This paper presents an eco-driving trajectory planning approach for a platoon of heterogeneous electric vehicles (EVs) operating in urban environments. The proposed control strategy considers energy consumption, mobility, and passenger comfort while enabling vehicles to pass signalized intersections without stops. The leader vehicle plans its trajectory using dynamic programming (DP), optimizing energy consumption and other factors. Following CAVs either use cooperative adaptive cruise control or plan their own trajectories based on intersection conditions. Simulation results demonstrate reduced energy consumption without compromising mobility. This research contributes to the development of eco-driving and platooning techniques for EVs in urban areas, offering potential benefits for traffic efficiency and environmental sustainability.
There is a way to plan the driving path for a group of different electric cars in cities. This plan helps save energy, makes sure everyone can move easily, and keeps passengers comfortable. The first car in the group plans its path using special calculations. The other cars follow it or make their own plans based on the traffic lights. When tested on a computer, this plan saved energy without making it harder to move around. This new technique can help make city driving better for the environment and traffic."
Definitions
- Eco-driving trajectory planning approach: A method of planning how electric cars drive in cities that saves energy.
- Platoon: A group of vehicles driving close together.
- Heterogeneous EVs: Different types of electric cars.
- Control strategy: A plan for how to drive that considers things like energy use, mobility (how easy it is to move), and passenger comfort.
- Signalized intersections: Places where there are traffic lights.
- Dynamic programming (DP): A way of calculating the best path to take when driving.
- Cooperative adaptive cruise control (CAVs): A system that helps cars drive safely together by communicating with each other.
- Simulation results: Tests done on a computer to see if something works well before trying it in real life.
- Traffic efficiency: How well traffic flows and moves smoothly.
- Environmental sustainability: Taking care of the environment so it stays healthy for a long time.
Eco-Driving Trajectory Planning for Platoon of Electric Vehicles
The development of electric vehicles (EVs) has been gaining traction in recent years, with the potential to reduce emissions and improve traffic efficiency. However, one challenge that remains is how to optimize energy consumption while maintaining mobility and passenger comfort. A research paper recently published by researchers at Tsinghua University presents an eco-driving trajectory planning approach for a platoon of heterogeneous EVs operating in urban environments.
Dynamic Programming Approach
The proposed control strategy considers energy consumption, mobility, and passenger comfort while enabling vehicles to pass signalized intersections without stops. The leader vehicle plans its trajectory using dynamic programming (DP), optimizing energy consumption and other factors. DP is a method used to solve complex optimization problems by breaking them down into smaller subproblems that can be solved independently. In this case, the leader vehicle uses DP to plan its trajectory based on intersection conditions such as speed limits and traffic signals.
Cooperative Adaptive Cruise Control
Following CAVs either use cooperative adaptive cruise control or plan their own trajectories based on intersection conditions. Cooperative adaptive cruise control (CACC) is a type of automated driving technology that enables vehicles to maintain a safe distance from each other while traveling at the same speed through an area with multiple intersections or turns. This allows the EVs in the platoon to travel together more efficiently than if they were manually driven, reducing fuel consumption and improving safety by eliminating human error from the equation.
Simulation Results
Simulation results demonstrate reduced energy consumption without compromising mobility or passenger comfort when compared with traditional methods of driving through intersections without stops. This research contributes to the development of eco-driving and platooning techniques for EVs in urban areas, offering potential benefits for traffic efficiency and environmental sustainability.
Conclusion
Overall, this research provides insight into how eco-driving trajectory planning can be used effectively for platoons of heterogeneous EVs operating in urban environments. By utilizing dynamic programming algorithms and cooperative adaptive cruise control technologies, these vehicles are able to reduce fuel consumption while still providing passengers with comfortable rides through signalized intersections without stops – all while helping contribute towards improved traffic efficiency and environmental sustainability overall!
Given the increasing popularity and demand for connected and autonomous vehicles (CAVs), Eco-driving and platooning in highways and urban areas to increase the efficiency of the traffic system is becoming a possibility. This paper presents Eco-driving trajectory planning for a platoon of heterogeneous electric vehicles (EVs) in urban environments. The proposed control strategy for the platoon considers energy consumption, mobility and passenger comfort, with which vehicles may pass signalized intersections with no stops. For a given urban route, first, the platoon's leader vehicle employs dynamic programming (DP) to plan a trajectory for the anticipated path with the aim of balancing energy consumption, mobility and passenger comfort. Then, every other following CAV in the platoon either follows its preceding vehicle using a PID-based cooperative adaptive cruise control or plans its own trajectory by checking whether it can pass the next intersection without stopping. Furthermore, a heavy-duty vehicle that cannot efficiently follow a light-weight vehicle would instead employ the DP-based trajectory planner. Simulation studies demonstrate the efficacy of the proposed control strategy with which the platoon's energy consumption is shown to reduce while the mobility is not compromised.
