Land-Use Transport Interaction: State of the Art

This paper investigates innovative approaches to the integration of land-use and transport planning in urban regions. Engineering, economic and social-science based theories and empirical studies are analyzed regarding their ability to explain the interaction between land use and transport - that land use determines traffic flows and that transport infrastructure changes land-use patterns. In addition, this paper provides an overview of the state of the art of computer models for the simulation of land use and transport. Based on these theories and models the effectiveness of policies to influence land use and transport in urban regions is assessed.Urban location theory, transportation research, land use- transport interaction, urban simulation modeling, location choice

A simulation of segregation in cities and its application for the analysis of price regulation

Social segregation in cities takes place where different household groups exist and when, according to Schelling, their location choice either minimizes the number of differing households in their neighbourhood or maximizes their own group. In this contribution an evolutionary simulation based on a monocentric city model with externalities among households is used to discuss the spatial segregation patterns of four groups. The resulting complex spatial patterns can be shown as graphic animations. They can be applied as initial situation for the analysis of the effects a price regulation has on segregation. JEL classification: D62, R14, R31, R52 Keywords: simulation, segregation, monocentric city, price regulation

Social-aware Forwarding in Opportunistic Wireless Networks: Content Awareness or Obliviousness?

With the current host-based Internet architecture, networking faces limitations in dynamic scenarios, due mostly to host mobility. The ICN paradigm mitigates such problems by releasing the need to have an end-to-end transport session established during the life time of the data transfer. Moreover, the ICN concept solves the mismatch between the Internet architecture and the way users would like to use it: currently a user needs to know the topological location of the hosts involved in the communication when he/she just wants to get the data, independently of its location. Most of the research efforts aim to come up with a stable ICN architecture in fixed networks, with few examples in ad-hoc and vehicular networks. However, the Internet is becoming more pervasive with powerful personal mobile devices that allow users to form dynamic networks in which content may be exchanged at all times and with low cost. Such pervasive wireless networks suffer with different levels of disruption given user mobility, physical obstacles, lack of cooperation, intermittent connectivity, among others. This paper discusses the combination of content knowledge (e.g., type and interested parties) and social awareness within opportunistic networking as to drive the deployment of ICN solutions in disruptive networking scenarios. With this goal in mind, we go over few examples of social-aware content-based opportunistic networking proposals that consider social awareness to allow content dissemination independently of the level of network disruption. To show how much content knowledge can improve social-based solutions, we illustrate by means of simulation some content-oblivious/oriented proposals in scenarios based on synthetic mobility patterns and real human traces.Comment: 7 pages, 6 figure

The Role of Spatial Interaction in Social Networks

This article addresses the role of spatial interaction in social networks. We analyse empirical data describing a network of leisure contacts and show that the probability to accept a person as a contact scales in distance with similar to d (-aEuro parts per thousand 1.4). Moreover, the analysis reveals that the number of contacts an individual possesses is independent from its spatial location and the spatial distribution of opportunities. This means that individuals living in areas with a low accessibility to other persons (rural areas) exhibit at average the same number of contacts compared to individuals living in areas with high accessibility (urban areas). Low accessibility is thus compensated with a higher background probability to accept other candidates as social contacts. In addition, we propose a model for large-scale social networks involving a spatial and social interaction between individuals. Simulation studies are conducted using a synthetic population based on census data as input. The results show that the model is capable of reproducing the spatial structure, but, however, fails to reproduce other topological characteristics. Both, the analysis of empirical data and the simulation results provide a further evidence that spatial interaction is a crucial aspect of social networks. Yet, it appears that spatial proximity does only explain the spatial structure of a network but has no significant impact on its topology

Achieving a Jobs-Housing balance in the Paris region - the potential of reducing car trafic

Many experts believe that the uninterrupted lengthening of trip distances, and especially trip-to-work distances, is carried mostly by urban sprawl combined to growing functional (economic functions/residential functions) and social (high-class residential areas/low-class residential areas) specialization of urban space. According to them, these three dynamics (urban sprawl - functional specialization - social specialization) drag along quantitative and qualitative spatial imbalances between economic and residential functions and these spatial imbalances contribute to widen the distance separating workers' homes and job places, and hence, to lenghten the trips-to-work. On the basis of this diagnosis, the re-establishement of a greater balance, on both quantitative and qualitative grounds, between jobs and housing in different areas of the city is currently emerging as a major issue regarding the car-traffic reducing goal. Making the assumption that the multiplication of long-distance trips occurs as a consequence of greater difficulties encountered by households searching decent housing nearby workplaces, many experts argue that efficient urban policies promoting a diversified housing supply nearby job centres would allow more reasonable commuting distances and that such a return should go forth with a reduction in car traffic. In this paper, through a simulation model based on re-assignment of households closer to their workplaces, we examine the potential of car traffic reduction in the case of the Paris region. More precisely the impact of jobs-housing balance policy is based on a simulation model which states assignment of households located far from their work place within zones located nearer to the work place. The households that are reassigned are those where all workers travel more than a given time-threshold to reach their work place. These households are relocated within a perimeter around either the work place of the head of the household if it is a one worker household or the work place of the female worker if it is a two worker household - this perimeter is defined with reference to a time-threshold (set to 20, 30 or 45 minutes by private car or by public transport). For each type of household (defined according to social status, number of workers and family profile), the type of housing demanded by reassigned households is derived from the structure of housing detained by households that are already located within the perimeter of re-assignment. Three analyses are conducted on the basis of this simulation. According to the different time-thresholds : first, we estimate the total distances saved on home-work trips by private car when households are reassigned. Second, we identify the characteristics of reassigned households (especially social status, number of workers, family profile, residential location, job location, etc.). Third, we estimate the housing offer/demand imbalance after re-assignment (with specific interest for the case of housing for low-income groups).

A Proposed Hybrid Effect Size Plus p -Value Criterion: Empirical Evidence Supporting its Use

DOI: 10.1080/00031305.2018.1564697 When the editors of Basic and Applied Social Psychology effectively banned the use of null hypothesis significance testing (NHST) from articles published in their journal, it set off a fire-storm of discussions both supporting the decision and defending the utility of NHST in scientific research. At the heart of NHST is the p-value which is the probability of obtaining an effect equal to or more extreme than the one observed in the sample data, given the null hypothesis and other model assumptions. Although this is conceptually different from the probability of the null hypothesis being true, given the sample, p-values nonetheless can provide evidential information, toward making an inference about a parameter. Applying a 10,000-case simulation described in this article, the authors found that p-values’ inferential signals to either reject or not reject a null hypothesis about the mean (α = 0.05) were consistent for almost 70% of the cases with the parameter’s true location for the sampled-from population. Success increases if a hybrid decision criterion, minimum effect size plus p-value (MESP), is used. Here, rejecting the null also requires the difference of the observed statistic from the exact null to be meaningfully large or practically significant, in the researcher’s judgment and experience. The simulation compares performances of several methods: from p-value and/or effect size-based, to confidence-interval based, under various conditions of true location of the mean, test power, and comparative sizes of the meaningful distance and population variability. For any inference procedure that outputs a binary indicator, like flagging whether a p-value is significant, the output of one single experiment is not sufficient evidence for a definitive conclusion. Yet, if a tool like MESP generates a relatively reliable signal and is used knowledgeably as part of a research process, it can provide useful information

Modelling Social Care Provision in An Agent-Based Framework with Kinship Networks

Current demographic trends in the UK include a fast-growing elderly population and dropping birth rates, and demand for social care amongst the aged is rising. The UK depends on informal social care -- family members or friends providing care -- for some 50\% of care provision. However, lower birth rates and a graying population mean that care availability is becoming a significant problem, causing concern amongst policy-makers that substantial public investment in formal care will be required in decades to come. In this paper we present an agent-based simulation of care provision in the UK, in which individual agents can decide to provide informal care, or pay for private care, for their loved ones. Agents base these decisions on factors including their own health, employment status, financial resources, relationship to the individual in need, and geographical location. Results demonstrate that the model can produce similar patterns of care need and availability as is observed in the real world, despite the model containing minimal empirical data. We propose that our model better captures the complexities of social care provision than other methods, due to the socioeconomic details present and the use of kinship networks to distribute care amongst family members.Comment: 15 pages, 12 figure

Socially Compliant Navigation through Raw Depth Inputs with Generative Adversarial Imitation Learning

We present an approach for mobile robots to learn to navigate in dynamic environments with pedestrians via raw depth inputs, in a socially compliant manner. To achieve this, we adopt a generative adversarial imitation learning (GAIL) strategy, which improves upon a pre-trained behavior cloning policy. Our approach overcomes the disadvantages of previous methods, as they heavily depend on the full knowledge of the location and velocity information of nearby pedestrians, which not only requires specific sensors, but also the extraction of such state information from raw sensory input could consume much computation time. In this paper, our proposed GAIL-based model performs directly on raw depth inputs and plans in real-time. Experiments show that our GAIL-based approach greatly improves the safety and efficiency of the behavior of mobile robots from pure behavior cloning. The real-world deployment also shows that our method is capable of guiding autonomous vehicles to navigate in a socially compliant manner directly through raw depth inputs. In addition, we release a simulation plugin for modeling pedestrian behaviors based on the social force model.Comment: ICRA 2018 camera-ready version. 7 pages, video link: https://www.youtube.com/watch?v=0hw0GD3lkA

COMPARING THE PROFITABILITY OF CASSAVA-BASED PRODUCTION SYSTEMS IN THREE WEST AFRICAN COUNTRIES: COTE D'IVOIRE, GHANA AND NIGERIA

Sub-Saharan Africa (SSA) cassava-producing countries such as Nigeria, Ghana, and Côte d'Ivoire have developed, in recent years, a renewed interest in cassava as an alternative food crop. This has led to a major expansion in cassava-based production systems in Nigeria and Ghana, whereas there has been a slower growth in Côte d'Ivoire (Nweke et al., 1998). This paper is based on the argument that the difference in various factors such as agricultural policies (i.e., trade and price policies, domestic production taxes or subsidies), location and technologies (production and processing) between Nigeria, Ghana and Côte d'Ivoire the difference in the level of growth in cassava-based production systems. The paper examines, using the Policy Analysis Matrix (PAM), the magnitude of the impact of these factors on the private and social profitability of cassava production and post-production processing in Côte d'Ivoire, Ghana and Nigeria. The topic has not been examined in previous studies. The paper relies primarily on data for Côte d'Ivoire, Ghana and Nigeria from the Collaborative Study of Cassava in Africa (COSCA) survey. The baseline results demonstrate the similarity in efficiencies of production in these West African countries. The simulation findings indicated that, in Côte d'Ivoire, farmers benefited from the depreciation of the equilibrium exchange rate while farmers in Ghana and Nigeria suffered losses. Simulation results also indicated that Ivorian and Ghanaian cassava/maize farmers could benefit from growing IITA's improved variety and adopting mechanized processing methods.Crop Production/Industries,