本文運用車用感測器模擬平台(PreScan)製作測試車用感測器之環境模擬路段。首先使用PreScan建置模擬路段或匯入真實路段，建造虛擬基礎設施、街道及場景，加入車輛及道路突發事件、交通號誌、人為因素、光源和模擬天氣變化等等，作為測試車用感測器數值的根據，透過PreScan進行測試。
建置完成後之虛擬路段場景，放置PreScan內建車輛模組，並於適當位置架設攝影鏡頭得知車輛行進時的視角，再利用SimuLink為車用感測器建模，進行車用感測器的測試。為了提高公路運輸的安全性，效率及可持續性，駕駛員支持系統和全自動智能交通系統是市場上最有前途的發展之一，與行車安全相關之技術也日益受到車廠重視。而關鍵就在於車用感測器的性能好壞與否，以往測試車用感測器大多是使用車輛真槍實彈上陣，當中的風險和成本是龐大且昂貴的，若是藉由PreScan進行測試，不只能因其經由真實測試得出的物理數據，獲得可信度高的數據，也能迴避使用實車測試車用感測器帶來的高成本高風險。 In this paper, we use vehicle sensor simulation platform (PreScan) to simulate the circumstance of driving on road to test the vehicle sensor. First, use PreScan to set up a scenario of streets and roads or to input realistic street view, to build virtual facilities, streets and scenes and add vehicles, road incidents, traffic signals, human errors, light factors and weather conditions, etc., as the base to test car sensor.
After the construction of the virtual road scene, add PreScan built-in vehicle module and set up a camera at appropriate place to get the perspective of the driver. Then use SimuLink to set model for vehicle sensors for testing. In order to improve the safety, the efficiency and the consistency of road transport, Driver Supporting System and Intelligent Transport System could be the most potential creation in the market. The technology also becomes more important to the vehicle manufacturers. The performance/function of the vehicle sensor is a key point. The test vehicle sensors in the past mostly use real vehicles for test and the risk and the cost of this kind of test is huge and expensive. But if we test it by PreScan, it can not only provide with almost real physical data to reliable information, but also can avoid the risks and the tremendous amount of cost resulted from using real vehicles for test.
