The assigment of vehicle assesment based on multi criteria decision making

• Main Authors: Ewelina Sendek-Matysiak, Dariusz PYZA
• Format: Article
• Language: English
• Published: Faculty of Transport, Warsaw University of Technology 2018-12-01
• Series: Archives of Transport
• Subjects: electric car; automotive market; multi-criteria scoring method
• Online Access: http://aot.publisherspanel.com/gicid/01.3001.0012.8367

The degree of emission limitation achieved through improved efficiency of combustion engine vehicles can no longer set off additional emissions caused by increasing traffic activity. As the restriction of greenhouse gas emissions from cars is expected to be particularly difficult, the air pollution and excessive dependence of road transportation on oil cannot be improved without the implementation of new mobility concepts (biofuels, hybrid drives, electric vehicles). The lack of these concepts, as emphasized in the White Paper, will preserve transportation dependence on crude oil so deeply that only 10% of energy will be derived from renewable sources. According to this scenario, until 2050 the CO2 emissions in the transportation sector will increase by one-third compared to 1990. Moreover, there will be an increase in the costs of traffic congestion until 2050 by ca. 50%. The difference in the availability between central and peripheral areas and social costs of accidents and noise pollution will increase as well (EC, 2011). The goal of the paper is to determine whether the implementation of a new solution would actually improve the situation of air pollution, traffic noise, etc. To this end, the paper proposes a comparative analysis of cars with various sources of energy using a multi-criteria scoring method. Notably, this method has never been used in such a confrontation before. Until now, the multi-criteria assessment methods have been used i.a. to evaluate implementation variants for infrastructural investment projects in rail transport (Jacyna and Wasiak, 2007), traffic flow distribution (Jacyna and Merkisz, 2014; Wasiak et al., 2017), supply chain efficiency (Jacyna-Gołda et al., 2018), effectiveness of vehicle allocation for tasks in supply chains (Jacyna-Gołda et al., 2017), etc.