scholarly journals Incorporating Multi-Modal Travel Planning into an Agent-Based Model: A Case Study at the Train Station Kellinghusenstraße in Hamburg

Land ◽  
2021 ◽  
Vol 10 (11) ◽  
pp. 1179
Author(s):  
Ulfia Annette Lenfers ◽  
Nima Ahmady-Moghaddam ◽  
Daniel Glake ◽  
Florian Ocker ◽  
Jonathan Ströbele ◽  
...  
Keyword(s):  
Public Transportation ◽  
Road Network ◽  
Route Planning ◽  
Multi Agent Systems ◽  
Individual Level ◽  
Dynamic Constraints ◽  
The Road ◽  
Intelligent Software ◽  
Bike Sharing ◽  
The Individual

Models can provide valuable decision support in the ongoing effort to create a sustainable and effective modality mix in urban settings. Modern transportation infrastructures must meaningfully combine public transport with other mobility initiatives such as shared and on-demand systems. The increase of options and possibilities in multi-modal travel implies an increase in complexity when planning and implementing such an infrastructure. Multi-agent systems are well-suited for addressing questions that require an understanding of movement patterns and decision processes at the individual level. Such models should feature intelligent software agents with flexible internal logic and accurately represent the core functionalities of new modalities. We present a model in which agents can choose between owned modalities, station-based bike sharing modalities, and free-floating car sharing modalities as they exit the public transportation system and seek to finish their personal multi-modal trip. Agents move on a multi-modal road network where dynamic constraints in route planning are evaluated based on an agent’s query. Modality switch points (MSPs) along the route indicate the locations at which an agent can switch from one modality to the next (e.g., a bike rental station to return a used rental bike and continue on foot). The technical implementation of MSPs within the road network was a central focus in this work. To test their efficacy in a controlled experimental setting, agents optimized only the travel time of their multi-modal routes. However, the functionalities of the model enable the implementation of different optimization criteria (e.g., financial considerations or climate neutrality) and unique agent preferences as well. Our findings show that the implemented MSPs enable agents to switch between modalities at any time, allowing for the kind of versatile, individual, and spontaneous travel that is common in modern multi-modal settings.

scholarly journals Macroscopic dynamics and the collapse of urban traffic

2018 ◽  
Vol 115 (50) ◽  
pp. 12654-12661 ◽  
Author(s):  
Luis E. Olmos ◽  
Serdar Çolak ◽  
Sajjad Shafiei ◽  
Meead Saberi ◽  
Marta C. González
Keyword(s):  
Travel Time ◽  
Road Network ◽  
Spatial Dynamics ◽  
Urban Traffic ◽  
Nonequilibrium Phase Transition ◽  
Vehicle Miles Traveled ◽  
The Road ◽  
Road Capacity ◽  
Total Vehicle ◽  
The Individual

Stories of mega-jams that last tens of hours or even days appear not only in fiction but also in reality. In this context, it is important to characterize the collapse of the network, defined as the transition from a characteristic travel time to orders of magnitude longer for the same distance traveled. In this multicity study, we unravel this complex phenomenon under various conditions of demand and translate it to the travel time of the individual drivers. First, we start with the current conditions, showing that there is a characteristic time τ that takes a representative group of commuters to arrive at their destinations once their maximum density has been reached. While this time differs from city to city, it can be explained by Γ, defined as the ratio of the vehicle miles traveled to the total vehicle distance the road network can support per hour. Modifying Γ can improve τ and directly inform planning and infrastructure interventions. In this study we focus on measuring the vulnerability of the system by increasing the volume of cars in the network, keeping the road capacity and the empirical spatial dynamics from origins to destinations unchanged. We identify three states of urban traffic, separated by two distinctive transitions. The first one describes the appearance of the first bottlenecks and the second one the collapse of the system. This collapse is marked by a given number of commuters in each city and it is formally characterized by a nonequilibrium phase transition.

scholarly journals Optimization of Evacuation and Walking-Home Routes from Osaka City After a Nankai Megathrust Earthquake Using Road Network Big Data

2021 ◽  
pp. 369-389
Author(s):  
Atsushi Takizawa ◽  
Yutaka Kawagishi
Keyword(s):  
Big Data ◽  
Public Transportation ◽  
Urban Areas ◽  
Road Network ◽  
Large Earthquake ◽  
The Road ◽  
Return Home ◽  
Flooded Area ◽  
Network Big Data ◽  
Surrounding Areas

AbstractWhen a disaster such as a large earthquake occurs, the resulting breakdown in public transportation leaves urban areas with many people who are struggling to return home. With people from various surrounding areas gathered in the city, unusually heavy congestion may occur on the roads when the commuters start to return home all at once on foot. In this chapter, it is assumed that a large earthquake caused by the Nankai Trough occurs at 2 p.m. on a weekday in Osaka City, where there are many commuters. We then assume a scenario in which evacuation from a resulting tsunami is carried out in the flooded area and people return home on foot in the other areas. At this time, evacuation and returning-home routes with the shortest possible travel times are obtained by solving the evacuation planning problem. However, the road network big data for Osaka City make such optimization difficult. Therefore, we propose methods for simplifying the large network while keeping those properties necessary for solving the optimization problem and then recovering the network. The obtained routes are then verified by large-scale pedestrian simulation, and the effect of the optimization is verified.

scholarly journals Impact of Road Network Topology on Public Transportation Development

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Minzhi Chen ◽  
Fan Wu ◽  
Min Yin ◽  
Jiangang Xu
Keyword(s):  
Public Transportation ◽  
Road Network ◽  
Road Networks ◽  
Urban Road Network ◽  
Urban Road ◽  
The Road ◽  
Layout Structure ◽  
Per Capita ◽  
Transportation Development ◽  
The Impact

Planning of road networks is fundamental for public transportation. The impact of road network density on public transportation has been extensively studied, but few studies in this regard involved evaluation indicators for connectivity and layout of road networks. With 29 cities in China as the study cases, this paper quantifies the layout structure of the road network based on the network’s betweenness centralization and establishes a multivariate linear regression model to perform regression of the logarithm of the frequency of per capita public transportation on betweenness centralization. It is found in the present work that there is a significant correlation between the layout structure of an urban road network and the residents’ utilization degree of public transportation. A greater betweenness centralization of the urban road network, namely a more centralized road network, means a higher frequency of per capita public transportation of urban residents and a higher degree of the residents’ utilization of public transportation. In the development of public transportation, centralized and axial-shaped layout structures of road networks can be promoted to improve the utilization of public transportation.

Analyzing Transit User Behavior with 51 Weeks of Smart Card Data

2019 ◽  
Vol 2673 (6) ◽  
pp. 33-45 ◽  
Author(s):  
Elodie Deschaintres ◽  
Catherine Morency ◽  
Martin Trépanier
Keyword(s):  
Smart Card ◽  
Public Transportation ◽  
Travel Behavior ◽  
Travel Demand ◽  
Public Transit ◽  
User Behavior ◽  
Individual Level ◽  
Smart Card Data ◽  
Demand Models ◽  
The Individual

A better understanding of mobility behaviors is relevant to many applications in public transportation, from more accurate travel demand models to improved supply adjustment, customized services and integrated pricing. In line with this context, this study mined 51 weeks of smart card (SC) data from Montréal, Canada to analyze interpersonal and intrapersonal variability in the weekly use of public transit. Passengers who used only one type of product (AP − annual pass, MP − monthly pass, or TB − ticket book) over 12 months were selected, amounting to some 200,000 cards. Data was first preprocessed and summarized into card-week vectors to generate a typology of weeks. The most popular weekly patterns were identified for each type of product and further studied at the individual level. Sequences of week clusters were constructed to represent the weekly travel behavior of each user over 51 weeks. They were then segmented by type of product according to an original distance, therefore highlighting the heterogeneity between passengers. Two indicators were also proposed to quantify intrapersonal regularity as the repetition of weekly clusters throughout the weeks. The results revealed MP owners have a more regular and diversified use of public transit. AP users are mainly commuters whereas TB users tend to be more occasional transit users. However, some atypical groups were found for each type of product, for instance users with 4-day work weeks and loyal TB users.

scholarly journals Which Green Space Metric Best Predicts a Lowered Odds of Type 2 Diabetes?

2021 ◽  
Vol 18 (8) ◽  
pp. 4088
Author(s):  
Soumya Mazumdar ◽  
Shanley Chong ◽  
Thomas Astell-Burt ◽  
Xiaoqi Feng ◽  
Geoffrey Morgan ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Road Network ◽  
Green Space ◽  
Estimating Equation ◽  
The Novel ◽  
Individual Level ◽  
Circular Buffer ◽  
Area Metric ◽  
The Individual

The choice of a green space metric may affect what relationship is found with health outcomes. In this research, we investigated the relationship between percent green space area, a novel metric developed by us (based on the average contiguous green space area a spatial buffer has contact with), in three different types of buffers and type 2 diabetes (T2D). We obtained information about diagnosed T2D and relevant covariates at the individual level from the large and representative 45 and Up Study. Average contiguous green space and the percentage of green space within 500 m, 1 km, and 2 km of circular buffer, line-based road network (LBRN) buffers, and polygon-based road network (PBRN) buffers around participants’ residences were used as proxies for geographic access to green space. Generalized estimating equation regression models were used to determine associations between access to green space and T2D status of individuals. It was found that 30%–40% green space within 500 m LBRN or PBRN buffers, and 2 km PBRN buffers, but not within circular buffers, significantly reduced the risk of T2D. The novel average green space area metric did not appear to be particularly effective at measuring reductions in T2D. This study complements an existing research body on optimal buffers for green space measurement.

scholarly journals Mining Topological Dependencies of Recurrent Congestion in Road Networks

2021 ◽  
Vol 10 (4) ◽  
pp. 248
Author(s):  
Nicolas Tempelmeier ◽  
Udo Feuerhake ◽  
Oskar Wage ◽  
Elena Demidova
Keyword(s):  
Network Topology ◽  
Real World ◽  
Public Transportation ◽  
Road Network ◽  
Road Networks ◽  
Traffic Load ◽  
Data Mining Algorithm ◽  
Urban Road ◽  
The Road ◽  
Spatio Temporal

The discovery of spatio-temporal dependencies within urban road networks that cause Recurrent Congestion (RC) patterns is crucial for numerous real-world applications, including urban planning and the scheduling of public transportation services. While most existing studies investigate temporal patterns of RC phenomena, the influence of the road network topology on RC is often overlooked. This article proposes the ST-Discovery algorithm, a novel unsupervised spatio-temporal data mining algorithm that facilitates effective data-driven discovery of RC dependencies induced by the road network topology using real-world traffic data. We factor out regularly reoccurring traffic phenomena, such as rush hours, mainly induced by the daytime, by modelling and systematically exploiting temporal traffic load outliers. We present an algorithm that first constructs connected subgraphs of the road network based on the traffic speed outliers. Second, the algorithm identifies pairs of subgraphs that indicate spatio-temporal correlations in their traffic load behaviour to identify topological dependencies within the road network. Finally, we rank the identified subgraph pairs based on the dependency score determined by our algorithm. Our experimental results demonstrate that ST-Discovery can effectively reveal topological dependencies in urban road networks.

scholarly journals ASSESSMENT OF THE FUNCTIONING OF MOTORWAY INTERNATIONAL TRANSPORT CORRIDORS OF UKRAINE

2020 ◽  
Vol 1 (46) ◽  
pp. 163-173
Author(s):  
Lanovoy O ◽  
◽  
Vyhovska I ◽  
Keyword(s):  
Road Network ◽  
Government Regulation ◽  
Full Range ◽  
Road Transport ◽  
The Road ◽  
Automated Highways ◽  
Public Road ◽  
Regulatory Frameworks ◽  
International Transport ◽  
The Individual

Formerly, international transport corridors (MTCs), solving problems of functioning and development of highways of Ukraine, with the application of the problems that have accumulated in the road complex, require systematic visits to a number of tasks, as well as: any number of civil servants has be open with the development and condition of the economy, as well as with the development of the transport system of Ukraine; the issue of the development of the road network, including international road transport corridors, should be considered in a comprehensive manner, regardless of the importance of the individual highways; coverage of the full range of issues, including improvements to governance, legislative and regulatory frameworks, government regulation, etc., is required. It is relevant to evaluate the functioning of international road transport corridors, which are part of the network of public roads of Ukraine. In order to improve the functioning of the public road network of Ukraine, it is necessary to develop new modern approaches to planning the development of this network, including international transport corridors. The purpose of the study is to prove the need to create a backbone network of «intelligent» automated highways within this network. KEYWORDS: ROAD NETWORK, FUNCTIONING, DEVELOPMENT, AN UNINTERRUPTED, SECURE AND CONVENIENT TRAFFIC FLOW

THE PRIORITY OF PUBLIC TRANSPORTATION, AS A METHOD OF IMPROVING THE FUNCTIONING OF THE ROAD NETWORK

2015 ◽  
Vol 2 (2) ◽  
pp. 661-665
Author(s):  
Лозовая ◽  
N. Lozovaya ◽  
Кущенко ◽  
S. Kushchenko ◽  
Кущенко ◽  
...  
Keyword(s):  
Public Transportation ◽  
Road Network ◽  
Basic Problem ◽  
Passenger Transport ◽  
The Road

The article describes the cause and the result of the growth of motorization. One reason is the problem of dependency of the population by passenger transport. The basic problem in the work of city passenger transport and measures for their elimination. Describes measures to reduce traffic in towns and their centers, special attention is paid to the priority of public transportation.

scholarly journals Optimization Model for the Supply Volume of Bike-Sharing: Case Study in Nanjing, China

Information ◽  
2021 ◽  
Vol 12 (5) ◽  
pp. 182
Author(s):  
Jiajie Yu ◽  
Yanjie Ji ◽  
Chenyu Yi ◽  
Chenchen Kuai ◽  
Dmitry Ivanovich Samal
Keyword(s):  
Optimization Model ◽  
Road Network ◽  
Optimal Solution ◽  
Traffic Analysis ◽  
Urban Traffic ◽  
Mixed Integer ◽  
The Road ◽  
Bike Sharing ◽  
Flow Conservation ◽  
Parking Facilities

In order to solve the oversupply and repositioning problems of bike-sharing, this paper proposes an optimization model to obtain a reasonable supply volume scheme for bike-sharing and infrastructure configuration planning. The optimization model is constrained by the demand for bike-sharing, urban traffic carrying capacity (road network and parking facilities carrying capacities), and the flow conservation of shared bikes in each traffic analysis zone. The model was formulated through mixed-integer programming with the aim of minimizing the total costs for users and bike-sharing enterprises (including the travel cost of users, production and maintenance costs of shared bikes, and repositioning costs). CPLEX was used to obtain the optimal solution for the model. Then, the optimization model was applied to 183 traffic analysis zones in Nanjing, China. The results showed that not only were user demands met, but the load ratios of the road network and parking facilities with respect to bike-sharing in each traffic zone were all decreased to lower than 1.0 after the optimization, which established the rationality and effectiveness of the optimization results.

scholarly journals Psychopathology and Neurocognition in the Era of the p-Factor: The Current Landscape and the Road Forward

2021 ◽  
Vol 2 (3) ◽  
pp. 233-249
Author(s):  
Darren Haywood ◽  
Frank D. Baughman ◽  
Barbara A. Mullan ◽  
Karen R. Heslop
Keyword(s):  
Structural Models ◽  
Thought Disorder ◽  
Neurocognitive Functioning ◽  
Neurocognitive Deficits ◽  
Neurocognitive Performance ◽  
Individual Level ◽  
The Road ◽  
Theoretical Perspectives ◽  
The Individual ◽  
P Factor

Neurocognitive abilities have frequently been claimed to be involved in the aetiology of psychopathology. Neurocognitive deficits have been reported across many disorders, and theoretical perspectives associate these deficits to the onset and maintenance of the symptomology. Recently, the heterogeneity of symptoms, and comorbidity of disorders, have motivated the development of structural models of psychopathology. Structural models indicate that factors such as internalising, externalising, thought disorder and the p-factor account for a wide variety of symptomology. It is unclear how neurocognitive abilities are best examined within these structures to advance our understanding of psychopathology. In this paper, we use Caspi et al.’s seminal writings as a framework to describe how neurocognitive abilities have been previously associated with categorical disorders and recently associated, and claimed to drive, the factors of psychopathology. We discuss the implications of the p-factor as a substantive construct or statistical artefact, and how this impacts the exploration of neurocognitive abilities and psychopathology. Further, we provide the case for alternative structural approaches, describe an innovative hypothesis of neurocognitive functioning, the multidimensional hypothesis, and explain how this may further our understanding of the heterogeneity of neurocognitive performance and psychopathology at the individual level. Finally, we provide a road forward for the future examination of neurocognitive abilities in psychopathology.

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