Panos D Prevedouros
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Prevedouros (now retired) has expertise in urban road network management, traffic safety, traffic flow analysis, traffic signal optimization, intelligent transportation systems and autonomous vehicles. demand forecasting and evaluation of transportation alternatives, sustainable infrastructure including transportation, energy, policies, and regulation. His current research is on the safety needs of rural and indigenous people and on the sustainability and resilience of developing countries.
Hybrid Cars Do Well in Assessments of the Environmental Impact of Urban Vehicles
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Joins life cycle impacts and a set of quantified indicators to assess the sustainability performance of seven popular light-duty vehicles and two types of transit buses. Shows the proposed sustainability dimensions produce robust sustainability assessment for several weighting scenarios.
Develops a method that integrates indirect costs (externalities), including emissions (i.e. global and local air pollution) and time losses with direct total cost of ownership. Facilitates vehicle comparisons and supports policymaking in transportation.
Begins with the basic sciences, mathematics, and engineering mechanics, and gradually introduces new concepts concerning societal context, geometric design, human factors, traffic engineering, simulation, transport planning, and evaluation.
Reveals that vehicle costs change significantly for different geographical areas depending on vehicle taxation, and the pricing of gasoline, electric power, and pollution.
Quantifies potential conflicts between left-turning vehicles and opposing through vehicles and pedestrians. Proposes a method that models the trade-off between safety and efficiency explicitly and considers both vehicle-to-vehicle and vehicle-to-pedestrian conflicts associated with left turns.
Aims to demonstrate the sustainability framework that focuses specifically on vehicle characteristics and compares two multi-criteria decision making methods in terms of ranking sustainability performance of transportation vehicles and applicability to selected indicators.
Develops a model that integrates external costs, including emissions and time losses, with societal and consumer life cycle costs. Reveals vehicle costs change significantly for different geographical areas depending on vehicle taxation, pricing of gasoline, electric power, and pollution.