No abstract

The introduction of shared autonomous vehicles into the transport system is suggested to bring significant impacts on traffic conditions, road safety and emissions, as well as overall reshaping travel behaviour. Compared with a private autonomous vehicle, a shared automated vehicle (SAV) is associated with different willingness-to-adopt and willingness-to-pay characteristics. An important aspect of future SAV adoption is the presence of other passengers in the SAV—often people unknown to the cotravellers. This study presents a cross-country exploration of user preferences and WTP calculations regarding mode choice between a private non-autonomous vehicle, and private and shared autonomous vehicles. To explore user preferences, the study launched a survey in seven European countries, including a stated-preference experiment of user choices. To model and quantify the effect of travel mode attributes and socio-demographic characteristics, the study employs a mixed logit model. The model results were the basis for calculating willingness-to-pay values for all countries and travel modes, and provide insight into the significant heterogeneous, gender-wise effect of cotravellers in the choice to use an SAV. The study results highlight the importance of analysis of the effect of SAV attributes and shared-ride conditions on the future acceptance and adoption rates of such services.

Under many circumstances, when providing full bus priority methods, urban transport officials have to operate buses in mixed traffic based on their road network limitations. In the case of Istanbul's Metrobus lane, for instance, when the route comes to the pre-designed Bosphorus Bridge, it has no choice but to merge with highway mixed traffic until it gets to the other side. Much has been written on the relative success of implementing Ramp Metering (RM), for example ALINEA (‘Asservissement line´ aire d’entre´ e autoroutie’) and Variable Speed Limits (VSL), two of the most widely-used “merging congestion” management strategies, in both a separate and combined manner. However, there has been no detailed study regarding the combination of these systems in the face of high bus volume. This being the case, the ultimate goal of this study is to bridge this gap by developing and proposing a combination of VSL and RM strategies in the presence of high bus volume (VSL+ALINEA/B). The proposed model has been coded using microscopic simulation software—VISSIM—and its vehicle actuated programming (VAP) feature; referred to as VisVAP. For current traffic conditions, the proposed model is able to improve total travel time by 9.0%, lower the number of average delays of mixed traffic and buses by 29.1% and 81.5% respectively, increase average speed by 12.7%, boost bottleneck throughout by 2.8%, and lower fuel consumption, Carbon Monoxide (CO), Nitrogen Oxides (NOx), and Volatile Organic Compounds (VOC) emissions by 17.3% compared to the existing “VSL+ALINEA” model. The results of the scenario analysis confirmed that the proposed model is not only able to decrease delay times on the Metrobus system but is also able to improve the adverse effects of high bus volume when subject to adjacent mixed traffic flow along highway sections.