低碳导向的多模式交通出行服务定价策略

发布时间：2024-11-26 07:49

选择公共交通工具的拼车服务，降低出行成本 #生活技巧# #节省生活成本# #低碳生活# #低碳消费策略#

低碳导向的多模式交通出行服务定价策略1. 北京交通大学交通运输学院, 北京 100044;
2. 北京交通大学综合交通运输大数据应用技术交通运输行业重点实验室, 北京 100044Low-carbon-oriented pricing strategy of multi-mode transportation serviceWANG Yue1, YAO Enjian1,2, HAO He11. School of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044, China;
2. Key Laboratory of Transport Industry of Big Data Application Technologies for Comprehensive Transport, Beijing Jiaotong University, Beijing 100044, China 摘要图/表参考文献相关文章Metrics 摘要优化出行结构、提升出行效率、降低交通碳排放是交通绿色低碳发展的重要路径。该文提出一种低碳导向的多模式交通出行服务定价调节策略,从出行服务商、出行者和环境角度出发,以服务商收益最大化,网络出行时间和交通碳排放量最小化为目标,构建多目标优化模型,在考虑出行者出行方式和路径联合选择行为的情况下对网络流量均衡分配,实现多方式协同出行和碳排放管理精细化。算例分析结果表明：服务商通过定价调节能优化网络出行结构、缓解小汽车路段拥堵状况、提高公共交通的分担率,同时实现自身盈利和交通碳排放量下降的目标。不同的优化结果表明：服务商不能仅追求自身收益最大化,还需要综合考虑出行者出行成本和出行方式对交通环境的影响,承担交通系统的协调与减排责任。该文明确了出行服务商在交通绿色低碳发展中的盈利空间和应承担的责任,为服务定价策略提供参考依据。服务把本文推荐给朋友加入引用管理器 E-mail AlertRSS收藏文章作者相关文章王月姚恩建郝赫关键词：多模式交通, 低碳出行, 出行即服务, 定价策略, 网络平衡 Abstract：[Objective] Optimising travel structure, improving travel efficiency, and reducing transport carbon emissions are essential paths to green and low-carbon transport development. Research into fine-grained carbon management has received much attention in recent years. However, the implementation is complex, and setting a price on carbon estimation tends to elicit negative feelings from travellers. [Methods] In the concept of mobility as a service (MaaS), the service can provide an end-to-end travel service by the combination of multi-transport modes, including roads and public transport, as well as many new forms of transportation. Thus, the service provider can realise flexible price adjustments for multi-transport modes and sections in a single trip. Consequently, this paper proposes a low-carbon-oriented pricing strategy for the service provider. From the different perspectives of the MaaS servicer, travellers and the environment, we propose a multi-objective optimisation model. The object includes maximising service providers' revenue and minimising network travel time and transportation network carbon emissions. The model is a two-layer planning model. The upper layer of the model is the process of finding decision variables to calculate the objective function. The lower layer is the joint traffic mode and route choice process, as well as traffic equilibrium allocation in a multi-modal transportation network. In this model, the joint choice of mode and route of travellers depends on the upper-layer decision variables. Then, to solve the above optimisation problem, the reference point based non-dominated sorting genetic algorithm (NSGA-Ⅲ) and the method of successive algorithm (MSA) are introduced. [Results] The case study was conducted on an example network with 1 origin-destination pair, 16 sections in 3 traffic modes (travel by car, bus, and metro), and 6 nodes. Three representative strategies of Pareto solutions were selected, including optimise service provider benefits (OP-S), optimise network travel time (OP-T), and optimise transportation carbon emissions (OP-C). Furthermore, the original (OR) state was also presented as the background. The result showed that the travel price significantly increased in OP-S, which was unfriendly to travellers. In contrast, OP-T and OP-C were respectively metro-friendly and public transport-friendly strategies. Compared with the OR state, service benefits and carbon emissions were optimised, which means that the service provider could achieve emission reductions in multi-modal transport networks while ensuring their own profitability through rationalised regulation of service pricing. The traffic volume analysis also proved that the service provider could optimise the network travel mode structure, thereby reducing road congestion and increasing the share of public transport. By comparing the results of the optimisation strategies under different demands, we found that with the travel demand increased, the service provider benefits continued to grow (especially in OP-S). Although traffic carbon emissions increased, the optimisations could always reduce the traffic carbon emissions of the system. [Conclusions] This paper validates the feasibility of travel service pricing strategies in multi-modal network traffic optimisation and low-carbon transport development. Service providers should not only seek to maximise their own revenue but also take into account the cost of travel and its impact on the transport environment and take responsibility for the coordination and reduction of transport system emissions. This paper identifies the profitability and responsibilities of travel service providers in the green and low-carbon development of transport and provides a basis for service pricing strategies.Key words：multi-modal transport low-carbon travel mobility as a service pricing strategies network balance收稿日期: 2022-12-27 出版日期: 2023-10-16基金资助:国家自然科学基金面上项目(52172312)通讯作者:姚恩建,教授,E-mail:enjyao@bjtu.edu.cn E-mail: enjyao@bjtu.edu.cn

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