论文标题
自动乘坐服务的竞争与合作:基于游戏的经纪人概念的模拟
Competition and Cooperation of Autonomous Ridepooling Services: Game-Based Simulation of a Broker Concept
论文作者
论文摘要
自动移动性按需服务有可能破坏未来的移动系统景观。特别是乘车服务可以通过增加平均车辆占用率来降低土地消耗并提高运输效率。但是,由于乘车服务需要足够的用户群才能汇总才能生效,因此如果多个运营商提供这样的服务并且必须分解需求,他们的性能可能会受到影响。这项研究提出了一个模拟框架,用于评估多个乘车提供者之间竞争与合作的影响。将两种通过经纪人平台进行的两种不同类型的交互与单个垄断操作员的基本案例和两个独立运营商的基本案例进行了比较。首先,经纪人礼物从所有运营商提供给客户(类似于移动性的服务平台),他们可以自由选择操作员。在第二个中,受监管的经纪人平台可以操纵操作员提供的目的是将客户运营商的分配从用户平衡转移到系统最佳。为了模拟服务设计的采用,具体取决于不同的交互情况,引入了游戏设置。在运营商之间的交替转弯中,操作员可以调整其服务的参数(车队的大小和目标功能),以最大程度地利用利润。基于曼哈顿出租车数据的案例研究的结果表明,运营商在经营最大的车队时会在经纪人环境中获得最高的利润。此外,与单个操作员相比,几乎可以维持合并效率。随之而来的服务率提高,规范的竞争福利不仅是运营商(利润)和城市(提高集合效率),而且还包括客户。相反,当用户可以自由决定时,观察到最低的集合效率和运营商的利润。
Autonomous mobility on demand services have the potential to disrupt the future mobility system landscape. Ridepooling services in particular can decrease land consumption and increase transportation efficiency by increasing the average vehicle occupancy. Nevertheless, because ridepooling services require a sufficient user base for pooling to take effect, their performance can suffer if multiple operators offer such a service and must split the demand. This study presents a simulation framework for evaluating the impact of competition and cooperation among multiple ridepooling providers. Two different kinds of interaction via a broker platform are compared with the base cases of a single monopolistic operator and two independent operators with divided demand. In the first, the broker presents trip offers from all operators to customers (similar to a mobility-as-a-service platform), who can then freely choose an operator. In the second, a regulated broker platform can manipulate operator offers with the goal of shifting the customer-operator assignment from a user equilibrium towards a system optimum. To model adoptions of the service design depending on the different interaction scenario, a game setting is introduced. Within alternating turns between operators, operators can adapt parameters of their service (fleet size and objective function) to maximize profit. Results for a case study based on Manhattan taxi data, show that operators generate the highest profit in the broker setting while operating the largest fleet. Additionally, pooling efficiency can nearly be maintained compared to a single operator. With the resulting increased service rate, the regulated competition benefits not only operators (profit) and cities (increased pooling efficiency), but also customers. Contrarily, when users can decide freely, the lowest pooling efficiency and operator profit is observed.