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Developing Ridesharing, but for Which Trip Category? A Comparative Analysis for the Paris Region

机译:正在开发拼车游戏,但针对哪个旅行类别?巴黎地区的比较分析

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While ridesharing is expected to grow rapidly, a major policy issue is to know which trips should be targeted first, e.g., long trips or frequent yet often shorter trips. This paper develops an algorithm to investigate various ridesharing adoption patterns based on distinct trip characteristics, in order to evaluate which leads to the greatest improvement regarding traffic conditions and the environment. The trip characteristics considered are distance, travel time, and trip frequency. This leads to three ridesharing scenarios, which are then evaluated using a traffic assignment model. The methodology is applied to a Paris region case study. We find that ridesharing growth scenarios based on trip frequency contribute more to the mitigation of traffic congestion and CO_2 emissions than scenarios based on trip distance and on travel time. Some policy recommendations about this effective factor for ridesharing are discussed.
机译:共享乘车预计将迅速增长,但主要的政策问题是要确定哪些旅行应首先针对,例如长途旅行或频繁但经常为短途旅行。本文开发了一种算法,可根据不同的出行特征调查各种乘车方式,以进行评估,从而最大程度地改善交通状况和环境。考虑的行程特性是距离,行程时间和行程频率。这导致了三种共乘场景,然后使用交通分配模型对其进行评估。该方法适用于巴黎地区的案例研究。我们发现,与基于出行距离和出行时间的方案相比,基于出行频率的共乘增长方案对缓解交通拥堵和减少CO_2排放的贡献更大。讨论了有关此有效乘车因素的政策建议。

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