摘要
智能手机、移动平台和在线支付系统的广泛使用为顺风车出行提供了新的机会,顺风车是一种持续的交通方式,可以充分利用交通系统中现有私家车辆的空闲承载能力。该文引入稳定性的概念来建立一个顺风车稳定匹配模型,并提出一种启发式算法来找到稳定或近似稳定的匹配方案,并进行数值模拟来证明所提出算法的计算效率,探索该方法在一定规模下的顺风车匹配的实际适用性。结果表明:(1)随着参与者数量的增加,匹配率Suc、总距离节省比率Sav和参与者个人出行距离节省比率Sipr都不断上升,且有两个交通聚集中心时,Suc,Sav和Sipr都比没有交通中心时高,而司机绕路比率Dt不断下降;(2)随着参与者时间机会成本系数的增加,匹配率Suc、总距离节省比率Sav和司机绕路比率Dt不断下降;(3)随着参与者弹性时间的增加,匹配率Suc、总距离节省比率Sav和参与者个人出行距离节省比率Sipr都上升,司机绕路比率Dt下降;(4)通过比较系统最优化模型,考虑参与者成本的系统优化模型和稳定匹配优化模型求解时间,发现所提出的偏好列表精简算法能够有效地降低求解稳定匹配解的时间。
The wide-spread use of smart phones,mobile platforms and online payment systems provides new opportunities to enable ridesharing,which is a continuous transport mode that can make full use of the free carrying capacity of existing private vehicles in the transport system.A notion of stability is introduced to build a stable ridesharing matching model.A heuristic algorithm is proposed to find a stable or approximately stable matching scheme,and numerical simulation is carried out to prove the computational efficiency of the proposed algorithm,and to explore the practical applicability of the method in a certain scale of ridesharing matching.The result shows that(1)With the increasing of number of participants,the matching rate Suc,the total distance saving rate Sav and the individual travel distance saving rate Sipr increase.When there are 2 traffic centers,Suc,Sav and Sipr are respectively higher than those when there are no traffic center,while the driver detour ratio Dt decreases.(2)With the increase of time opportunity cost coefficient of participants,Suc,Sav and Dt decrease.(3)With the increase of participants’elastic time,Suc,Sav and Sipr increase,while Dt decreases.(4)By comparing the solution time of the system optimization model,the system optimization model considering the cost of participants and the stable matching optimization model,it is found that the proposed preference list reduction algorithm can effectively reduce the solution time of stable matching.
作者
马瑞民
姚立飞
MA Rui-min;YAO Li-fei(School of Management,Guangzhou University,Guangzhou Guangdong 510006,China;School of Geography and Tourism,Guangdong University of Finance and Economics,Guangzhou Guangdong 510320,China)
出处
《公路交通科技》
CAS
CSCD
北大核心
2021年第4期131-141,共11页
Journal of Highway and Transportation Research and Development
基金
教育部人文社会科学项目(19YJC630119)。
