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【背景】随着自动驾驶技术的迭代与成熟，共享自动驾驶汽车（SharedAutonomousVehicles，SAV）未来将成为一种重要出行方式，SAV出行相较于常规公交出行更加便利和舒适，然而SAV的投放会对常规公交运营产生影响。【目标】探究SAV的车队规模、合乘策略及定价对公交的运营影响，为未来SAV 在国内的规模化营运提供具有针对性的科学依据。【方法】研究以呼和浩特市为例，整合高精度GTFS（General Transit Feed Specification）公交数据及全市居民出行链，构建基于MATSim多智能体的SAV与常规公交运营仿真模型，模拟不同SAV车队配置与常规公交的动态交互。【结果】研究结果显示：随着SAV车队规模扩大到3至4万辆，SAV分担率超过51.5%，但公交的基础需求仍保持稳定；SAV引入合乘方式后，SAV车辆行驶里相较于非合乘方式平均缩减43.00%；在合乘方式下，当公里单价维持在1.0至1.5元/km范围内，同时车队规模控制在3万辆至4万辆的区间内能将新增加车辆有效转化为“座位供给”，可以获得更高的合乘效率，缩短公交和SAV乘客等待时间，并减缓公交运行压力，与公交形成互补，同时避免了低定价和高定价带来的过度合乘及乘车抑制情况的发生。【应用】本研究结果为探索城市交通中SAV投放策略与定价机制提供理论依据。
Abstract：[Background] With the rapid diffusion of automated driving， shared autonomous vehicles (SAV) are poised to become a salient urban travel mode; however， their deployment can materially reshape the operations of conventional bus systems. [Objective] This study examines how SAV fleet size， carpooling strategy， and per-kilometer pricing affect bus operations， providing evidence to guide large-scale SAV deployment in China. [Method] Using Hohhot as a case， we integrate high-resolution GTFS (General Transit Feed Specification) data with citywide trip chains and develop a multi-agent SAV-bus interaction model in MATSim to simulate dynamic competition and complementarity under multiple “fleet & carpooling & pricing” scenarios. [Results] As the SAV fleet expands beyond 30 000 vehicles， the SAV mode share surpasses 51.5%， while the baseline bus demand remains. Enabling carpooling yields marked system-level gains: vehicle-kilometers traveled are on average 43.00% lower than in non-pooled configurations， and passenger waiting times decrease. Under moderate pricing (1.0-1.5 CNY/km) with pooling and a 30 000-40 000 vehicle fleet， additional vehicles are more effectively converted into seat supply， leading to higher pooling efficiency， shorter waits for both SAV and bus users， and reduced operational pressure on buses-indicating complementarity rather than pure substitution. Conversely， overly low or high prices risk over-carpooling or demand suppression， undermining network performance. [Application] The findings provide an empirical basis for SAV deployment scale， pooling intensity， and pricing design， supporting policy and operations that align SAV growth with robust， sustainable bus service.
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基本信息:
DOI：10.19961/j.cnki.1672-4747.2025.07.012
中图分类号:U463.6;U491.17
引用信息:
[1]郝峰,王亚宁,刘亚超,等.基于多智能体仿真的共享自动驾驶汽车对公交运营影响[J].交通运输工程与信息学报().DOI:10.19961/j.cnki.1672-4747.2025.07.012.
基金信息:
内蒙古自治区自然科学基金项目(2025MS05045); 国家自然科学基金项目(52062039)
2026-02-26
2026-02-26
2026-02-26