Abstract-Autonomous vehicles present new opportunities for addressing traffic congestion through flexible traffic control schemes. This paper explores the possibility that auctions could be run at each intersection to determine the order in which drivers perform conflicting movements. While such a scheme would be infeasible for human drivers, autonomous vehicles are capable of quickly and seamlessly bidding on behalf of human passengers. Specifically, this paper investigates applying autonomous vehicle auctions at traditional intersections using stop signs and traffic signals, as well as to autonomous reservation protocols. This paper also addresses the issue of fairness by having a benevolent system agent bid to maintain a reasonable travel time for drivers with low budgets. An implementation of the mechanism in a microscopic simulator is presented, and experiments on city-scale maps are performed.

Abstract-Autonomous vehicles have seen great advancements in recent years, and such vehicles are now closer than ever to being commercially available. The advent of driverless cars provides opportunities for optimizing traffic in ways not possible before. This paper introduces an open source multiagent microscopic traffic simulator called AORTA, which stands for Approximately Orchestrated Routing and Transportation Analyzer, designed for optimizing autonomous traffic at a city-wide scale. AORTA creates scale simulations of the real world by generating maps using publicly available road data from OpenStreetMap (OSM). This allows simulations to be set up through AORTA for a desired region anywhere in the world in a matter of minutes. AORTA allows for traffic optimization by creating intelligent behaviors for individual driver agents and intersection policies to be followed by these agents. These behaviors and policies define how agents interact with one another, control when they cross intersections, and route agents to their destination. This paper demonstrates a simple application using AORTA through an experiment testing intersection policies at a city-wide scale.

Origin-destination (OD) data is a vital source of information on travel patterns but its utility is limited by reliance on zone centroids. This paper presents a reproducible and open two-stage ‘jittering’ approach to tackling this problem, which (1) uses random points to represent unique start and end points (sampling), and (2) splits OD pairs representing many trips into many ‘sub-OD’ pairs. We find that route networks generated from jittered OD data are more diffuse and potentially realistic based on an example from Edinburgh. Further work is needed to validate the approach and to find optimal parameters for sampling and disaggregation.

The location of new housing developments, and the provision of safe space for walking and cycling to key destinations around them, have major and long lasting impacts on travel behaviour, health, and environmental outcomes. Transit Oriented Development (TOD) is a well-recognised concept in urban planning, but systemic evidence is often lacking on the likely ‘active travel performance’ of new developments, making it hard for the planning process to support sustainable transport objectives. This paper articulates the concept of‘Active Travel Oriented Development’ (ATOD) and describes methods for operationalising it. We demonstrate the use of a set of simple metrics to assess the active travel performance of new and proposed development sites. ATOD has the benefits of building on the established concept of TOD and being easy to assess. We conclude that ATOD, and tools for measuring it, are needed to ensure that transport and development policies work in harmony.

Zones are the building blocks of urban analysis. Fields ranging from demographics to transport planning routinely use zones - spatially contiguous areal units that break-up continuous space into discrete chunks - as the foundation for diverse analysis techniques. Key methods such as origin-destination analysis and choropleth mapping rely on zones with appropriate sizes, shapes and coverage. However, existing zoning systems are sub-optimal in many urban analysis contexts, for three main reasons: 1) administrative zoning systems are often based on somewhat arbitrary factors; 2) zoning systems that are evidence-based (e.g., based on equal population size) are often highly variable in size and shape, reducing their utility for inter-city comparison; and 3) official zoning systems in many places simply do not exist or are unavailable. We set out to develop a flexible, open and scalable solution to these problems. The result is the zonebuilder project (with R, Rust and Python implementations), which was used to create the ClockBoard zoning system. ClockBoard consists of 12 segments emanating from a central place and divided by concentric rings with radii that increase in line with the triangular number sequence (1, 3, 6 km etc). 'ClockBoards' thus create a consistent visual frame of reference for monocentric cities that is reminiscent of clocks and a dartboard. This paper outlines the design and potential uses of the ClockBoard zoning system in the historical context, and discusses future avenues for research into the design and assessment of zoning systems.