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"Traffic planning"
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Planning of a comprehensive transportation system in Ma’anshan based on mobile phone signaling data
Integrated transportation system planning is forward-looking and oriented to the future development of transportation. It is an important issue for special planning in terms of current land and spatial planning, and all community sectors recognize its importance. The continuous development of big data technology in recent years has brought a great deal of transformative power to urban traffic planning theory and technology. Using mobile phone signaling data (MPSD) to analyze and calculate traffic data information is a new technology in wide-area dynamic traffic detection. This paper uses MPSD to extract traffic contact characteristic data, commuter contact characteristic data, and thermal population data to analyze the traffic characteristics of Ma’anshan’s metropolitan clusters, suburbs, and city areas. We identify its co-urban connection characteristics with neighboring cities and the strong southern river corridor of the metropolis, the characteristics of the connection, and the centripetal connection of the central city. According to the problems existing in Ma’anshan’s facility configuration and traffic model, we propose corresponding countermeasures: building a multilevel integrated transportation system in the same city at the metropolitan cluster regional level; forming a centrally radiating multiple-transit network to support the development of the urban spatial pattern at the suburban level; and forming public transportation leadership and road support to optimize the urban transportation network at the city level.
Journal Article
Facing the needs for clean bicycle data – a bicycle-specific approach of GPS data processing
BackgroundGPS-based cycling data are increasingly available for traffic planning these days. However, the recorded data often contain more information than simply bicycle trips. GPS tracks resulting from tracking while using other modes of transport than bike or long periods at working locations while people are still tracking are only some examples. Thus, collected bicycle GPS data need to be processed adequately to use them for transportation planning.ResultsThe article presents a multi-level approach towards bicycle-specific data processing. The data processing model contains different steps of processing (data filtering, smoothing, trip segmentation, transport mode recognition, driving mode detection) to finally obtain a correct data set that contains bicycle trips, only. The validation reveals a sound accuracy of the model at its’ current state (82–88%).
Journal Article
Multiple UAS Traffic Planning Based on Deep Q-Network with Hindsight Experience Replay and Economic Considerations
This paper explores the use of deep reinforcement learning in solving the multi-agent aircraft traffic planning (individual paths) and collision avoidance problem for a multiple UAS, such as that for a cargo drone network. Specifically, the Deep Q-Network (DQN) with Hindsight Experience Replay framework is adopted and trained on a three-dimensional state space that represents a congested urban environment with dynamic obstacles. Through formalising a Markov decision process (MDP), various flight and control parameters are varied between training simulations to study their effects on agent performance. Both fully observable MDPs (FOMDPs) and partially observable MDPs (POMDPs) are formulated to understand the role of shaping reward signals on training performance. While conventional traffic planning and optimisation techniques are evaluated based on path length or time, this paper aims to incorporate economic analysis by considering tangible and intangible sources of cost, such as the cost of energy, the value of time (VOT) and the value of reliability (VOR). By comparing outcomes from an integration of multiple cost sources, this paper is better able to gauge the impact of various parameters on efficiency. To further explore the feasibility of multiple UAS traffic planning, such as cargo drone networks, the trained agents are also subjected to multi-agent point-to-point and hub-and-spoke network environments. In these simulations, delivery orders are generated using a discrete event simulator with an arrival rate, which is varied to investigate the effect of travel demand on economic costs. Simulation results point to the importance of signal engineering, as reward signals play a crucial role in shaping reinforcements. The results also reflect an increase in costs for environments where congestion and arrival time uncertainty arise because of the presence of other agents in the network.
Journal Article
Streetfight : handbook for an urban revolution
As New York Citys transportation commissioner, Janette Sadik-Khan managed the seemingly impossible and transformed the streets of one of the worlds greatest, toughest cities into dynamic spaces safe for pedestrians and bikers. Her approach was dramatic and effective: Simply painting a part of the street to make it into a plaza or bus lane not only made the street safer, but it also lessened congestion and increased foot traffic, which improved the bottom line of businesses. Real-life experience confirmed that if you know how to read the street, you can make it function better by not totally reconstructing it but by reallocating the space thats already there. Breaking the street into its component parts, Streetfight demonstrates, with step-by-step visuals, how to rewrite the underlying source code of a street, with pointers on how to add protected bike paths, improve crosswalk space, and provide visual cues to reduce speeding. Achieving such a radical overhaul wasnt easy, and Streetfight pulls back the curtain on the battles Sadik-Khan won to make her approach work. She includes examples of how this new way to read the streets has already made its way around the world, from pocket parks in Mexico City and Los Angeles to more pedestrian-friendly streets in Auckland and Buenos Aires, and innovative bike-lane designs and plazas in Austin, Indianapolis, and San Francisco. Many are inspired by the changes taking place in New York City and are based on the same techniques. Streetfight deconstructs, reassembles, and reinvents the street, inviting readers to see it in ways they never imagined.
Book
Combining Traffic Microsimulation Modeling and Multi-Criteria Analysis for Sustainable Spatial-Traffic Planning
Spatial and traffic planning is important in order to achieve a quality, safe, functional, and integrated urban environment. Different tools and expert models were developed that are aimed at a more objective view of the consequences of reconstruction in different spatial and temporal ranges while respecting selection criteria. In this paper we analyze the application of the multi-criteria analysis method when choosing sustainable traffic solutions in the center of a small town, in this case Belišće, Croatia. The goal of this paper is to examine the possibility of improving the methodology for selecting an optimal spatial–traffic solution by combining the quantifiable results of the traffic microsimulation and the method of multi-criteria optimization. Socially sensitive design should include psychological and social evaluation criteria that are included in this paper as qualitative spatial–urban criteria. In the optimization process, different stakeholder groups (experts, students, and citizens) were actively involved in evaluating the importance of selected criteria. The analysis of stakeholders’ survey results showed statistically significant differences in criteria preference among three groups. The AHP (Analytic Hierarchy Process) multi-criteria analysis method was used; a total of five criteria groups (functional, safety, economic, environmental, and spatial–urban) were developed, which contain 21 criteria and 7 sub-criteria; and the weights of criteria groups were varied based on stakeholders’ preferences. The application of the developed methodology enabled the selection of an optimal solution for the improvement of traffic conditions in a small city with the potential to also be applied to other types of traffic–spatial problems and assure sustainable traffic planning.
Journal Article
Urbanism and transport in Germany : building blocks for architects and city and transport planners
\"Helmut Holzapfel's Urbanism and Transport in Germany, a bestseller in its own country, now available in English, examines the history and the future of urban design for transport in major European cities. Holzapfel shows the social impact of the automobile throughout German and European history, and the cultural, political, and economic processes that promoted it. From the unlikely birth of the automobile in Germany, and its shared history with the fascist government of 1933-1945, to new models of \"shared space\" and street and settlement networks, Holzapfel shows how the car has shaped the urban fabric of Europe, from roads, to neighborhoods and houses, to the city at large. Focusing not just on planning, but on historical, architectural, and economic factors, Urbanism and Transport in Germany offers new vistas and solutions to problems of urban sprawl and automobile-centric urban design\"--Provided by publisher.
Book
The universal visitation law of human mobility
Human mobility impacts many aspects of a city, from its spatial structure
1
–
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to its response to an epidemic
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–
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. It is also ultimately key to social interactions
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, innovation
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,
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and productivity
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. However, our quantitative understanding of the aggregate movements of individuals remains incomplete. Existing models—such as the gravity law
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,
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or the radiation model
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—concentrate on the purely spatial dependence of mobility flows and do not capture the varying frequencies of recurrent visits to the same locations. Here we reveal a simple and robust scaling law that captures the temporal and spatial spectrum of population movement on the basis of large-scale mobility data from diverse cities around the globe. According to this law, the number of visitors to any location decreases as the inverse square of the product of their visiting frequency and travel distance. We further show that the spatio-temporal flows to different locations give rise to prominent spatial clusters with an area distribution that follows Zipf’s law
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. Finally, we build an individual mobility model based on exploration and preferential return to provide a mechanistic explanation for the discovered scaling law and the emerging spatial structure. Our findings corroborate long-standing conjectures in human geography (such as central place theory
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and Weber’s theory of emergent optimality
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) and allow for predictions of recurrent flows, providing a basis for applications in urban planning, traffic engineering and the mitigation of epidemic diseases.
Using large-scale mobility data from diverse cities around the globe, a simple and robust scaling law that captures the temporal and spatial range of population movement is revealed.
Journal Article