This article examines the urban layout and development of the ancient city of Angamuco (AD 250–1530)—a populated urban center located within the core area of the Purépecha Empire in Michoacán, Mexico—through the lens of its complex road network. Image and network analysis of lidar datasets revealed more than 3,000 roads distributed throughout the site, identified the main patterns of road arrangement, and documented variable accessibility within the city. After presenting a summary of these results, I propose that road networks are fundamental components of urban centers that can help reveal social configurations, local interactions, and models of governance. The study of the road network at the site of Angamuco suggests that this city developed organically without the strong influence of political hierarchy a few centuries prior to the formation of the Purépecha Empire. Angamuco inhabitants organized and negotiated space and settlement within their immediate community and had access to virtually all areas of the city.

The large-scale provision of defenses around small towns in Roman Britain during the 2nd c. CE is without parallel in the Roman Empire. Although the relationship between defended small towns and the Roman road network has been noted previously, provincial-level patterns remain to be explored. Using network analysis and spatial inference methods, this paper shows that defended small towns in the 2nd c. are on average better integrated within the road network – and located on road segments important for controlling the flow of information – than small towns at random. This research suggests that the fortification of small towns in the 2nd c. was structured by the connectivity of the Roman road network and associated with the functioning of the cursus publicus.

City road networks have been extensively studied for their social significance or to quantify their connections and centralities, but often their geographical origin is forgotten. This work focuses on the spatial-geographical and geometrical aspects of the road network skeleton. Following previous work, a multi-scale object, the way, is constructed, based only on the local geometry at road crossings. The best method to reconstruct significant elements is investigated. The results show that this object is geographically meaningful, with many particular characteristics. A new indicator, structurality, is introduced and compared with previous indicators, on the cities of Paris and Avignon. Structurality appears to be stable over the borders of the map sample, and is able to reveal the underlying coherence of the road network. This stability can be interpreted as coming from the particular way the network developed in time, and was later preserved. This link with the historical development of the cites, which deserves to be further studied, is exemplified in the cases of Villers-sur-Mer (France) and Manaus (Brazil). The construction method, the results, and their potential meaning are discussed in detail so that they can be used in various related disciplines, such as sociology, town planning, geomatics, and physics.

Accurate vehicle location is essential for various applications in the field of intelligent transportation systems (ITS). Existing vehicle location systems rely on multiple positioning sensors and powerful computing devices to execute complex map matching algorithms. There exists a strong need for exploring a solution for vehicle location that relies on a GPS receiver as the sole means of positioning and does not require complex computations. Towards this end, the error characteristics of the GPS signal were studied through the analysis of GPS data collected during test drives. Based on the inferences drawn and a simple fuzzy rule set, a novel yet simple map matching algorithm was developed. Due to the difficulties in testing the algorithm through on-road trials, a simulation environment that is capable of reproducing the field conditions in the laboratory was developed. Simulation results confirm that the proposed algorithm overcomes many of the inadequacies of the existing methods and is capable of achieving high accuracy with minimal computational requirements.