This paper proposes a novel simultaneous transmission and reflection reconfigurable intelligent surface (STAR-RIS) aided integrated sensing and communication (ISAC) scheme for millimeter wave (mmWave) systems in high mobility scenarios. The proposed scheme aims to improve the communication service of in-vehicle user equipment (UE) and simultaneously track and sense the vehicle using nearby roadside units (RSUs). A STAR-RIS is equipped on the outside surface of the vehicle, which can reflect and refract signals to both sides, enabling full-space coverage. The transmission structure for ISAC is developed, utilizing training sequences with orthogonal precoders and combiners at the base station (BS) and RSUs for channel parameter extraction. The near-field static channel model between the STAR-RIS and UE, and the far-field time-frequency selective BS-RIS-RSUs channel model are characterized. The multidimensional orthogonal matching pursuit (MOMP) algorithm is used to extract the cascaded channel parameters of the BS-RIS-RSUs links at the RSUs, enabling vehicle localization and velocity measurement. The reflection and refraction phase shifts of the STAR-RIS are designed based on the sensing results to enhance the received signal strength. A trade-off design for sensing and communication is proposed by optimizing the energy splitting factors of the STAR-RIS. Simulation results validate the effectiveness and feasibility of the proposed scheme.This paper proposes a novel simultaneous transmission and reflection reconfigurable intelligent surface (STAR-RIS) aided integrated sensing and communication (ISAC) scheme for millimeter wave (mmWave) systems in high mobility scenarios. The proposed scheme aims to improve the communication service of in-vehicle user equipment (UE) and simultaneously track and sense the vehicle using nearby roadside units (RSUs). A STAR-RIS is equipped on the outside surface of the vehicle, which can reflect and refract signals to both sides, enabling full-space coverage. The transmission structure for ISAC is developed, utilizing training sequences with orthogonal precoders and combiners at the base station (BS) and RSUs for channel parameter extraction. The near-field static channel model between the STAR-RIS and UE, and the far-field time-frequency selective BS-RIS-RSUs channel model are characterized. The multidimensional orthogonal matching pursuit (MOMP) algorithm is used to extract the cascaded channel parameters of the BS-RIS-RSUs links at the RSUs, enabling vehicle localization and velocity measurement. The reflection and refraction phase shifts of the STAR-RIS are designed based on the sensing results to enhance the received signal strength. A trade-off design for sensing and communication is proposed by optimizing the energy splitting factors of the STAR-RIS. Simulation results validate the effectiveness and feasibility of the proposed scheme.