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Vehicle platooning has been proposed as one of the potential technologies for intelligent transport systems to improve transportation and energy efficiency in urban cities. Despite extensive studies conducted on the platooning of heavy-duty trucks, literature on the analysis of urban vehicle platoons has been limited. To analyse the impact of platooning in urban environments, this paper studies the influence of intervehicle distance, platoon size and vehicle speed on the drag coefficient of the vehicles in a platoon using computational fluid dynamics (CFD). Two vehicle models—a minibus and a passenger car—are analysed to characterise the drag coefficients of the respective platoons. An analysis of energy consumption is conducted to evaluate the energy savings with platooning using a longitudinal dynamics simulation. The results showed a reduction in the average drag coefficient of the platoon of up to 24% at an intervehicle distance of 1 m depending on the number of vehicles in the platoon. With a larger intervehicle distance of 4 m, the reduction in the drag coefficient decreased to 4% of the drag coefficient of the isolated vehicle. Subsequently, energy savings with platooning were calculated to be up to 10% depending on the driving cycle, intervehicle distance and platoon size.

There is rapidly growing interest in autonomous electric vehicles due to their potential in improving safety, accessibility, and environmental outcomes. However, their market penetration rate is dependent on costs. Use of autonomous electric vehicles for shared-use mobility may improve their cost competitiveness. So far, most of the research has focused on the cost impact of autonomy on taxis and ridesourcing services. Singapore is planning for island-wide deployment of autonomous vehicles for both scheduled and on-demand services as part of their transit system in the year 2030. TUMCREATE developed an autonomous electric vehicle concept, a microtransit vehicle with 30-passenger capacity, which can complement the existing bus transit system. This study aims to determine the cost of autonomous electric microtransit vehicles and compare them to those of buses. A total cost of ownership (TCO) approach was used to compare the lifecycle costs. It was shown that although the acquisition costs of autonomous electric vehicles are higher than those of their conventional counterparts, they can reduce the TCO per passenger-km up to 75% and 60% compared to their conventional counterparts and buses, respectively.

In life cycle assessment (LCA) of road transportation systems, limited attention is given to noise as an impact category. This paper presents a method in order to include the environmental effects of noise in the LCA of road transportation. Life cycle inventory is developed based on the IMAG INE road vehicle noise emission model. Life cycle impact assessment is based on cause-effect chain including fate, exposure, effect, and damage analysis. The health effects of road traffic noise are evaluated in terms of acute myocardial infarction, annoyance, and sleep disturbance. The corresponding health damages are quantified using disability adjusted life years (DALY). A case study evaluating the health effects of road transportation noise for the nine municipalities of Istanbul using the proposed method is also presented. It was shown that transportation noise has significant adverse health effects and therefore should be accounted for in the LCA of road transportation along with other environmental interventions.

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