Truck Platooning Based on Lead Vehicle Speed Profile Optimization and Artificial Physics

2015 ◽  
Author(s):  
Luca Caltagirone ◽  
Sina Torabi ◽  
Mattias Wahde
Keyword(s):  
Vehicle Speed ◽  
Speed Profile ◽  
Profile Optimization ◽  
Lead Vehicle ◽  
Artificial Physics

scholarly journals Fuel-Efficient Driving Strategies for Heavy-Duty Vehicles: A Platooning Approach Based on Speed Profile Optimization

2018 ◽  
Vol 2018 ◽  
pp. 1-12 ◽  
Author(s):  
Sina Torabi ◽  
Mattias Wahde
Keyword(s):  
Speed Profile ◽  
Fuel Reduction ◽  
Heavy Duty ◽  
Cruise Control ◽  
Fuel Savings ◽  
Percentage Points ◽  
Profile Optimization ◽  
Layer Control ◽  
Lead Vehicle ◽  
Heavy Duty Vehicles

A method for reducing the fuel consumption of a platoon of heavy-duty vehicles (HDVs) is described and evaluated in simulations for homogeneous and heterogeneous platoons. The method, which is based on speed profile optimization and is referred to as P-SPO, was applied to a set of road profiles of 10 km length, resulting in fuel reduction of 15.8% for a homogeneous platoon and between 16.8% and 17.4% for heterogeneous platoons of different mass configurations, relative to the combination of standard cruise control (for the lead vehicle) and adaptive cruise control (for the follower vehicle). In a direct comparison with MPC-based approaches, it was found that P-SPO outperforms the fuel savings of such methods by around 3 percentage points for the entire platoon, in similar settings. In P-SPO, unlike most common platooning approaches, each vehicle within the platoon receives its own optimized speed profile, thus eliminating the intervehicle distance control problem. Moreover, the P-SPO approach requires only a simple vehicle controller, rather than the two-layer control architecture used in MPC-based approaches.

scholarly journals Feedforward Tactical Optimization for Energy-Efficient Operation of Freight Trains: The Swiss Case

2018 ◽  
Vol 2672 (10) ◽  
pp. 278-288 ◽  
Author(s):  
Valerio De Martinis ◽  
Ambra Toletti ◽  
Francesco Corman ◽  
Ulrich A. Weidmann ◽  
Andrew Nash
Keyword(s):  
Energy Efficiency ◽  
Energy Efficient ◽  
Real Data ◽  
Efficient Solutions ◽  
Future Market ◽  
Speed Profile ◽  
Efficient Operation ◽  
The North ◽  
Simulation Based ◽  
Profile Optimization

The optimization of rail operation for improving energy efficiency plays an important role for the current and future market of rail freight services and helps rail compete with other transport modes. This paper presents a feedforward simulation-based model that performs speed profile optimization together with minor rescheduling actions. The model’s purpose is to provide railway operators and infrastructure managers with energy-efficient solutions that are tailored especially for freight trains. This work starts from the assumption that freight train characteristics are completely defined only a few hours before actual departure; therefore, small specific feedforward adjustments that do not affect the surrounding operation can still be considered. The model was tested in a numerical example. The example clearly shows how the optimized solutions can be evaluated with reference to energy saved and robustness within the rail traffic. The evaluation is based on real data from the North–South corridor crossing Switzerland from Germany to Italy.

scholarly journals Energy-Efficient Speed Profile Optimization and Sliding Mode Speed Tracking for Metros

Energies ◽  
2020 ◽  
Vol 13 (22) ◽  
pp. 6093
Author(s):  
Xiaowen Wang ◽  
Zhuang Xiao ◽  
Mo Chen ◽  
Pengfei Sun ◽  
Qingyuan Wang ◽  
...  
Keyword(s):  
Energy Saving ◽  
Energy Efficient ◽  
Artificial Bee Colony ◽  
Sliding Mode ◽  
Speed Profile ◽  
Terminal Sliding Mode ◽  
Bee Colony ◽  
Speed Tracking ◽  
Speed Error ◽  
Profile Optimization

Nowadays, most metro vehicles are equipped with an automatic train operation (ATO) system, and the speed control method, combining cruise speed planning and proportional-integral-derivative (PID) control, is widely used. The automation is achieved, and the energy-efficient can be improved. This paper presents an improved artificial bee colony algorithm for speed profile optimization with coast mode and an adaptive terminal sliding mode method for speed tracking. Specifically, a multi-objective optimization model is established, which considers energy consumption, comfortableness, and punctuality. Then, a novel artificial bee colony algorithm named regional reinforcement artificial bee colony (RR-ABC) is designed, to search the optimal speed profile with coast mode, in which some improvements are made to speed up convergence and to avoid local optimal solutions. For speed-tracking control, the adaptive terminal sliding mode controller (ATSMC) is used to improve the speed error, robustness, and energy saving. In addition, a disturbance observer (DOB) is designed to improve the anti-interference ability of the system and further improve the robustness and anti-disturbance, which are also conducive to speed error and energy saving. Finally, the line and train data of the Qingdao Metro Line 6 are used for simulation, which proves the effectiveness of the study. Specific to the energy saving rate, and compared with normal algorithms, RR-ABC with coast mode is approximately 9.55%, and ATSMC+DOB is 7.58%.

Novel Stop Sign Detection Algorithm Based on Vehicle Speed Profile

2019 ◽  
Author(s):  
Soodeh Dadras ◽  
Homayoun Jamshidi ◽  
Sara Dadras ◽  
Thomas Edward Pilutti
Keyword(s):  
Detection Algorithm ◽  
Vehicle Speed ◽  
Speed Profile ◽  
Stop Sign ◽  
Sign Detection

Fleet Speed Profile Optimization for Autonomous and Connected Vehicles

2021 ◽  
Author(s):  
Mohammad Arifur Rahman ◽  
Md Ehsanul Haque ◽  
Yilmaz Sozer ◽  
Ali Riza Ozdemir
Keyword(s):  
Connected Vehicles ◽  
Speed Profile ◽  
Profile Optimization
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