Impact of Automated Vehicle Eco-Approach on Human-Driven Vehicles

Lian Cui, Huifu Jiang, B. Brian Park, Young Ji Byon, Jia Hu

Research output: Contribution to journalArticlepeer-review

18 Scopus citations


In urban areas, traffic signals cause unnecessary stops and delays to vehicles resulting in excessive energy consumptions and emissions. The eco-approach technology has been introduced to achieve environment-friendly driving behaviors and to improve energy efficiencies with reduced rapid accelerations or decelerations. However, it is not clear how the behavior of drivers would change while following an eco-approaching vehicle. Especially in the mixed traffic, dynamics behind the interactions between the human-driven vehicle and connected automated vehicle (CAV) that perfectly achieves the eco-approach and the impacts on energy consumptions are not transparent. This research designs a driving simulation environment for the mixed traffic to assess the benefits of the eco-approach. In the experiments, a straight roadway with four signalized intersections equipped with communication devices is developed. An eco-guidance algorithm for human drivers and an eco-approach control algorithm of CAV with the I2-V communication system are designed and compared, where each scenario is tested 50 times with a human driver using a driving simulator. The results indicate that both the eco-guidance scenario and following CAV with the eco-approach scenario could reduce over 6% of fuel consumptions compared with the base-case scenario, which is normal-driving without guidance. This indicates the energy efficiency benefit of the eco-approach of CAVs and its impact on surrounding vehicles in the mixed traffic.

Original languageBritish English
Article number8485800
Pages (from-to)62128-62135
Number of pages8
JournalIEEE Access
StatePublished - 2018


  • connected and automated vehicle
  • eco-approach
  • human factor
  • Road transportation
  • traffic flow


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