GIS-based analytical tools for transport planning: spatial regression models for transportation demand forecast

Considering the importance of spatial issues in transport planning, the main objective of this study was to analyze the results obtained from different approaches of spatial regression models. In the case of spatial autocorrelation, spatial dependence patterns should be incorporated in the models, since that dependence may affect the predictive power of these models. The results obtained with the spatial regression models were also compared with the results of a multiple linear regression model that is typically used in trips generation estimations. The findings support the hypothesis that the inclusion of spatial effects in regression models is important, since the best results were obtained with alternative models (spatial regression models or the ones with spatial variables included). This was observed in a case study carried out in the city of Porto Alegre, in the state of Rio Grande do Sul, Brazil, in the stages of specification and calibration of the models, with two distinct datasets.

A way forward for land-use planning to achieve policy goals by using spatial modelling scenarios

This paper investigates how demographic (socioeconomic) and land-use (physical and environmental) data can be integrated within a decision support framework to formulate and evaluate land-use planning scenarios. A case-study approach is undertaken with land-use planning scenarios for a rapidly growing coastal area in Australia, the Shire of Hervey Bay. The town and surrounding area require careful planning of the future urban growth between competing land uses. Three potential urban growth scenarios are put forth to address this issue. Scenario A ('continued growth') is based on existing socioeconomic trends. Scenario B ('maximising rates base') is derived using optimisation modelling of land-valuation data. Scenario C ('sustainable development') is derived using a number of social, economic, and environmental factors and assigning weightings of importance to each factor using a multiple criteria analysis approach. The land-use planning scenarios are presented through the use of maps and tables within a geographical information system, which delineate future possible land-use allocations up until 2021. The planning scenarios are evaluated by using a goal-achievement matrix approach. The matrix is constructed with a number of criteria derived from key policy objectives outlined in the regional growth management framework and town planning schemes. The authors of this paper examine the final efficiency scores calculated for each of the three planning scenarios and discuss the advantages and disadvantages of the three land-use modelling approaches used to formulate the final scenarios.

Spatial-temporal mining of archived automatic vehicle location (AVL) data for transit service planning applications

An Automatic Vehicle Location (AVL) system is a computer-based vehicle tracking system that is capable of determining a vehicle's location in real time. As a major technology of the Advanced Public Transportation System (APTS), AVL systems have been widely deployed by transit agencies for purposes such as real-time operation monitoring, computer-aided dispatching, and arrival time prediction. AVL systems make a large amount of transit performance data available that are valuable for transit performance management and planning purposes. However, the difficulties of extracting useful information from the huge spatial-temporal database have hindered off-line applications of the AVL data. ^ In this study, a data mining process, including data integration, cluster analysis, and multiple regression, is proposed. The AVL-generated data are first integrated into a Geographic Information System (GIS) platform. The model-based cluster method is employed to investigate the spatial and temporal patterns of transit travel speeds, which may be easily translated into travel time. The transit speed variations along the route segments are identified. Transit service periods such as morning peak, mid-day, afternoon peak, and evening periods are determined based on analyses of transit travel speed variations for different times of day. The seasonal patterns of transit performance are investigated by using the analysis of variance (ANOVA). Travel speed models based on the clustered time-of-day intervals are developed using important factors identified as having significant effects on speed for different time-of-day periods. ^ It has been found that transit performance varied from different seasons and different time-of-day periods. The geographic location of a transit route segment also plays a role in the variation of the transit performance. The results of this research indicate that advanced data mining techniques have good potential in providing automated techniques of assisting transit agencies in service planning, scheduling, and operations control. ^

Housing and Planning in London under the Conservative Government: Spatial impacts, social polarisation, sustainable development and social justice

This paper will be based on my continuing research on planning and housing development in London. It will focus on the proposals in the Government’s Housing and Planning Bill, which are likely to be enacted in Spring 2016. It will review the evidence of potential spatial impacts in terms of the supply of existing affordable homes and the location and affordability of new supply. This will be related to a review of the alternative development options for London’s growth in the context of the Mayor of London’s draft 2050 Infrastructure Plan. The paper will analyse the potential impact of new Government policy and legislation on whether London’s housing requirements can be delivered in accordance with the objectives of sustainable planning and social justice, and will also consider the constraints on the ability of the new Mayor of London, to be elected in May 2016 to achieve manifesto commitments.

Spatial Data Systems for Transportation Planning, 1997

The objective of this research was to develop a methodology for transforming and dynamically segmenting data. Dynamic segmentation enables transportation system attributes and associated data to be stored in separate tables and merged when a specific query requires a particular set of data to be considered. A major benefit of dynamic segmentation is that individual tables can be more easily updated when attributes, performance characteristics, or usage patterns change over time. Applications of a progressive geographic database referencing system in transportation planning are vast. Summaries of system condition and performance can be made, and analyses of specific portions of a road system are facilitated.

Governance and effectiveness in regional planning: an analysis of North American, European, and Australasian practice

Over the past several years, there has been resurgent interest in regional planning in North America, Europe and Australasia. Spurred by issues such as metropolitan growth, transportation infrastructure, environmental management and economic development, many states and metropolitan regions are undertaking new planning initiatives. These regional efforts have also raised significant question about governance structures, accountability and measures of effectiveness.n this paper, the authors conducted an international review of ten case studies from the United States, Canada, England, Belgium, New Zealand and Australia to explore several critical questions. Using qualitative data template, the research team reviewed plans, documents, web sites and published literature to address three questions. First, what are the governance arrangements for delivering regional planning? Second, what are the mechanisms linking regional plans with state plans (when relevant) and local plans? Third, what means and mechanisms do these regional plans use to evaluate and measure effectiveness? The case study analysis revealed several common themes. First, there is an increasing focus on goverance at the regional level, which is being driven by a range of trends, including regional spatial development initiatives in Europe, regional transportation issues in the US, and the growth of metropolitan regions generally. However, there is considerable variation in how regional governance arrangements are being played out. Similarly, there is a range of processes being used at the regional level to guide planning that range from broad ranging (thick) processes to narrow and limited (thin) approaches. Finally, evaluation and monitoring of regional planning efforts are compiling data on inputs, processes, outputs and outcomes. Although there is increased attention being paid to indicators and monitoring, most of it falls into outcome evaluations such as Agenda 21 or sustainability reporting. Based on our review we suggest there is a need for increased attention on input, process and output indicators and clearer linkages of these indicators in monitoring and evaluation frameworks. The focus on outcome indicators, such as sustainability indicators, creates feedback systems that are too long-term and remote for effective monitoring and feedback. Although we found some examples of where these kinds of monitoring frameworks are linked into a system of governance, there is a need for clearer conceptual development for both theory and practice.

Planning for smart urban ecosystems : information technology applications for capacity building in environmental decision making

Since the industrial revolution, our world has experienced rapid and unplanned industrialization and urbanization. As a result, we have had to cope with serious environmental challenges. In this context, an explanation of how smart urban ecosystems can emerge, gains a crucial importance. Capacity building and community involvement have always been key issues in achieving sustainable development and enhancing urban ecosystems. By considering these, this paper looks at new approaches to increase public awareness of environmental decision making. This paper will discuss the role of Information and Communication Technologies (ICT), particularly Webbased Geographic Information Systems (Web-based GIS) as spatial decision support systems to aid public participatory environmental decision making. The paper also explores the potential and constraints of these webbased tools for collaborative decision making.

Multi-objective mission flight planning in civil unmanned aerial systems

Unmanned Aerial Vehicles (UAVs) are emerging as an ideal platform for a wide range of civil applications such as disaster monitoring, atmospheric observation and outback delivery. However, the operation of UAVs is currently restricted to specially segregated regions of airspace outside of the National Airspace System (NAS). Mission Flight Planning (MFP) is an integral part of UAV operation that addresses some of the requirements (such as safety and the rules of the air) of integrating UAVs in the NAS. Automated MFP is a key enabler for a number of UAV operating scenarios as it aids in increasing the level of onboard autonomy. For example, onboard MFP is required to ensure continued conformance with the NAS integration requirements when there is an outage in the communications link. MFP is a motion planning task concerned with finding a path between a designated start waypoint and goal waypoint. This path is described with a sequence of 4 Dimensional (4D) waypoints (three spatial and one time dimension) or equivalently with a sequence of trajectory segments (or tracks). It is necessary to consider the time dimension as the UAV operates in a dynamic environment. Existing methods for generic motion planning, UAV motion planning and general vehicle motion planning cannot adequately address the requirements of MFP. The flight plan needs to optimise for multiple decision objectives including mission safety objectives, the rules of the air and mission efficiency objectives. Online (in-flight) replanning capability is needed as the UAV operates in a large, dynamic and uncertain outdoor environment. This thesis derives a multi-objective 4D search algorithm entitled Multi- Step A* (MSA*) based on the seminal A* search algorithm. MSA* is proven to find the optimal (least cost) path given a variable successor operator (which enables arbitrary track angle and track velocity resolution). Furthermore, it is shown to be of comparable complexity to multi-objective, vector neighbourhood based A* (Vector A*, an extension of A*). A variable successor operator enables the imposition of a multi-resolution lattice structure on the search space (which results in fewer search nodes). Unlike cell decomposition based methods, soundness is guaranteed with multi-resolution MSA*. MSA* is demonstrated through Monte Carlo simulations to be computationally efficient. It is shown that multi-resolution, lattice based MSA* finds paths of equivalent cost (less than 0.5% difference) to Vector A* (the benchmark) in a third of the computation time (on average). This is the first contribution of the research. The second contribution is the discovery of the additive consistency property for planning with multiple decision objectives. Additive consistency ensures that the planner is not biased (which results in a suboptimal path) by ensuring that the cost of traversing a track using one step equals that of traversing the same track using multiple steps. MSA* mitigates uncertainty through online replanning, Multi-Criteria Decision Making (MCDM) and tolerance. Each trajectory segment is modeled with a cell sequence that completely encloses the trajectory segment. The tolerance, measured as the minimum distance between the track and cell boundaries, is the third major contribution. Even though MSA* is demonstrated for UAV MFP, it is extensible to other 4D vehicle motion planning applications. Finally, the research proposes a self-scheduling replanning architecture for MFP. This architecture replicates the decision strategies of human experts to meet the time constraints of online replanning. Based on a feedback loop, the proposed architecture switches between fast, near-optimal planning and optimal planning to minimise the need for hold manoeuvres. The derived MFP framework is original and shown, through extensive verification and validation, to satisfy the requirements of UAV MFP. As MFP is an enabling factor for operation of UAVs in the NAS, the presented work is both original and significant.

The planning of airport regions and National Aviation Policy Issues and challenges in the Australian experience 2008-2009

The planning of airports has long been contentious because of their localisation of negative impacts. The globalisation, commercialisation and deregulation of the aviation industry has unleashed powerful new economic forces both on and offairport. Over the last two decades, many airports have evolved into airport cities located at the heart of the wider aerotropolis region. This shifts the appropriate scale of planning analysis towards broader regional concerns. However,governments have been slow to respond and airport planning usually remains poorly integrated with local, city and regional planning imperatives. The Australian experience exemplifies the divide. The privatization of major Australian airports from 1996 has seen billions of dollars spent on new airside and landside infrastructure but with little oversight from local and state authorities because the ultimate authority for on-airport development is the Federal Minister for Transport. Consequently, there have been growing tensions in many major airport regions between the private airport lessee and the broader community, exacerbated by both the building of highly conspicuous non-aeronautical developments and growing airport area congestion. This paper examines the urban planning content of Australia’s national aviation policy review (2008-09) with reference to current and potential opportunities for all-of-region collaboration in the planning process.

A planning support system for airport city development

Many airports around the world are diversifying their land use strategies to integrate non-aeronautical development. These airports embrace the “airport city” concept to develop a wide range of commercial and light industrial land uses to support airport revenues. The consequences of this changing urban form are profound for both airport and municipal planners alike and present numerous challenges with regard to integration of airport and regional planning. While several tools exist for regional planning and airport operational planning, no holistic airport landside and regional planning tool exist. What is required is a planning support system that can integrate the sometimes conflicting stakeholder interests into one common goal for the airport and the surrounding region. This paper presents a planning support system and evaluates its application to a case study involving Brisbane Airport and the South East Queensland region in Australia.

Important omitted spatial variables in safety models: Understanding contributing crash causes at intersections

Advances in safety research—trying to improve the collective understanding of motor vehicle crash causation—rests upon the pursuit of numerous lines of inquiry. The research community has focused on analytical methods development (negative binomial specifications, simultaneous equations, etc.), on better experimental designs (before-after studies, comparison sites, etc.), on improving exposure measures, and on model specification improvements (additive terms, non-linear relations, etc.). One might think of different lines of inquiry in terms of ‘low lying fruit’—areas of inquiry that might provide significant improvements in understanding crash causation. It is the contention of this research that omitted variable bias caused by the exclusion of important variables is an important line of inquiry in safety research. In particular, spatially related variables are often difficult to collect and omitted from crash models—but offer significant ability to better understand contributing factors to crashes. This study—believed to represent a unique contribution to the safety literature—develops and examines the role of a sizeable set of spatial variables in intersection crash occurrence. In addition to commonly considered traffic and geometric variables, examined spatial factors include local influences of weather, sun glare, proximity to drinking establishments, and proximity to schools. The results indicate that inclusion of these factors results in significant improvement in model explanatory power, and the results also generally agree with expectation. The research illuminates the importance of spatial variables in safety research and also the negative consequences of their omissions.