, several issues need to be revised. When it comes to mobility, a key point is to determine the most efficient way to travel a certain distance with the lowest cost and environmental impact. Due to the size of the world fleet of vehicles, it is easy to understand how an increase of efficiency of the internal combustion engines (ICE) lead to a reduction of the total volume of fuel consumed in the planet. That combined to the possibility of integration with an online network, showing the flow conditions of each road, would allow a further reduction of the fuel consumed globally as well as a mitigation of the emission of harmful gases to the environment associated to urban mobility. In Brazil, the automobile fleet consists of approximately 60% of Flex-Fuel vehicles, which can use either ethanol or gasoline. Despite of the fact that the biofuel is renewable and less
The study aims at an integrative analysis between the means of locomotion, the routes and the technology for monitoring and enforcement. It aims to equalize the daily travel flows following the provisions of Law 12,587 / 12, known as the Urban Mobility Law, and contributing to the improvement of the life quality of the population. The inclusion of urban tolls tends to reduce the number of journeys of individual motor vehicles in the expanded center, an area already established since 1996. In contrast, investment in the provision of public transport service, in addition to favoring the reduction of emission of pollutants in the atmosphere, tends to shorten travel time and significantly improve the health and well-being of the population. The technology-based monitoring allows real-time enforcing of the circulating fleet in the expanded center, indirectly contributing to public safety. As a result, the integration of monitoring, roads and fleet establishes a collective gain in urban
The safety, reliability and efficiency in the progress of the autonomous vehicle have increased in recent years. In parallel, companies in the segment of people transportation, either individually or shared, took the world leadership using smartphone app into a new concept of urban mobility with conventional vehicles with drivers, starting consequently a change of habit of the population, and defying the laws of local transport. These services for urban mobility are related as tendencies of driving forces in the face of the relevance of the limitations of resources, population density, greater awareness toward the environment and traffic congestion. The acquisition of the “own vehicle” as currently, conceived and successful by Alfred Sloan in the 1920s, has become a question for future generations. This study shows that the provision of a more secure service, reliable, and efficient, will enable a significant reduction in total cost of ownership to the increasingly sophisticated and
Urban Mobility is one of the most critical issues at the present. Public transport in connection with feeder bus system is proposed to be one of the main solution. Chulalongkorn University has a fleet of electric feeder bus in operation for a few years now. The fleet service is, however, to be improved because of current limitations in battery energy capacity and long battery charging time. This paper aims to examine the total cost of ownership (TCO) of the electric feeder buses using various types of energy storage. The results on the sensitivity analysis highlight the major parameters that exert strong influence in the TCOs. The fast charging system using supercapacitor battery bus shows the lowest TCO for the present bus fleet. The travel distance (km/year) and operational years were illustrated to be the top two parameters that exert major influence towards the TCO.
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