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The potential impacts of automated cars on urban transport: An exploratory analysis

机译:自动化汽车对城市交通的潜在影响:探索性分析

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摘要

Objective: The concept of automated cars is rapidly becoming a reality. Yet there has been very little analysis of the impacts of such developments on the performance of urban transport systems. These impacts are potentially complex. On the positive side, automation has the potential to increase road capacity, make driving available to more people, and reduce accidents and emissions. On the negative side, it could attract users away from public transport, walking and cycling, substantially increase traffic levels and stimulate urban sprawl. These impacts cannot currently be measured empirically and, by the time that they can, it will be too late to change the implementation model to rectify any resulting problems. Predictive assessments are therefore needed. This paper considers the possible impacts of automated vehicles, predicts their effects on the urban land use and transport system, and discusses the policy implications. We focus on automation of the car fleet, and do not consider the potential of automation of public transport or freight.Methods: We consider the literature on the range of attributes of automated vehicles which might affect transport and land use patterns, and suggest potential outcomes for each over the period to 2050. These include the proportion of automated vehicles in the car fleet, whether automated vehicles are privately purchased or publicly shared, the impacts on network capacity, the reduced need to pay for and walk from parking places, the potential reduction in the value of in-vehicle time and the potential use by current non-drivers. We represent these attributes in an expanded causal link diagram of the urban land use and transport system and import those causal links into the MARS system dynamics model. We determine from the literature a level for each attribute, and test the impacts in a set of ten scenarios using an updated MARS model of Leeds.Results: Based on our input assumptions, we find that car-km in 2050 could be over 50% higher than in the business as usual scenario. Public transport use could fall by 18%, threatening accessibility for those dependent on it, while walking and cycling could fall by 13%, reducing their health benefits. Overall person-km would rise, suggesting a reduction in sustainability. A requirement that all automated cars are shared vehicles could reduce these adverse impacts somewhat, but the effects are sensitive to the charge per km.Discussion: Our use of a single value for each attribute means that our analysis is exploratory, but the size of the resulting impacts demonstrates the importance of understanding the scale of systems response to each of the attributes which we have considered. It will be important to manage the way in which automated cars are introduced into urban areas, if they are not to lead to a worsening of the urban environment, accessibility and health. A requirement to make all such vehicles part of shared fleets offers one way forward, but more work is needed to understand the way in which use of such fleets should be charged.
机译:目的:自动汽车的概念迅速成为现实。然而,对城市交通系统表现的影响几乎没有分析。这些影响可能是复杂的。在积极的方面,自动化有可能提高道路容量,使驾车提供给更多的人,并减少事故和排放。在消极方面,它可以吸引用户远离公共交通,步行和骑自行车,大大增加流量水平并刺激城市蔓延。目前无法经验衡量这些影响,并且当他们可以的时间来说,改变实施模型将速度为时已晚,以纠正任何导致的问题。因此需要预测评估。本文考虑了自动车辆可能影响,预测其对城市土地利用和运输系统的影响,并讨论了政策影响。我们专注于汽车舰队的自动化,并不考虑公共交通工具或运费的自动化。方法:我们考虑了可能影响运输和土地利用模式的自动车辆属性范围的文献,并提出潜在的结果对于每次到2050年。这些包括汽车舰队中自动车辆的比例,自动车辆是否被私下购买或公开分享,对网络能力的影响,减少需要支付和从停车位散步,潜在的需求减少车载时间的值以及当前非驱动程序的潜在使用。我们在城市土地使用和运输系统的扩展因果关系中表示这些属性,并将这些因果关系导入火星系统动态模型。我们从文献中确定每个属性的一个级别,并使用更新的火星模型测试了一组十个方案的影响。结果:根据我们的输入假设,我们发现2050年的汽车KM可能超过50%比往常的情况高于业务。公共交通运输可以降低18%,威胁到它的人的威胁可达性,而行走和骑自行车可能降低13%,减少了健康益处。总体人KM将上升,表明可持续性降低。所有自动汽车都是共用车辆的要求可以减少这些不利影响,但这些效果对每公里的电荷敏感。探讨:我们对每个属性的单个值的使用意味着我们的分析是探索性的,但是产生的影响展示了了解对我们考虑的每个属性的系统响应的规模的重要性。如果他们不导致城市环境恶化,可访问性和健康,将管理自动汽车被引入城市地区的方式是很重要的。要求使所有这些车辆的共享车队的一部分提供一种前进的方式,但需要更多的工作来了解应该收取此类车队的使用方式。

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