First steps towards a holistic impact assessment methodology for connected and automated vehicles.

Connected and automated vehicles have become more common in recent years, increasing the need to assess their societal level impacts. In this paper a methodology is presented to explore and define relevant impact areas as a starting point for quantitative impact assessment. The many interrelations between impact areas increases the complexity of obtaining a complete overview.

Examining road safety impacts of Green Light Optimal Speed Advisory (GLOSA) system.

Mobility and environmental benefits of Green Light Optimal Speed Advisory (GLOSA) systems have been reported by many previous research studies, however, there is insufficient knowledge on the safety implications of such an application. For safe deployment of GLOSA system, it is most critical to identify and address potential safety issues in the design process. It can be argued that implementation of GLOSA system can improve safety by reducing traffic conflicts associated with the interrupted traffic flow at signalised intersections.

Network-wide safety impacts of dedicated lanes for connected and autonomous vehicles.

Cooperative, Connected and Automated Mobility (CCAM) enabled by Connected and Autonomous Vehicles (CAVs) has potential to change future transport systems. The findings from previous studies suggest that these technologies will improve traffic flow, reduce travel time and delays. Furthermore, these CAVs will be safer compared to existing vehicles.

A comprehensive analysis of the relationships between the built environment and traffic safety in the Dutch urban areas.

Built-environment factors potentially alleviate or aggravate traffic safety problems in urban areas. This paper aims to investigate the relationships of these factors with vehicle-bicycle and vehicle-vehicle property damage only (PDO) and killed and severe injury (KSI) crashes in urban areas. For this purpose, an area-level analysis using 100x100m cells, along with a Spatial Hurdle Negative Binomial regression model were employed.