Costs associated with traffic externalities such as congestion, air pollution, noise, safety, etcetera are becoming unbearable. The Braess paradox shows that combating congestion by adding infrastructure may not improve traffic conditions, and geographical and/or financial constraints may not allow infrastructure expansion. Road pricing presents an alternative to combat traffic externalities. T...

OBJECTIVE To determine whether the road safety policies introduced between 2000 and 2010 in Catalonia, Spain, which aimed primarily to reduce deaths from road traffic collisions by 50% by 2010, were associated with economic benefits to society. METHODS A cost analysis was performed from a societal perspective with a 10-year time horizon. It considered the costs of: hospital admissions; ambula...

OBJECTIVE To assess the availability and coverage of publicly available road safety data at the national and state levels in India. METHODS We reviewed the 2 publicly accessible data sources in India for the availability of data related to traffic injuries and deaths: (1) the National Crime Records Bureau (NCRB) and (2) the Ministry of Road Transport and Highways (MORTH). Using the World Heal...

Abstract With the emerge of intelligent and connected transportation systems, driver perception on-board safety systems could be extended with roadside camera units. Computer vision can utilised to detect road users, conveying their presence vehicles that cannot perceive them. However, accurate object detection algorithms are typically computationally heavy, depending on delay-prone cloud compu...

A well-developed road network allows all forest activities, including wood harvesting, firefighting and recreational activities. However, forest road construction and maintenance involve economic and environmental costs. For these reasons, forest road network planning is a fundamental phase of forest management, maximising the benefits and reducing costs and impacts. Thanks to modern technologi...

Data that describes the driving of vehicles in road networks, notably GPS data, is becoming increasingly available. Large volumes of such data allow us to better capture and understand the dynamic and uncertain traffic patterns that occur in road networks. Based on the availability of large volumes of GPS data, the dissertation proposes techniques that enable the efficient and accurate modeling...