Mobility In Urban Environment Research Articles

City lights revolution: Next-gen optical fibre for smart cities

In the rapidly evolving landscape of smart cities, the integration of advanced technologies is crucial for ensuring safety, optimizing traffic flow, and enhancing the urban living experience. Vehicle-to-vehicle (V2V) communication and visible light communication (VLC) have emerged as promising solutions to address these challenges. This paper explores the integration of V2V communication and VLC at smart pedestrian crosswalks to enhance pedestrian safety and traffic management in smart cities. It explores the impact of neighbouring vehicles on V2V-VLC performance and proposes novel methodologies to assess traffic density effects. Results indicate a significant chance of encountering nearby cars during rush hours, emphasizing the importance of these integrated systems for safety and mobility in urban environments. The outcomes show that the chance of running into extra cars in nearby lanes is independent of the particular lane and increases to 80% through rush hours, but falls to a lower amount than 20% through off-peak and initial morning hours.

ENHANCING URBAN PATHFINDING FOR PEDESTRIANS THROUGH FUSION OF MLS AND HMLS DATA

Abstract. Pedestrian pathfinding is crucial for enhancing pedestrian mobility in urban environments. In this research a method to generate navigation graphs based on Mobile Laser Scanning (MLS) and Handheld Laser Scanning (HMLS) data fusion is developed. The input data comprises a 2-kilometer urban street network that integrates both MLS and HMLS data, effectively mitigating sidewalk occlusions caused mainly by parked vehicles. The proposed method encompasses the following steps: (1) Deep Learning semantic segmentation of urban ground elements and navigation-related obstacles, (2) Static vs. Dynamic object differentiation to replicate conditions of unobstructed passage. (3) Sidewalk enrichment with inclination, preservation status, and width. (4) Physical accessibility estimation between sidewalks and crosswalks incorporating curb information. And (5) navigation graph computation based on the enhanced sidewalk data, crosswalks, with accurate node location and connections. Routes were calculated within a Geographical Information System, and results ensure that pedestrians can navigate in urban environments with precision and efficiency.

5.E. Workshop: Salutogenic Cities: European experiences in Urban Health

Abstract The Workshop titled “Salutogenic Cities: European experiences in Urban Health” - proposed and developed by the three EUPHA Section: Urban Public Health (URB), Public Mental Health (MEN) and Environmental Health (ENV) - is aimed to foster the dialogue between designers (architects and urban planners), Public Health experts (operators, professionals and epidemiologists), policy/decision makers and city users, to establish a multidisciplinary approach for understanding together how to create and manage healthy living outdoor urban environments. The Workshops mainly address both the “Climate emergency / Environment and health / Urban health” and the “Global health and Europe's role in global health” EPH23 conference topics. The Workshops purpose is to explore the link between the morpho-typological features of the urban environment and Public Health outcomes, that's crucial in the scientific scenario, taking into consideration the urbanization phenomena that characterizes contemporary society. Health is no longer a specifically individual health issue, but a collective priority strongly influenced by the environmental context and by strategies implemented by local Governments. Urban planning, at large and small scales, can be considered a key tool to protect and promote Urban Public Health. In this scenario, the COVID-19 emergency, has accelerated and emphasized several social, environmental and digital challenges, underling the focus on several aspects such as Urban mobility and walkable environment; Urban Green Spaces and ecosystem services assessment; Urban Health policies and actions. The Workshops program include inputs which they argue current experiences, emerging practices and scientific outcomes related to the Urban Health discipline. From methods, in “Improving health and wellbeing through health-centered, evidence-based urban planning methodologies” to actions, in “The urban burden of disease estimation for policy-making in 1000 European cities”. From epidemiological outcomes, in “Association between area-level walkability and glycated haemoglobin: a Portuguese population-based study” to hospitalizations implications, in “Daily temperature variability in cities and mental health-related hospitalizations”. Key messages • Explore the link between the morpho-typological features of the urban environment and Public Health outcomes, taking into consideration the urbanization phenomena that affect the contemporary society. • Establish a multidisciplinary approach for understanding together how to create and manage healthy living outdoor urban environments.

Deep Koopman Traffic Modeling for Freeway Ramp Metering

Ramp metering has been considered as one of the most effective approaches of dealing with the traffic congestion on the freeways. The modelling of the freeway traffic flow dynamics is challenging because of its non-linearity and uncertainty. Recently, Koopman operator, which transfers a non-linear system to a linear system in an infinite-dimensional space, has been studied for modelling complex dynamics. In this paper, we propose a data-driven modelling approach based on neural networks, denoted by deep Koopman model, to learn a finite-dimensional approximation of the Koopman operator. To consider the sequential relations of the ramps and main roads on the freeway, a long short-term memory network is applied. Furthermore, a model predictive controller with the trained deep Koopman model is proposed for the real-time control of the ramp metering on the freeway. To validate the performance of the proposed approach, experiments based on the simulation in the traffic simulation software Simulation of Urban MObility (SUMO) environment are conducted. The results demonstrate the effectiveness of the proposed approach on both the dynamics prediction and the real-time control of the ramp metering.

Deep reinforcement learning for traffic signal control with consistent state and reward design approach

Intelligent Transportation Systems are essential due to the increased number of traffic congestion problems and challenges nowadays. Traffic Signal Control (TSC) plays a critical role in optimizing the traffic flow and mitigating the congestion within the urban areas. Various research works have been conducted to enhance the behavior of TSCs at intersections and subsequently reduce the traffic congestion. Researchers recently leveraged Deep Learning (DL) and Reinforcement Learning (RL) techniques to optimize TSCs. In RL framework, the agent interacts with surrounding world through states, rewards and actions. The formulation of these key elements is crucial as they impact the way the RL agent behaves and optimizes its policy. However, most of existing frameworks rely on hand-crafted state and reward designs, restricting the RL agent from acting optimally. In this paper, we propose a novel approach to better formulate state and reward definitions in order to boost the performance of the traffic signal controller agent. The intuitive idea is to define both state and reward in a consistent and straightforward manner. We advocate that such a design approach helps achieving training stability and hence provides a rapid convergence to derive best policies. We consider the double deep Q-Network (DDQN) along with prioritized experience replay (PER) for the agent architecture. To evaluate the performance of our approach, we conduct series of simulations using the Simulation of Urban MObility (SUMO) environment. The statistical analysis of our results show that the performance of our proposal outperforms the state-of-the-art state and reward design approaches.

SPROUT case studies: Assessing future mobility scenarios by following a city-led consequence analysis framework - the case of Budapest and Tel Aviv city

The rapid changes in the urban mobility environment together with the on-going and future technological trends constitute a great challenge for policy makers to assess the expected impacts. This study aims to confront these issues through the development and application of a framework for anticipating the effect of the transition taking place in a city's urban mobility environment. The framework is used for collecting the required data from the cities, followed by the analysis of the results and the identification of the impacts of any city-specific future mobility scenario. In this paper, the cases of Budapest and Tel Aviv are chosen to be presented as two cities with similar size, population and level of smartness. The cross-comparison of the two cases shows the consequences foreseen, as for example an increased level of congested streets, while also of the Air Quality index.

Renewable compensatory measures to mitigate the grid stress after different penetration shares of electric mobility in urban environment

Renewable compensatory measures to mitigate the grid stress after different penetration shares of electric mobility in urban environment

Renewable compensatory measures to mitigate the grid stress after different penetration shares of electric mobility in urban environment

Renewable compensatory measures to mitigate the grid stress after different penetration shares of electric mobility in urban environment

Cooperative Traffic Signal Control based on Biased ReLU Neural Network Approximation

Traffic signal control is important in intelligent transportation system, of which the cooperative control is difficult to realize but yet vital. Popular methods for solving this problem are based on multi-agent reinforcement learning (RL), in which function approximator, e.g., different kinds of neural network play a critical role. In this paper, we propose a multi-agent actor-critic RL framework with global value function and local policy function, for which the piecewise linear neural network, named biased ReLU (BReLU) is used as the function approximator. The reason for doing this is two-fold. First, it has been proved in the control literature that minimizing (maximizing) a piecewise linear function over a polyhedron yields piecewise linear solutions. Second, the BReLU neural network can provide a more accurate approximation than the traditional ReLU neural network when they have similar network structures. The proposed method is evaluated on the Simulation of Urban Mobility (SUMO) environment compared with two benchmark traffic signal control methods. The simulated results illustrate the proposed algorithm can coordinate the signal control between different intersections, achieve lower and more sustainable intersection delays on the whole traffic network.

Wind-optimal lateral trajectories for a multirotor aircraft in urban air mobility

The primary motivation for this paper is to quantify the operational benefits (energy consumption and flight duration) of flying wind-optimal lateral trajectories for short flights (less than 60 miles) anticipated in the urban environment. The optimal control model presented includes a wind model for quantifying the effect of wind on the lateral trajectory. The optimal control problem is numerically solved using the direct collocation method. Energy consumption and flight duration flying wind-optimal lateral trajectories are compared with corresponding values obtained flying great-circle paths between the same origin and destination pairs to determine the operational benefits of wind-optimal routing for short flights. The flight duration results for different scenarios are validated using a simulation tool designed and developed at NASA for exploring advanced air traffic management concepts. This research study suggests that for short flights in an urban environment, operational benefits of the wind-optimal lateral trajectories over the corresponding great-circle trajectories in terms of energy consumption and flight duration per flight are dependent on: i) wind field’s spatial variability, ii) wind magnitude, iii) the direction of route relative to the wind field, and iv) cruise segment length. The operational benefits observed in realistic flyable wind scenarios are less than 2.5%; these could be translated to an equivalent of a maximum of 2 min of cruise flight duration savings in the urban air mobility environment. As expected, headwinds and tailwinds along the flight route most significantly impact energy consumption and flight duration.

SWSCAV: Real-time traffic management using connected autonomous vehicles

Traffic management methods aim to increase the infrastructure’s capacity to lower congestion levels. Using vehicle-to-vehicle (V2V), vehicle-to-infrastructure (V2I), and vehicle-to-everything (V2X) connectivity technologies, connected autonomous vehicles (CAVs) have the potential to operate as actuators for traffic control. In this study, a CAV-based alternative approach for traffic management is proposed (SWSCAV), and its performance is compared to that of lane control signals (LCS) and variable speed limits (VSL), which are also traffic management systems. When a shockwave is detected due to an incident, the CAVs on the road slow until they reach the speed of the observed shockwave (SWS), according to this proposed procedure. Thus, the incoming traffic flow towards the incident is slowed, preventing the queue behind from extending. In a simulation of the urban mobility (SUMO) environment, the suggested method is evaluated for 4800 scenarios on a three-lane highway by varying the market penetration rate of CAVs in traffic flow, the control distances, the incident lane, and the duration. The proposed method reduces the incidence of density values of over 38 veh/km/lane and 28 veh/km/lane in the vicinity of the incident region by 12.68 and 8.15 percent, respectively. Even at low CAV market penetration rates, the suggested method reduces traffic density throughout the network and in the location of the incident site by twice as much as the LCS system application.

Methodology for Consequence Analysis of Future Mobility Scenarios: The SPROUT Framework

The various social, political, environmental, and economical mega-trends together with the rapid rise of digitalization are shaping cities worldwide including the way that citizens and products move within the urban environment. New mobility services are popping up which are showing the path toward more on-demand and personalized mobility patterns. The transformation of the urban mobility environment though constitutes a great challenge for policy-makers, as little is known about the impact of these trends on the city’s current mobility environment while the assessment of the future state of a mobility system can be considered a quite complex process taken its multi-parametric and multi-dimensional nature. This paper aims to simplify this process by presenting a coherent multi-actor consequence analysis framework as a tool for assessing future mobility scenarios which was developed in the framework of the H2020 SPROUT. This paper presents in detail the main components of this framework together with the list of key performance indicators used for assessing the performance in terms of sustainability of future mobility scenarios as well as indicative results from its use by the city of Padua.

Operational Requirements Analysis for Electric Vertical Takeoff and Landing Vehicle in the Brazilian Regulatory Framework

Air passenger transport is expected to change, in the next years, the urban air mobility (UAM) environment. New technologies are enabling the introduction of a new concept of aircraft, referred to as electric vertical takeoff and landing vehicle (eVTOL), with vertical take-off and landing capability, distributed electric propulsion system and low noise level compared to helicopters. This article presents an analysis of the Brazilian Civil Aviation Regulations (RBAC) No. 91 and 135, which address the minimum requirements for commercial operations of commuter and on-demand public passenger transport with airplanes with up to 19 seats. The objective of this article is to identify the technical and regulatory barriers to initiating the eVTOL operation in Brazil and to validate the current operational air traffic rules. After the analysis of the operational requirements and the current Air Traffic Management (ATM) infrastructure for helicopter operation, the minimum required and recommended navigation, communication and surveillance equipment are identified, as well as the main operational limitations for the operation of this type of aircraft in transporting passengers. This analysis is just the beginning of a broader study and there are many challenges to support an increased eVTOL operations.

Accessibility Barriers and Perceived Accessibility: Implications for Public Transport

The ability to live the life one wants with public transport is one of the key factors of sustainable and inclusive societies. Given the current trend in the transport domain, providing accessible public transport is necessary in order to allow people to participate in their day-to-day activities without using a car. Using survey data obtained from Sweden, this study investigates factors that may have a negative effect on the perceived accessibility of public transportation in major city areas and other areas. Overall, regression analyses show that time and economic resources, organizational and temporal functions, frequent travel by public transport, and geographical context all act as accessibility barriers. These findings highlight the need not only to target increased mobility in urban environments, but also to turn the focus to the citizenry’s perceived accessibility. These findings point to implications for policies, planning and interventions targeted at accessible public transport. Adopting an accessibility-oriented approach to urban development, including the individual perspective, could be a pathway for creating a socially sustainable transport system.

You'll never share alone: Analyzing carsharing user group behavior

The rapidly developing concept of carsharing is an essential and scalable part of sustainable, multimodal mobility in urban environments. There is a clear need for carsharing operators to understand their users and how they use different transportation modes to intensify the development of carsharing and its positive impacts on the environment and urban cohabitation. We foster this understanding by analyzing usage data of carsharing in a medium-sized German city. We compare user groups based on individual characteristics and their carsharing usage behavior. We focus on a station-based two-way carsharing scheme and its relation to free-floating carsharing. Based on different clustering and segmentation approaches, we defined 20 particularly interesting user groups among the carsharing users and analyzed noticeable usage patterns. Additionally, we examined these partially overlapping user groups in the spatial dimension. With these results, we support research and operators in understanding carsharing customers and assessing users’ individual behavior.

Integration of Network Scheduling Using Accrued Delay Across Vehicle Connectivity

Current air traffic management processes lack integration among elements of the airspace system such as airport and airspace resources, often due to disconnected and inconsistent use of information, models, and metrics. This integration is hindered further by the separation between the traffic management problem, which has focused on a gate-to-gate flight model, and the management of connecting vehicles, crews, and passengers between flights. To help induce such integration, an accrued delay metric is used to continuously measure the delay that a flight has accumulated during the flight and inherited from previous flights through the turnaround at airports. The authors presented previously an application of this metric to mitigate the delay propagation between management initiatives during a flight. In this paper, the authors extend this metric to mitigate delay propagation through vehicle turnaround. It is first shown through a historical data analysis that this delay propagation is a significant source of delay for airline operators and that schedule padding hides some of it. Then, accrued delay along a vehicle trip is shown to mitigate some of this propagation across the network. Through an abstract, closed, three-node network example, using accrued delay is shown to help implicitly coordinate the distributed scheduling among the nodes. These nodes may represent a set of airports or a set of vertiports in an urban air mobility environment. It is shown that prioritizing flights that have accrued high delay at previous nodes significantly reduces the variance of flight delay.

Experimental vs. simulation analysis of LoRa for vehicular communications

LoRa, a Low Power Wide Area Network (LPWAN) technology, demands reduced network infrastructure to cover a large area, with low power consumption. In the context of vehicular communications, LoRa has the potential to support monitoring and cooperative navigation applications, where small amounts of data can be transmitted asynchronously through the network. Nevertheless, the literature lacks evaluations of LoRa in the context of vehicular communications. Thus, in this paper we analyze the performance of this technology operating in an urban mobility environment, using LoRa terminal devices embarked on vehicles and a LoRa receiver unit, acting as infrastructure. Moreover, we evaluate the equivalence between experimental and simulated results, obtained from the communication link between the LoRa module inside a vehicle and a LoRa receiver comparing to those produced by NS-3 simulations. Three metrics of interest are evaluated: Packet Delivery Ratio (PDR), Packet Inter-Reception (PIR) time, and Received Signal Strength Indicator (RSSI). Field experiments are performed at the campus of the Federal University of Rio de Janeiro (UFRJ), Brazil. Results revealed that all the metrics evaluated in the simulated experiments are consistent with the results of the real experiments, however, we concluded that the model can be improved by looking for a stronger correlation with real experiments.

DESIGN CRITERIA OF MODERN SHOPPING CENTRE BUILDING BASED ON PUBLIC PEDESTRIAN SPACE

Mobility contributes to quality of life (Muller, 2016). In Indonesia, shopping centre buildings and urban pedestrian spaces have not been supporting each other in accommodating public pedestrian mobility. It lets people to drive more automobiles instead of walking even though their settlements are actually convenient from the commercial places. This problem is further causing the other matters such as traffic jam, accidence, air pollution, anxiety, and so on. By considering this problem, it is important to transform the design criteria of the modern shopping centre building to be not only serving as commercial destinations, but also space for public pedestrians that provides good mobility in urban environment, so that the walking lifestyle could be popular again in Indonesia. This research is aimed to identify design criteria of modern shopping centre buildings that are based on public pedestrian space. The criteria is expected to be new standard in planning and designing future shopping centre buildings in Indonesian cities. The Evaluative Method is utilized in this research involving a theory of Urban Mobility as the main parameter.

On the Opportunistic Topology of Taxi Networks in Urban Mobility Environment

Understanding and characterizing the connectivity of vehicular networks has become increasingly important because of their wide applications and fast development. To address the dynamical links in vehicular networks, time-varying graph (TVG) is one of the most important models. Nowadays, due to the fact that lots of vehicular applications can tolerate a small amount of latency in communication, opportunistic reachability graph (ORG) characterizes the connectivity better by introducing delay tolerance to the model. However, people still do not have a high-level summarization, i.e., the topology, of the vehicular network on how nodes are clustered and isolated. In this paper, based on ORG model, we analyze the opportunistic topology of taxi networks in urban mobility environment by mainly focusing on the number, location and evolution of connected components and the size of the largest components to reveal the unique properties of the taxi networks instead of just links and hops. Our analysis is based on the real taxi traces of big cities and reflects the real urban mobility environment. We find that the opportunistic topology of the networks with delay tolerance is substantially different from the instantaneous topology without considering the delay. Moreover, we unveil the fundamental relationships and trade-offs between the dynamical topology and the key network parameters related to mobility, e.g., delay tolerance, transmission distance, etc. To the best of our knowledge, our study is the first work to reveal the characteristics of opportunistic topology models in the large-scale urban mobility environment with real traces.

Photovoltaic Electric Scooter Charger Dock for the Development of Sustainable Mobility in Urban Environments

Means and modes of transport in urban environments are changing. The emergence of new means of personal transport, such as e-scooters or e-bikes, combined with new concepts such as `vehicle sharing' are changing urban transport. A greater social awareness of the harmful effects of polluting gases is leading to the adoption of new e-mobility solutions. A sustainable e-scooter recharging dock has been designed, built, and put into operation in a small town north of the city of Valencia (Spain). In the proposed novel solution, a stand-alone PV system is built for the free recharge of e-scooters using an original system that supports new sustainable means of transport. The design of the PV system considers the size limitations of the equipment, where a single PV module must generate the energy needed to recharge the e-scooters. A battery is used to store the energy and adjust power generation and consumption profiles. A commercial electronic converter adjusts the various electrical characteristics of generation, storage, and consumption. As a result of the system analysis, the surplus autonomy provided for the e-scooter recharging dock is calculated. Potential stakeholders in the use of the proposed system and their reasons for adopting this sustainable solution are identified. Experimental results of the first months of operation are included and these demonstrate the correct operation of the proposed system.