Abstract: To explore spatiotemporal characteristics of vehicles in a long tunnel road under the vehicle-road coopera-tive environment，the human-machine interface of tunnel warning system based on the connected vehicle technology was designed and a driving simulation experiment was carried out． 35 drivers' spatiotemporal characteristics of vehi-cle were studied by taking the group without warning system as the control group． The results reveal that when the system was on，the slowdown trigger points of vehicle was earlier，and the curvature values and number of inflection points of the spatiotemporal graph decreased． Moreover，the coefficient of variation of vehicle speed near the entrance and inside tunnel and the degree of overspeed in tunnel decreased obviously when the system was on． In conclusion，with the warning system，the driving pattern was changed from a visual stimulation-based response be-havior to a psychological expectation-based proactive behavior，which was easy to form the stable spatiotemporal characteristics． Further research shows that，assuming that the minimum headway of the following distance is 1. 5s，and based on the best converging patterns from 35 drivers' spatiotemporal trajectories，the overall traffic capacity was 21. 27% higher than that without the warning system．

Key words: traffic engineering, vehicle-road cooperation, tunnel warning system, driving simulation, spatiotemporal characteristic, traffic capacity