Abstract: With the continuous acceleration of urbanization, urban public transportation systems are facing multiple pressures, including increasing passenger flow, complex operational scheduling, and inefficient resource allocation, making traditional development models inadequate for the needs of new smart city construction. This paper, grounded in the core development trends of the automotive industry"intelligentization, connectivity, and sharing", expands on the five-dimensional synergy of "people, vehicles, roads, stations, and cloud". It closely examines key directions such as autonomous driving applications, smart service upgrades, and shared ecosystem development to explore transformation strategies for public transportation. Through case study methods, the paper integrates platform operation data and user behavior data, compares technical selections, application scenarios, and performance outcomes across different regions, and quantifies data to validate the feasibility of the "five-dimensional expansion" model. This approach promotes deep integration between the automotive industry and public transportation systems, breaking the constraints of traditional isolated operations, delayed scheduling, and supply-demand mismatches in public transportation. It drives the industry from "passively responding to demand" to "proactively optimizing services" while fostering interdisciplinary collaborative research and development, provide theoretical references for building an efficient, green, and intelligent smart bus system.

Key words: public transportation systems; intelligent connected; case study; interdisciplinary collaboration

摘要： 随着城市化进程的持续提速，城市公共交通系统正面临客流规模攀升、运营调度复杂、 资源配置低效等多重压力，传统发展模式已难以适配新型智慧城市建设需求。文章立足汽车 产业“智能化、网联化、共享化”的核心发展趋势，以“人、车、路、站、云”五维协同为 拓展，紧扣自动驾驶应用、智慧服务升级、共享生态打造等核心方向探讨了公共交通的转型 策略。通过案例研究法整合平台运营数据、用户行为数据，对比各地技术选型、应用场景、 成效表现等内容，量化数据验证“五维拓展”模式的可行性，推动汽车产业与公共交通系统 深度融合，改变传统公共交通孤立运营、调度滞后、供需错配的发展桎梏，推动行业从“被 动应对需求”向“主动优化服务”升级，同时推动跨学科的协同研究与发展，为构建高效、 绿色、智能的智慧公交系统提供理论参考。

关键词: 公共交通系统；智能网联；案例研究；跨学科协同