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One method to reduce CO2 emissions from vehicle exhaust is the use of liquified petroleum gas (LPG) fuel. The global use of this fuel is high in European countries such as Poland, Romania, and Italy. There are a small number of computational models for the purpose of estimating the emissions of LPG vehicles. This work is one of the first to present a methodology for developing microscale CO2 emission models for LPG vehicles. The developed model is based on data from road tests using the portable emission measurement system (PEMS) and on-board diagnostic (OBDII) interface. This model was created from a previous exploratory data analysis while using gradient-boosting machine learning methods. Vehicle velocity and engine RPM were chosen as the explanatory variables for CO2 prediction. The validation of the model indicates its good precision, while its use is possible for the analysis of continuous CO2 emissions and the creation of emission maps for environmental analyses in urban areas. The validation coefficients for the selected gradient-boosting method of modelling CO2 emissions for an LPG vehicle are the R2 test of 0.61 and the MSE test of 0.77. [ABSTRACT FROM AUTHOR]

Short-term, automated car rental services, i.e., car sharing, are a solution that has been improving in urban transportation systems over the past few years. Due to the intensive expansion of the systems, service providers face increasing challenges in their competitiveness. One of them is to meet the customer expectations for the fleet of vehicles offered in the system. Although this aspect is noted primarily in the literature review on fleet optimization and management, there is a gap in research on the appropriate selection of vehicle models. In response, the article aimed to identify the vehicles best suited for car-sharing systems from the customer's point of view. The selection of suitable vehicles was treated as a multi-criteria decision-making issue; therefore, the study used ELECTRE III—one of the multi-criteria decision-making methods. The work focuses on researching the opinions of users who rarely use car-sharing services in Poland. The most popular car models in 2021, equipped with internal combustion, hybrid, and electric engines, were selected for the analysis. The results indicate that the best suited cars are relatively large, spacious, and equipped with electric drive and represent the D segment of vehicles in Europe. In addition, these vehicles are to be equipped with a powerful engine, a spacious boot, and a fast battery charging time. Interestingly, small city cars, so far associated with car sharing, ranked the worst in the classification method. In addition, factors such as the warranty period associated with the quality of the vehicles, or the number of car doors, are not very important to users. The results support car-sharing operators in the process of selecting or modernizing a fleet of vehicles. [ABSTRACT FROM AUTHOR]

Short-term car rental services, i.e., carsharing, is a solution that has been developing better and better in urban transport systems in recent years. Along with intensive expansion, service providers have to face an increasing number of challenges to compete with each other. One of them is meeting the expectations of customers about the fleet of vehicles offered in the system. While this aspect is noticed in the literature review mainly in terms of fleet optimization and management, there is a research gap regarding the appropriate selection of vehicle models. In response, the article was dedicated to identifying the vehicles that were best suited to carsharing systems from the point of view of frequent customers. The selection of appropriate vehicles was treated as a multi-criteria decision issue, therefore the study used one of the multi-criteria decision support methods—ELECTRE III. The work focuses on researching the opinions of users (experts) who often use carsharing services in Poland. The study included a list of the most popular vehicles in Europe in 2021, including classic, electric, and hybrid cars, and a list of 11 evaluation criteria. The research results indicate for frequent users the advantage of conventional drive vehicles over electric and hydrogen vehicles. Moreover, they indicate that the best vehicles are relatively large cars (European car segments C and D) with the greatest possible length, boot capacity, engine power, number of safety systems, and quality. On the other hand, the least important issues are the number of seats in the vehicle and the number of doors. Interestingly, the vehicles selected by frequent users questioned the concept of small city cars, which occupied a small public space on which carsharing was supposed to focus. The results obtained support the operators of carsharing services in making fleet decisions. [ABSTRACT FROM AUTHOR]

Increasing the market share of low-emission vehicles in relation to individual mobility is one of the main postulates of modern transport policy. In the discussion on low-emission and the new structure of the car fleet, the role of new vehicles is emphasized above all, ignoring the importance of the secondary market. In recent years, both in Poland and in other European Union countries, there has been a noticeable dynamic development of electromobility implementation processes in urban areas, the initial effect of which is increasing market accessibility to commercial vehicles with electric EV/BEV, hybrid HEV/PHEV and fuel cell powered FCEV. As in the case of vehicles powered by conventional ICEV fuels, also in relation to those defined as low-emission, their residual value is lost along with the operational process. Information on this variable is important both for the owner of a newly purchased vehicle, which after the period of its operation will decide to sell it as well as to the future buyer. The scientific aim of the study is to analyze the residual values of selected vehicle models from the primary and secondary market, with particular emphasis on stochastic operational phenomena. The subject of the research is to obtain extensive knowledge on the achieved changes in the residual values of low-emission vehicles in relation to ICEVs. For this purpose, a comparative analysis of the commercial program, data approximated from auction portals and own numerical modeling tool based on a neural network was performed. The research sample included, among others, selected models of passenger cars, the purchase offer of which included the choice of a drive unit powered by conventional and low-emission fuels. The use of this method allowed to answer the question whether low-emission vehicles are characterized by a greater or lesser loss of value in relation to conventionally powered vehicles ICEV. [ABSTRACT FROM AUTHOR]