The emergence of software-defined vehicles (SDVs), combined with autonomous driving technologies, has enabled a new era of vehicle computing (VC), where vehicles serve as a mobile computing platform. However, the interdisciplinary complexities of automotive systems and diverse technological requirements make developing applications for autonomous vehicles challenging. To simplify the development of applications running on SDVs, we propose a comprehensive suite of vehicle programming interfaces (VPIs). In this study, we rigorously explore the nuanced requirements for application development within the realm of VC, centering our analysis on the architectural intricacies of the Open Vehicular Data Analytics Platform (OpenVDAP). We then detail our creation of a comprehensive suite of standardized VPIs, spanning five critical categories: Hardware, Data, Computation, Service, and Management, to address these evolving programming requirements. To validate the design of VPIs, we conduct experiments using the indoor autonomous vehicle, Zebra, and develop the OpenVDAP prototype system. By comparing it with the industry-influential AUTOSAR interface, our VPIs demonstrate significant enhancements in programming efficiency, marking an important advancement in the field of SDV application development. We also show a case study and evaluate its performance. Our work highlights that VPIs significantly enhance the efficiency of developing applications on VC. They meet both current and future technological demands and propel the software-defined automotive industry toward a more interconnected and intelligent future.