Access Surplus: Valuing Accessibility by Integrating Opportunity Supply and Willingness to Pay

The prevalence of widespread poverty and deprivation in South Asian countries points towards the need to adopt a wider concept of social security that would include both promotional and protective social security. This article advocates this view against the backdrop of the coverage and financing of existing social security programmes and points to the inadequacies of these measures in attaining the objectives of higher economic growth and the eradication of poverty. A character istic feature of current social security programmes in South Asian economies is that they are designed in a conceptual vacuum and are implemented mainly as wel fare measures. The emphasis is on promotional measures and even within that cat egory, on poverty alleviation programmes. A balanced provision of promotional and protective social security measures is not evident in any country. Some esti mates of the resource requirements for providing such balanced social security suggest that the cumulative cost of essential human investment over the period 1995-2010 would be over 4-5 per cent of GDP. Such allocation of resources towards the wider connotation of social security is essential for the South Asian countries to reap the benefits of the linkages between social attainments and eco nomic growth, a la East Asia.

This chapter gives an overviewof the content of the book. The book deals with a new approach to logit type discrete choice probability models – for transportation networks in particular. The models are derived from a new definition of cost-minimizing behavior – the likelihood of a sample is decreasing as a function of average cost. The formal definitions are given in Chap. 4: Definition 1 (multinomial logit model) and Definition 4 (general logit model). The results for the multinomial logit model and the general logit model are obtained in Propositions 1 and 3 respectively. All logit type choice probability functions satisfy the new definition. The new definition is in Part I applied to networks with constant link costs. It is shown that the simple (multinomial) logit model exhibits cost-minimizing behavior. Furthermore cost-minimizing behavior implies the logit model. A number of standard logit models are derived – stochastic route choice model, multi-attribute discrete choice model, gravity model and the general logit model. New structured logit models, different from the standard nested logit model, are obtained. A welfare measure based on cost and a measure of freedom of choice is given. The new welfare measure is shown to be identical with composite cost. The presence of cost-minimizing behavior in an observed data set can be investigated by using the property that the likelihood is decreasing as a function of average cost. This is used in constructing a graphical test for cost-minimizing behavior. In Part II of the book the new definition of cost-minimizing behavior is extended to the case of volume dependent separable link costs. Here equilibrium is studied. Cost-minimizing behavior implies that the most probable trip patterns are user equilibria. The most probable flow patterns are approximately obtained by solving the optimization problem obtained by relaxing the integer constraints and replacing the cumulative cost function with the Beckmann integral.Models are derived for route choice, combined choice of origin, destination and route as well as combined choice of origin, destination, mode and route.KeywordsLogit ModelAverage CostRoute ChoiceChoice ProbabilityUser EquilibriumThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Road hazardous material transportation plays a critical role in road traffic management. Due to the dangerous nature of the cargo, hazardous material transportation trucks (HMTTs) have different route selection and driving characteristics compared to traditional freight trucks. These differences lead to unique travel and emission patterns, which in turn affect traffic management strategies and emission control measures. However, existing research predominantly focuses on safety aspects related to individual vehicle behavior, with limited exploration of the broader travel and emission characteristics of HMTTs. To bridge this gap, this study develops a comprehensive framework for analyzing the travel patterns and emissions of HMTTs. The methodology begins by applying a Gaussian mixture distribution model to identify vehicle stop points, eliminating biases associated with subjective settings. Origin–destination (OD) pairs are then determined through stop time clustering, followed by the extraction of travel characteristics using non-negative matrix factorization. Emissions are subsequently calculated based on the identified trip data. The relationship between emissions and land use characteristics is further analyzed using geographically weighted regression (GWR). Crucially, this study leverages data from the BeiDou Satellite Navigation System, focusing on HMTTs operating within Shanghai. The processed data reveal three distinct travel modes of HMTTs, categorized by spatiotemporal patterns: Daytime—Surrounding cities, Early morning—In-city, and Midnight—Scattered. Moreover, unlike other road vehicles, HMTT emissions are heavily influenced by industrial and company-related points of interest (POIs). These findings highlight the significant role of BeiDou Satellite Navigation System data in optimizing HMTT management strategies to reduce emissions and improve overall safety.

Improving urban mobility, especially pedestrian mobility, is a current challenge in virtually every city worldwide. To calculate the least-cost paths and safer, more efficient routes, it is necessary to understand the geometry of streets and their various elements accurately. In this study, we propose a semi-automatic methodology to assess the capacity of urban spaces to enable adequate pedestrian mobility. We employ various data sources, but primarily point clouds obtained through a mobile laser scanner (MLS), which provide a wealth of highly detailed information about the geometry of street elements. Our method allows us to characterize preferred pedestrian-traffic zones by segmenting crosswalks, delineating sidewalks, and identifying obstacles and impediments to walking in urban routes. Subsequently, we generate different displacement cost surfaces and identify the least-cost origin–destination paths. All these factors enable a detailed pedestrian mobility analysis, yielding results on a raster with a ground sampling distance (GSD) of 10 cm/pix. The method is validated through its application in a case study analyzing pedestrian mobility around an educational center in a purely urban area of A Coruña (Galicia, Spain). The segmentation model successfully identified all pedestrian crossings in the study area without false positives. Additionally, obstacle segmentation effectively identified urban elements and parked vehicles, providing crucial information to generate precise friction surfaces reflecting real environmental conditions. Furthermore, the generation of cumulative displacement cost surfaces allowed for identifying optimal routes for pedestrian movement, considering the presence of obstacles and the availability of traversable spaces. These surfaces provided a detailed representation of pedestrian mobility, highlighting significant variations in travel times, especially in areas with high obstacle density, where differences of up to 15% were observed. These results underscore the importance of considering obstacles’ existence and location when planning pedestrian routes, which can significantly influence travel times and route selection. We consider the capability to generate accurate cumulative cost surfaces to be a significant advantage, as it enables urban planners and local authorities to make informed decisions regarding the improvement of pedestrian infrastructure.

The increase in population and motorized vehicles in Bengkalis City has led to greater demand for public transportation, which remains insufficient in meeting accessibility needs. This study aims to develop a model for planning public transportation routes using Geographic Information System (GIS) tools to improve accessibility in Bengkalis City. The study employs primary data from field surveys and secondary data from relevant agencies. GIS-based spatial analysis methods, such as service area analysis and the Origin-Destination (OD) matrix, are applied to evaluate accessibility and passenger movement patterns. The analysis results in two route alternatives assessed based on stop point density, community accessibility, and passenger distribution. The first alternative is identified as more effective in serving population centers and minimizing service gaps. The findings provide a spatially grounded approach to transportation planning and may support local efforts to improve public transport coverage.