AEB effectiveness research methods based on reconstruction results of truth vehicle-to-TW accidents in China

2020 ◽  
pp. 095440702097674
Author(s):  
Yong Peng ◽  
Weifeng Yu ◽  
Xinghua Wang ◽  
Qian Xu ◽  
Honggang Wang ◽  
...  
Keyword(s):  
Real Life ◽  
Latin Hypercube Sampling ◽  
Severe Accident ◽  
Simulation Program ◽  
Physical Parameters ◽  
Latin Hypercube ◽  
Nsga Ii ◽  
Multi Objective ◽  
Emergency Braking ◽  
Triggering Conditions

Vehicle-to-TW accidents are one of the largest components of traffic accidents system in China, which always leads to severe accident consequences because the cyclists are vulnerable road users and drive at a high collision velocity. With the development of information and communication technology, automated Emergency Braking (AEB) system has been applied to modern vehicles, which can perform emergency braking automatically in dangerous situations and mitigate the consequence of accident. The purpose of this study is to propose a method to identify the mechanism that affects the effectiveness of AEB functions under real-life vehicle-to-TW traffic accident scenarios with Chinese county characteristics. Through the analysis and reconstruction for the sampling accident case-by-case, the whole process of the accident has been reproduced. The trajectory analysis program determines the accident triggering conditions and then generates the virtual physical parameters of the triggering conditions through the virtual sample generation method based on the initial sample. In parallel, the AEB effectiveness simulation program has been established. Plug in parameters of AEB system generated by the Latin hypercube sampling to the AEB effectiveness simulation program for getting the mechanism that affect the effectiveness of AEB functions. The AEB system parameters generated by Latin hypercube sampling are inserted into the AEB effectiveness simulation program to obtain the mechanism that affects the effectiveness of the AEB function. Under the multi-objective optimization problem of accident avoidance rate, technical cost and occupant comfort, the optimal parameters and multi-objective values of AEB are obtained by the NSGA-II algorithm. These results can adapt to Chinese actual traffic conditions to a certain extent, and provide a reliable basis for the research and development of AEB system in China.

scholarly journals Multi-Objective Reentrant Hybrid Flowshop Scheduling with Machines Turning on and off Control Strategy Using Improved Multi-Verse Optimizer Algorithm

2019 ◽  
Vol 2019 ◽  
pp. 1-18 ◽  
Author(s):  
Kaifeng Geng ◽  
Chunming Ye ◽  
Lei Cao ◽  
Li Liu
Keyword(s):  
Energy Consumption ◽  
Control Strategy ◽  
Latin Hypercube Sampling ◽  
Industrial Applications ◽  
Flowshop Scheduling ◽  
Start Time ◽  
Nsga Ii ◽  
Hybrid Flowshop ◽  
Multi Objective ◽  
Hybrid Flowshop Scheduling

This paper focuses on the multi-objective optimization of the reentrant hybrid flowshop scheduling problem (RHFSP) with machines turning on and off control strategy. RHFSP exhibits significance in many industrial applications, but scheduling with both energy consumption consideration and reentrant concept is relatively unexplored at present. In this study, an improved Multi-Objective Multi-Verse Optimizer (IMOMVO) algorithm is proposed to optimize the RHFSP with objectives of makespan, maximum tardiness, and idle energy consumption. To solve the proposed model more effectively, a series of improved operations are carried out, including population initialization based on Latin hypercube sampling (LHS), individual position updating based on Lévy flight, and chaotic local search based on logical self-mapping. In addition, a right-shift procedure is used to adjust the start time of operations aiming to minimize the idle energy consumption without changing the makespan. Then, Taguchi method is utilized to study the influence of different parameter settings on the scheduling results of the IMOMVO algorithm. Finally, the performance of the proposed IMOMVO algorithm is evaluated by comparing it with MOMVO, MOPSO, MOALO, and NSGA-II on the same benchmark set. The results show that IMOMVO algorithm can solve the RHFSP with machines turning on and off control strategy effectively, and in terms of convergence and diversity of non-dominated solutions, IMOMVO is obviously superior to other algorithms. However, the distribution level of the five algorithms has little difference. Meanwhile, by turning on and off the machine properly, the useless energy consumption in the production process can be reduced effectively.

Multi-objective optimization of customized bus routes based on full operation process

2020 ◽  
Vol 34 (25) ◽  
pp. 2050266
Author(s):  
Chao Wang ◽  
Changxi Ma
Keyword(s):  
Real Life ◽  
Route Optimization ◽  
Operating Efficiency ◽  
Multi Objective Optimization ◽  
Nsga Ii ◽  
Parking Lots ◽  
Multi Objective ◽  
Hybrid Coding ◽  
Mutation Operators ◽  
Operation Process

In order to rationally formulate a customized bus route plan to improve the operation efficiency of customized buses, in view of the problem of ignoring the distance between the boarding area and the alighting area, and setting it as a fixed value when performing custom bus route optimization modeling, as well as solving the problem of multiple custom bus parking lots. This paper proposes a method based on the NSGA-II algorithm using a three-stage hybrid coding method to solve. First, according to real life, the entire operation process of customized buses is divided into four phases. Second, based on the four stages, a multi-objective optimization model of customized bus routes that satisfies multiple parking lots, multiple cars, and multiple boarding and alighting stations is constructed to pursue the minimum total travel time of passengers and minimizes the operating costs of customized bus companies. Third, the NSGA-II algorithm is employed to solve the model, including three-stage hybrid coding, segmented crossover, and segmented mutation operators. Finally, the local road network in Lanzhou City is adopted for simulation research. The results show that it is feasible to use NSGA-II algorithm to solve the problem of customizing bus routes for multiple parking lots, multiple vehicles, and multiple boarding and alighting stations. The research results are of great value for exploring the optimization methods of customized bus routes and improving the operating efficiency of custom buses.

scholarly journals Optimal Scheduling of Hydro–PV–Wind Hybrid System Considering CHP and BESS Coordination

2019 ◽  
Vol 9 (5) ◽  
pp. 892 ◽  
Author(s):  
Shengmin Tan ◽  
Xu Wang ◽  
Chuanwen Jiang
Keyword(s):  
Renewable Energy ◽  
Hybrid System ◽  
Renewable Resources ◽  
Renewable Energy Sources ◽  
Real Life ◽  
Latin Hypercube Sampling ◽  
Optimal Scheduling ◽  
Latin Hypercube ◽  
Piecewise Linearization ◽  
Proposed Model

Coordination of a hydropower, combined heat and power (CHP), and battery energy storage system (BESS) with multiple renewable energy sources (RES) can effectively reduce the adverse effects of large-scale renewable energy integration in power systems. This paper proposes a concept of a renewable-based hybrid energy system and puts forward an optimal scheduling model of this system, taking into account the cost of operation and risk. An optimization method is proposed based on Latin hypercube sampling, scene reduction, and piecewise linearization. Firstly, a large number of samples were generated with the Latin hypercube sampling method according to the uncertainties, including the renewable resources availability, the load demand, and the risk aversion coefficients, and the generated samples were reduced with a scene reduction method. Secondly, the piecewise linearization method was applied to convert nonlinear constraints into linear to obtain the best results of each scene. Finally, the performance of the proposed model and method was evaluated based on case studies with real-life data. Results showed that the renewable-based hybrid system can not only reduce the intermittent and volatility of renewable resources but also ensure the smooth of tie-line power as much as possible. The proposed model and method are universal, feasible, and effective.

Fuzzy multi-objective location and routing problem

2020 ◽  
Vol 39 (3) ◽  
pp. 3259-3273
Author(s):  
Nasser Shahsavari-Pour ◽  
Najmeh Bahram-Pour ◽  
Mojde Kazemi
Keyword(s):  
Firefly Algorithm ◽  
High Reliability ◽  
Research Area ◽  
Nsga Ii ◽  
Location Routing Problem ◽  
Routing Problem ◽  
Location Allocation ◽  
Multi Objective ◽  
Location Routing ◽  
The Cost

The location-routing problem is a research area that simultaneously solves location-allocation and vehicle routing issues. It is critical to delivering emergency goods to customers with high reliability. In this paper, reliability in location and routing problems was considered as the probability of failure in depots, vehicles, and routs. The problem has two objectives, minimizing the cost and maximizing the reliability, the latter expressed by minimizing the expected cost of failure. First, a mathematical model of the problem was presented and due to its NP-hard nature, it was solved by a meta-heuristic approach using a NSGA-II algorithm and a discrete multi-objective firefly algorithm. The efficiency of these algorithms was studied through a complete set of examples and it was found that the multi-objective discrete firefly algorithm has a better Diversification Metric (DM) index; the Mean Ideal Distance (MID) and Spacing Metric (SM) indexes are only suitable for small to medium problems, losing their effectiveness for big problems.

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