Understanding Space: the nascent synthesis of cognition and the syntax of spatial morphologies

24-28 September, 200

Calibration and Validation of A Shared space Model: A Case Study

Shared space is an innovative streetscape design that seeks minimum separation between vehicle traffic and pedestrians. Urban design is moving toward space sharing as a means of increasing the community texture of street surroundings. Its unique features aim to balance priorities and allow cars and pedestrians to coexist harmoniously without the need to dictate behavior. There is, however, a need for a simulation tool to model future shared space schemes and to help judge whether they might represent suitable alternatives to traditional street layouts. This paper builds on the authors’ previously published work in which a shared space microscopic mixed traffic model based on the social force model (SFM) was presented, calibrated, and evaluated with data from the shared space link typology of New Road in Brighton, United Kingdom. Here, the goal is to explore the transferability of the authors’ model to a similar shared space typology and investigate the effect of flow and ratio of traffic modes. Data recorded from the shared space scheme of Exhibition Road, London, were collected and analyzed. The flow and speed of cars and segregation between pedestrians and cars are greater on Exhibition Road than on New Road. The rule-based SFM for shared space modeling is calibrated and validated with the real data. On the basis of the results, it can be concluded that shared space schemes are context dependent and that factors such as the infrastructural design of the environment and the flow and speed of pedestrians and vehicles affect the willingness to share space

Traffic simulation in 3D world

This paper is the result of more than three months of research completed at the School of the Built Environment, Virtual Environment Suite. This study focusing on measuring the impacts of a change in the infrastructure using a 3D traffic simulation model. Various aspects about the research area and the simulation model were explained. Details on technical aspects of the simulation and the modelling are also given. The focus will lay on motor traffic and thus especially on the changes in traffic circulation as a result of relocating the car access of the City Site. The impacts of the infrastructure changes will be analysed, by simulating the current situation as well as the future situation. Comparison of the different simulations will show the impacts

Pedestrian Models for Autonomous Driving Part II: High-Level Models of Human Behavior

Abstract—Autonomous vehicles (AVs) must share space with pedestrians, both in carriageway cases such as cars at pedestrian crossings and off-carriageway cases such as delivery vehicles navigating through crowds on pedestrianized high-streets. Unlike static obstacles, pedestrians are active agents with complex, inter- active motions. Planning AV actions in the presence of pedestrians thus requires modelling of their probable future behaviour as well as detecting and tracking them. This narrative review article is Part II of a pair, together surveying the current technology stack involved in this process, organising recent research into a hierarchical taxonomy ranging from low-level image detection to high-level psychological models, from the perspective of an AV designer. This self-contained Part II covers the higher levels of this stack, consisting of models of pedestrian behaviour, from prediction of individual pedestrians’ likely destinations and paths, to game-theoretic models of interactions between pedestrians and autonomous vehicles. This survey clearly shows that, although there are good models for optimal walking behaviour, high-level psychological and social modelling of pedestrian behaviour still remains an open research question that requires many conceptual issues to be clarified. Early work has been done on descriptive and qualitative models of behaviour, but much work is still needed to translate them into quantitative algorithms for practical AV control

Space syntax and spatial cognition: or why the axial line?

200

"So go downtown": simulating pedestrian movement in town centres

Pedestrian movement models have been developed since the 1970s. A review of the literature shows that such models have been developed to explain and predict macro, meso, and micro movement patterns. However, recent developments in modelling techniques, and especially advances in agent-based simulation, open up the possibility of developing integrative and complex models which use existing models as 'building blocks'. In this paper we describe such integrative, modular approach to simulating pedestrian movement behaviour. The STREETS model, developed by using Swarm and GIS, is an agent-based model that focuses on the simulation of the behavioural aspects of pedestrian movement. The modular structure of the simulation is described in detail. This is followed by a discussion of the lessons learned from the development of STREETS, especially the advantages of adopting a modular approach and other aspects of using the agent-based paradigm for modelling

Game Theory For Self-Driving Cars

Pedestrian behaviour understanding is of utmost importance for autonomous vehicles (AVs). Pedestrian behaviour is complex and harder to model and predict than other road users such as drivers and cyclists. In this paper, we present an overview of our ongoing work on modelling AV-human interactions using game theory for autonomous vehicles control

Neuroadaptive LBS: towards human-, context-, and task-adaptive mobile geographic information displays to support spatial learning for pedestrian navigation

Well-designed, neuroadaptive mobile geographic information displays (namGIDs) could improve the lives of millions of mobile citizens of the mostly urban information society who daily need to make time critical and societally relevant decisions while navigating. What are the basic perceptual and neurocognitive processes with which individuals make movement decisions when guided by human- and context-adaptive namGIDs? How can we study this in an ecologically valid way, also outside of the highly controlled laboratory? We report first ideas and results from our unique neuroadaptive research agenda that brings us closer to answering this fundamental empirical question. We present our first implemented methodological solutions of novel ambulatory evaluation methods to study and improve Location-based System (LBS) displays, by critical examination of how perceptual, neurocognitive, psychophysiological, and display design factors might influence decision-making and spatial learning in pedestrian mobility across broad ranges of users and mobility contexts