ABSTRACT

Positive impacts of car-sharing, such as reductions in car ownership, congestion, vehicle-miles-traveled and greenhouse gas emissions, have been extensively analyzed. However, these benefits are not fully effective if car-sharing subtracts travel demand from existing sustainable modes. This paper evaluates substitution rates of car-sharing against private cars and public transport using a Random Forest classifier and Binomial Logit model. The models were calibrated and validated using a stated-preference travel survey and applied to a revealed-preference survey, both administered to a representative sample of the population living in Turin (Italy). Results of the two models show that the predictive power of both models is comparable, albeit the Logit model tends to estimate predictions with a higher reliability and the Random Forest model produces higher positive switches towards car-sharing. However, results from both models suggest that the substitution rate of private cars is, on average, almost five times that of public transport.

摘要

广泛分析了汽车共享的积极影响，如减少汽车拥有量，交通拥堵，行驶里程和温室气体排放。但是，如果汽车共享从现有的可持续发展模式中减去出行需求，则这些好处并不完全有效。本文使用随机森林分类器和二项式Logit模型评估了私家车和公共交通工具对汽车共享的替代率。使用陈述偏好旅行调查表对模型进行校准和验证，然后将其应用于显性偏好调查表，二者均适用于都灵（意大利）人口的代表性样本。两种模型的结果表明，两种模型的预测能力是可比的，尽管Logit模型倾向于以更高的可靠性来估计预测，而Random Forest模型对共享汽车产生了更高的积极转变。但是，两种模型的结果都表明，私家车的替代率平均约为公共交通的五倍。