Investigating the effects of car-following strategies of connected and automated vehicle on traffic efficiency and safety - Lai, Alson Zhi Jie (Nanyang Technological University, 2021)
The introduction of Connected and Autonomous Vehicles (CAV) for real-world applications has many possible implications for road use. CAV can be implemented with a wide variety of car-following model and strategies to optimize road use in a heterogenous traffic condition. In this report, the effects of CAV with CTH strategy and IVTH strategy on traffic efficiency and safety are investigated to determine the optimum car-following strategy in each traffic scenario. A highway and a signalized traffic intersection will be simulated for each car model based on real roads in Singapore to represent a typical road network in Singapore. Related data on traffic efficiency, the number of potential conflict and traffic throughput will be collected for every simulation starting from 10% penetration rate of CAV to 100% penetration rate for each car-following strategy. For the simulated highway, a low, medium, and high traffic density is simulated, whereas, for the simulated signalized traffic intersection, a high traffic density is considered. Each simulation will be repeated three times to obtain the average values of each data. The results show that increasing the penetration rate of CAV with the IVTH strategy improves traffic efficiency and road safety for all traffic density. In comparison with the CTH strategy, traffic efficiency and safety worsen for most traffic density. As for the signalized traffic intersection, IVTH strategy shows a more significant improvement of traffic throughput and the number of potential conflicts compared to the CTH strategy. The results conclude that the IVTH strategy provides better performance in terms of traffic efficiency and road safety level in comparison to the CTH strategy. These results can guide the auto manufactures and Singapore government to better use CAV technology.