Connected and Automated Vehicles (CAVs) Using Eco-Friendly Traffic Optimization Systems Can Reduce Fuel Consumption up to 15 Percent and Waiting Time Up to 85 Percent at Equipped Intersections.

Simulation Study Quantifies Wait Time and Environmental Benefits of Connected Vehicle Communications.

Date Posted
05/30/2023
Identifier
2023-B01748
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Eco-friendly Cooperative Traffic Optimization at Signalized Intersections

Summary Information

Implementing strategies that take advantage of connected vehicle communications can potentially improve overall efficiency of signalized intersections and reduce fuel consumption. One example is Eco-Approach and Departure (EAD) application that communicates signal phase and timing information to vehicles. This study evaluated how connected vehicle technology could reduce wait times and fuel consumption at signalized intersections by developing an Eco-friendly Cooperative Traffic Operation (ECoTOp) system for signalized intersections where equipped Connected and Automated Vehicles (CAVs) were proactively managed and traversed the intersection in coordination with traffic signal optimization to minimize energy consumption. A microscopic traffic simulation model of a signalized intersection was used to measure the impact of the proposed ECoTOp system under different CAV market penetration rates (MPR).

METHODOLOGY

The ECoTOp system co-optimizes traffic signal and vehicle dynamics to maximize the throughput from all phases in the cycle and minimize the total energy consumption of each CAV in all the time steps, considering constraints from the signal, roadway and traffic. As CAVs approached the intersection, they communicated their intentions to the traffic signal controller, which then calculated and relayed optimal signal timings. Vehicles then performed eco-driving based on this data, balancing downstream lane-specific traffic conditions and energy efficiency.

A typical four-leg signalized intersection with two through lanes and a left-turn lane for each direction was modeled in a microscopic traffic simulation software with application programming interface (API) capabilities. Four different scenarios were analyzed: (i) fixed traffic signal control, (ii) signal optimization only, (ii) EAD only and (iv) ECoTOp for different CAV penetrations. Fuel consumption, average speed, and average waiting time were used as performance measures.

FINDINGS 

The results shown below indicate the performance of ECoTOp compared to a fixed signal timing plan scenario. Table 1 shows the findings for waiting time and fuel consumption.

Table 1. ECoTOp performance comparison at different CAV penetrations

CAV MPR Reduction in Waiting Time Reduction in Fuel Consumption 
100 85.70% 15.40%
80 77.60% 11.80%
60 57.40% 8.40%
40 44.10% 4.60%

 

Overall, ECoTOp performed better than fixed traffic signal control and signal optimization scenarios at all MPRs. ECoTOp performed better than EAD only scenario when MPR was 60 percent and more, with nearly similar benefits when MPR was lower. Speed decreased in all MPRs but only up 7.6 percent.

Results Type