Abstract: The development of autonomous driving technology has potentials to alleviate urban traffic congestion. However, its induced surge in travel demand may exacerbate the bottleneck of per-vehicle transport efficiency. Modular bus breaks through per-vehicle capacity limitations via dynamic fleet reconfiguration, forming collaborative capacity synergy with autonomous private cars to address supply-demand imbalance during morning commute peak. This paper develops a bi-mode bottleneck model integrating modular buses and private cars in autonomous driving context, derives equilibrium solutions under bus supply constraints, and investigates supply strategies targeting both travel cost minimization and operator revenue maximization. Results indicate that: increasing initial supply or supply rate can partially alleviate demand-supply imbalances when modular buses are undersupplied, the total travel cost will still rise. There exist two thresholds of supply rate that nullify the marginal contributions of initial and final supply, and the key to revenue optimization lies in dynamically coordinating the combination of initial and final supply. Initial supply and supply rate directly influence queue lengths during mode-switching phases, thereby affecting queuing costs and home waiting time for private car commuters. Increasing initial supply under high supply rate effectively reduces commuting delays. This paper integrates modular bus supply constraints into bi-mode traffic equilibrium framework, proposing synergistic supply strategies that establish theoretical foundations for morning-peak congestion mitigation and dynamic fleet optimization in single-bottleneck scenarios.

Key words: intelligent transportation, bi-mode equilibrium, bottleneck model, autonomous modular bus, supply constraints

摘要： 自动驾驶技术的快速发展有助于缓解城市交通拥堵，但其引发的出行需求激增可能加剧单车运输的供需失衡问题。模块化公交通过动态编组突破单车运力限制，与自动驾驶私家车形成运力协同，为破解早高峰通勤供需失衡提供新路径。本文构建自动驾驶环境下模块化公交与私家车共存的双模式瓶颈模型，推导公交供应限制下早高峰通勤均衡解，并探究以最小化出行成本和最大化运营商收益为目标的供应策略。研究结果表明：当模块化公交供应不足时，提高初始供应量或供应速率虽然能够满足通勤者的出行需求和缓解部分供需矛盾，但总出行成本会持续上升；存在两个供应速率的临界点，分别使初始和最终供应量的边际贡献为0，优化运营收益的关键在于动态调整初始和最终供应量的组合；初始供应量与供应速率直接影响出行模式切换时的排队长度，进而影响私家车通勤者的排队成本与居家等待时间；在高供应速率下，提升初始供应量可有效减少通勤等待时长。本文将模块化公交供应限制纳入双模式交通均衡框架，提出的协同供应策略为单瓶颈场景下缓解早高峰拥堵和优化模块化公交动态调度提供理论支撑。

关键词: 智能交通, 双模式均衡, 瓶颈模型, 自动驾驶模块化公交, 供应限制