Transport and Health

Urban Health ◽  
2019 ◽  
pp. 52-58 ◽  
Author(s):  
Mark Nieuwenhuijsen ◽  
Haneen Khreis
Keyword(s):  
Urban Health ◽  
Public Transportation ◽  
Urban Areas ◽  
Autonomous Vehicles ◽  
Urban Environments ◽  
Urban Residents ◽  
Vehicular Pollution ◽  
Traffic Jams ◽  
Challenges And Opportunities ◽  
Improve Health

Densely populated urban areas afford an enormous opportunity for their residents to have access to a range of salutary resources, thus avoiding some of the challenges that characterize less dense communities. However, transportation often bedevils urban areas, with limited opportunities offered for urban residents to get around cities. Traffic jams and vehicular pollution are associated with poor health of urban residents even as the data are clear that investments in public transportation are both cost beneficial and can improve health. Emerging solutions, including autonomous vehicles, stand to transform urban environments and health in these environments. This chapter discusses transportation as a determinant of health in cities, outlining challenges and opportunities for efficient and effective transportation with an eye toward emerging solutions that can improve urban health.

Education

Urban Health ◽  
2019 ◽  
pp. 94-101
Author(s):  
Jennifer Karas Montez ◽  
Amy Ellen Schwartz
Keyword(s):  
Urban Health ◽  
Low Income ◽  
Urban Areas ◽  
Urban Environments ◽  
Education For All ◽  
Urban Residents ◽  
Healthy Population ◽  
Low Income Country ◽  
Challenges And Opportunities ◽  
Effective Education

There is little question that education is a core determinant of the health of populations. In the context of urban environments, where more people are now concentrated than ever before, the provision of effective education represents both an opportunity to create an informed and healthy population and a challenge to provide education for all urban residents without leaving large segments of the population behind. In many high-income countries, the provision of quality education for all in cities has been challenging, with cycles of poor education perpetuating growing class divides. Provision of effective education in rapidly growing low-income country urban areas is very much a challenge of our current moment. This chapter discusses the challenges and opportunities inherent in providing education in urban areas and the implications these have for urban health.

scholarly journals Changes in traffic infrastructure with the arrival of autonomous vehicles

2021 ◽  
Author(s):  
Hrvoje Kmoniček ◽  
Filip Ruška
Keyword(s):  
Reaction Time ◽  
Traffic Safety ◽  
Public Transportation ◽  
Urban Areas ◽  
Autonomous Vehicles ◽  
Transport Infrastructure ◽  
Mixed Traffic ◽  
Traffic Lights ◽  
Traffic Jams ◽  
Significant Step

Autonomous vehicles represent a significant step forward in traffic safety and efficiency. Although it will be quite some time before all vehicles on public roads are autonomous, it is certainly advisable to consider the changes that will need to be introduced to traffic and traffic infrastructure. Autonomous vehicles will significantly increase the efficiency and use of public transportation and car-sharing, which will ultimately mean fewer cars on the roads and less need for parking in urban areas, or their conversion into a type of waiting area. Also, fewer vehicles, whose software has a drastically faster reaction time and much better control of the vehicle, will also mean less traffic jams, greater intersection flow, less need to channel traffic in traffic lanes and will remove traffic lights almost entirely out of use. This paper will look at the form of transport infrastructure and its variants in the case of mixed traffic with autonomous vehicles and drivers, as well as the situation with fully autonomous traffic without people behind the wheel.

scholarly journals CREATING MULTI-TEMPORAL MAPS OF URBAN ENVIRONMENTS FOR IMPROVED LOCALIZATION OF AUTONOMOUS VEHICLES

2020 ◽  
Vol XLIII-B2-2020 ◽  
pp. 317-323
Author(s):  
J. Schachtschneider ◽  
C. Brenner
Keyword(s):  
Urban Areas ◽  
Autonomous Vehicles ◽  
Weather Conditions ◽  
Point Clouds ◽  
Urban Environments ◽  
Seasonal Effects ◽  
Data Set ◽  
Multi Temporal ◽  
One Year

Abstract. The development of automated and autonomous vehicles requires highly accurate long-term maps of the environment. Urban areas contain a large number of dynamic objects which change over time. Since a permanent observation of the environment is impossible and there will always be a first time visit of an unknown or changed area, a map of an urban environment needs to model such dynamics.In this work, we use LiDAR point clouds from a large long term measurement campaign to investigate temporal changes. The data set was recorded along a 20 km route in Hannover, Germany with a Mobile Mapping System over a period of one year in bi-weekly measurements. The data set covers a variety of different urban objects and areas, weather conditions and seasons. Based on this data set, we show how scene and seasonal effects influence the measurement likelihood, and that multi-temporal maps lead to the best positioning results.

What Is Urban Health?

2020 ◽  
pp. 3-26
Author(s):  
Ana V. Diez Roux
Keyword(s):  
Public Health ◽  
Urban Health ◽  
Urban Areas ◽  
Important Public Health ◽  
Public Health Priority ◽  
Health Priority ◽  
Improve Health

This chapter discusses why urban health is an important public health priority and presents themes and approaches that are especially relevant to the field. It reviews key geographical concepts in urban health including definitions of urban areas, cities, and neighborhoods. It outlines key elements that are needed to understand and improve health in urban areas.

Why Cities and Health?

Urban Health ◽  
2019 ◽  
pp. 15-24 ◽  
Author(s):  
Catherine K. Ettman ◽  
David Vlahov ◽  
Sandro Galea
Keyword(s):  
Conceptual Framework ◽  
Urban Health ◽  
Urban Residents ◽  
Urban Populations ◽  
Urban Living ◽  
Causal Thinking ◽  
Profound Influence ◽  
Improve Health ◽  
The Way

Urban health is concerned with understanding how features of cities influence the health of urban populations, thus pointing the way to interventions that can improve health. An understanding of urban health requires a grounding in the fundamentals of causal thinking. How do cities influence the health of populations? And what is unique or uniquely interesting about urban health? This chapter addresses these questions through providing a conceptual framework to organize and guide thinking. The authors explicate how we may think of urban living as a ubiquitous exposure influencing other factors to which urban residents are exposed and that have a profound influence on the health of these residents.

Urban Planning

2019 ◽  
pp. 99-122
Author(s):  
Fran Baum
Keyword(s):  
New York ◽  
Urban Planning ◽  
Public Transportation ◽  
Conflicts Of Interest ◽  
Good Practice ◽  
Urban Environments ◽  
Visionary Leadership ◽  
Urban Residents ◽  
Symbiotic Relationship ◽  
Development Processes

This chapter discusses the symbiotic relationship between urban planning and public health, examines the features of healthy and sustainable urban environments, provides positive examples of healthy urban planning and the blocks to conducting such planning. Consideration is given to how urban planning can contain sprawl and can create cites that rely more on public transportation, cycling, and walking. Examples of good practice from New York, Zurich, and Bursa (Turkey) are provided. Issues of governance, including public participation in planning and the importance of visionary leadership, are discussed. A perspective of cities as contested ground in which developers seek to maximize profits, often at the expense of urban residents, is developed. Conflicts of interest that arise in development processes are examined.

Migration

Urban Health ◽  
2019 ◽  
pp. 85-93
Author(s):  
Sabrina Hermosilla ◽  
Tahilia J. Rebello
Keyword(s):  
Social Cohesion ◽  
Rapid Growth ◽  
Urban Areas ◽  
Urban Environments ◽  
City Size ◽  
Urban Residents ◽  
Economic Potential ◽  
Population Displacement ◽  
Immigrant Populations ◽  
Short Period

The rapid growth of cities is attributable, in part, to substantial migration to cities from non-urban areas. As the economic potential of cities has grown, more and more people are drawn to urban environments, thus contributing to growing city size and to dynamic urban environments. And yet migration to urban areas is associated with its own challenges. Immigrant populations often face exclusion and challenges integrating in urban environments. In cities where a large influx of immigrants has changed the environment in a short period of time, social cohesion has been challenged, with attendant social divides. Migration results in population displacement and gentrification, each bringing its own challenges to health. This chapter discusses the opportunities and challenges that migration presents to the health of urban residents.

scholarly journals Multi-Task End-to-End Self-Driving Architecture for CAV Platoons

Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1039 ◽  
Author(s):  
Sebastian Huch ◽  
Aybike Ongel ◽  
Johannes Betz ◽  
Markus Lienkamp
Keyword(s):  
Urban Areas ◽  
Autonomous Vehicles ◽  
Ride Comfort ◽  
Urban Environments ◽  
Training Environment ◽  
Improve Energy Efficiency ◽  
V2v Communication ◽  
End To End ◽  
Reduce Emissions ◽  
Point To Point

Connected and autonomous vehicles (CAVs) could reduce emissions, increase road safety, and enhance ride comfort. Multiple CAVs can form a CAV platoon with a close inter-vehicle distance, which can further improve energy efficiency, save space, and reduce travel time. To date, there have been few detailed studies of self-driving algorithms for CAV platoons in urban areas. In this paper, we therefore propose a self-driving architecture combining the sensing, planning, and control for CAV platoons in an end-to-end fashion. Our multi-task model can switch between two tasks to drive either the leading or following vehicle in the platoon. The architecture is based on an end-to-end deep learning approach and predicts the control commands, i.e., steering and throttle/brake, with a single neural network. The inputs for this network are images from a front-facing camera, enhanced by information transmitted via vehicle-to-vehicle (V2V) communication. The model is trained with data captured in a simulated urban environment with dynamic traffic. We compare our approach with different concepts used in the state-of-the-art end-to-end self-driving research, such as the implementation of recurrent neural networks or transfer learning. Experiments in the simulation were conducted to test the model in different urban environments. A CAV platoon consisting of two vehicles, each controlled by an instance of the network, completed on average 67% of the predefined point-to-point routes in the training environment and 40% in a never-seen-before environment. Using V2V communication, our approach eliminates casual confusion for the following vehicle, which is a known limitation of end-to-end self-driving.

scholarly journals Smart-Mobility Services for Climate Mitigation in Urban Areas: Case Studies of Baltic Countries and Germany

2021 ◽  
Vol 13 (8) ◽  
pp. 4127
Author(s):  
Gabriele Cepeliauskaite ◽  
Benno Keppner ◽  
Zivile Simkute ◽  
Zaneta Stasiskiene ◽  
Leon Leuser ◽  
...  
Keyword(s):  
Public Transportation ◽  
Urban Areas ◽  
Universal Access ◽  
Urban Environments ◽  
Transport Sector ◽  
Climate Mitigation ◽  
The European Union ◽  
Baltic Countries ◽  
Smart Mobility ◽  
Negative Environmental Impact

The transport sector is one of the largest contributors of CO2 emissions and other greenhouse gases. In order to achieve the Paris goal of decreasing the global average temperature by 2 °C, urgent and transformative actions in urban mobility are required. As a sub-domain of the smart-city concept, smart-mobility-solutions integration at the municipal level is thought to have environmental, economic and social benefits, e.g., reducing air pollution in cities, providing new markets for alternative mobility and ensuring universal access to public transportation. Therefore, this article aims to analyze the relevance of smart mobility in creating a cleaner environment and provide strategic and practical examples of smart-mobility services in four European cities: Berlin (Germany), Kaunas (Lithuania), Riga (Latvia) and Tartu (Estonia). The paper presents a systematized literature review about the potential of smart-mobility services in reducing the negative environmental impact to urban environments in various cities. The authors highlight broad opportunities from the European Union and municipal documents for smart-mobility initiatives. The theoretical part is supplemented by socioeconomic and environmental descriptions, as well as experience, related to smart-mobility services in the four cities selected.

scholarly journals Going carless in different urban fabrics: socio-demographics of household car ownership

2021 ◽  
Author(s):  
L. E. Karjalainen ◽  
M. Tiitu ◽  
J. Lyytimäki ◽  
V. Helminen ◽  
P. Tapio ◽  
...  
Keyword(s):  
Public Transportation ◽  
Urban Form ◽  
Urban Areas ◽  
National Level ◽  
Urban Environments ◽  
Neighborhood Density ◽  
Car Ownership ◽  
Sustainable Mobility ◽  
Demographic Profiles ◽  
Residential Distance

AbstractDiverse physical features of urban areas alongside socio-demographic characteristics affect car ownership, and hence the daily mobility choices. As a case of sustainable mobility, we explore how various urban environments and socio-demographics associate with the spatial and social distribution of household car ownership and carlessness in the Helsinki Metropolitan Area, Finland. Three urban fabrics characterizing the study area are established based on the transportation mode (walking, public transportation, or automobile) the physical urban environment primarily supports. The national level Monitoring System of Spatial Structure and Urban Form database, and the National Travel Survey (2016) are utilized to further include spatial and socio-demographic variables into our analysis across these fabrics. Our results show that households with and without cars differ in terms of residential distance to the city center, neighborhood density, house type, and socio-demographic profiles. Single pensioners and students are most likely to be carless, whereas families represent the opposite. Within the carless households the differences are also evident between different groups. For the more affluent households residing in dense and well-connected areas, and mostly possessing driver’s licenses, carlessness is presumably a choice. Contrarily, many other carless households represent the less affluent often located in the more distant, low-density, and less accessible areas, while also possessing less driver’s licenses, making carlessness more of a constraint, as the local urban fabric does not support such lifestyle. Consequently, carless households should be increasingly recognized as a focus group in sustainable urban planning in terms of identifiable best practices and potential vulnerability.

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