• Department of Civil and Environmental Engineering The Hong Kong University of Science and Technology Hong Kong China
  • School of Intelligent Systems Engineering Sun Yat-sen University Shenzhen Guangdong China
  • 拼车服务是由交通网络公司 (TNC) 提供的新兴城市出行服务,包括非拼车服务和拼车服务。通过接收在线订单和提供高效的门到门服务,拼车服务正成为公共交通的流行替代方案。同时,不可忽视的出行时间变异性影响着乘客的出行行为和 TNC 的定价策略。为了研究旅行时间变异性的影响,本文提出了一个双层框架。交通网络中乘客的方式选择、搜索司机的区域选择以及随后的路线选择交通均衡被制定为下层。上层研究最优定价策略。在网络公式中,乘客会遇到等待时间的可变性,绕道时间和高速公路行驶时间。提出了两种定价策略来适应配对不成功的风险。定价策略 1 收取固定价格,即使拼车请求因配对不成功而变为非拼车服务;而定价策略 2 如果配对不成功,则将拼车请求的价格提高到非拼车服务的价格。结果表明,定价策略 1 产生了更多的利润并引发了更多的拼车需求。此外,在更可靠的交通条件下,寻车服务的最优价格更高,网络出行时间减少。结果说明了出行时间可变性对网约车市场的影响,并为公司在出行时间可变性下的网络定价策略提供了指导。

    Ride-sourcing services are burgeoning urban mobility services provided by transportation network companies (TNCs), consisting of non-pooling service and ride-pooling service. By receiving online orders and offering efficient door-to-door services, ride-sourcing services are becoming popular alternatives to public transit. Meanwhile, unignorable travel time variability influences passengers’ travel behavior and TNC’s pricing strategy. To investigate the effect of travel time variability, this paper proposes a bi-level framework. The mode choice of passengers, zone choice of searching drivers and the subsequent route choice traffic equilibrium in a transportation network is formulated as the lower level. And the upper level investigates the optimal pricing strategy. In the network formulation, passengers encounter variability of waiting time, detour time and highway travel time. Two pricing strategies are proposed to accommodate the risk of unsuccessful pairing. Pricing strategy 1 charges a fixed price even when a ride-pooling request becomes a non-pooling service due to unsuccessful pairing; whereas pricing strategy 2 increases the price of a ride-pooling request to that of non-pooling service if pairing is unsuccessful. The results show that pricing strategy 1 produces more profit and induces more ride-pooling demand. In addition, under more reliable traffic conditions, the optimal prices for ride-sourcing services are higher and the network travel time decreases. The results illustrate the influence of travel time variability on the ride-sourcing market and provide guidance on the company’s pricing strategy regarding a network under travel time variability.