CN108045374B - A kind of intelligent electric vehicle autonomous driving decision-making technique for taking into account driving economy - Google Patents

A kind of intelligent electric vehicle autonomous driving decision-making technique for taking into account driving economy Download PDF

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CN108045374B
CN108045374B CN201710998555.3A CN201710998555A CN108045374B CN 108045374 B CN108045374 B CN 108045374B CN 201710998555 A CN201710998555 A CN 201710998555A CN 108045374 B CN108045374 B CN 108045374B
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driving
power consumption
executes
decision
task
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CN108045374A (en
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孙宾宾
高松
李鹏程
于文琪
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Shandong University of Technology
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Shandong University of Technology
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    • BPERFORMING OPERATIONS; TRANSPORTING
    • B60VEHICLES IN GENERAL
    • B60WCONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W30/00Purposes of road vehicle drive control systems not related to the control of a particular sub-unit, e.g. of systems using conjoint control of vehicle sub-units, or advanced driver assistance systems for ensuring comfort, stability and safety or drive control systems for propelling or retarding the vehicle
    • B60W30/18Propelling the vehicle
    • B60W30/182Selecting between different operative modes, e.g. comfort and performance modes
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06QDATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00Administration; Management
    • G06Q10/06Resources, workflows, human or project management, e.g. organising, planning, scheduling or allocating time, human or machine resources; Enterprise planning; Organisational models
    • G06Q10/063Operations research or analysis
    • G06Q10/0637Strategic management or analysis
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06QDATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q50/00Systems or methods specially adapted for specific business sectors, e.g. utilities or tourism
    • G06Q50/30Transportation; Communications
    • YGENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02TCLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
    • Y02T10/00Road transport of goods or passengers
    • Y02T10/80Technologies aiming to reduce greenhouse gasses emissions common to all road transportation technologies
    • Y02T10/84Data processing systems or methods, management, administration

Abstract

A kind of intelligent electric vehicle autonomous driving decision-making technique for taking into account driving economy, belong to intelligent vehicle automation field, it is characterized in that the distribution characteristics of risk source in domain can be threatened according to different brackets, autonomous driving decision adaptable therewith is executed, from level Intelligent Optimal electric vehicle driving economy of making decisions on one's own.It makes decisions on one's own field the invention belongs to intelligent vehicle, related technical solution are as follows: threaten in domain from lane level-one there are when danger source, by calculating whether driving economy and lane-change value-at-risk, decision vehicle execute lane-change;From lane level-one threaten domain not in threaten in domain there are when danger source there are danger source and from lane second level, by calculating driving economy and risk growth rate, whether decision vehicle executes economy optimization Driving Decision-making strategy;It threatens in domain from lane level-one and second level there is no when danger source, by calling economy optimization to refer to driving strategy, carries out vehicle autonomous driving Decision Control.

Description

A kind of intelligent electric vehicle autonomous driving decision-making technique for taking into account driving economy
Technical field
It makes decisions on one's own field the invention belongs to intelligent vehicle, is related to a kind of autonomous driving decision-making party for intelligent electric motor car Method.
Background technique
Currently, facing increasingly serious energy crisis, environmental pollution and traffic safety three major issues, develop intelligent electric motor car Just by automobile industry extensive concern.Vehicle is driven different from conventional driver, establishes autonomous driving decision system to substitute It is the key that various forms intelligent vehicle needs solve common problem that human driver, which carries out Driving Decision-making,.Existing autonomous driving Decision Control method is generally confined to guarantee driving safety, and has ignored driving economy and optimize this key factor, does not fill Divide and excavates intelligent electric vehicle economy optimization space.For this purpose, the invention proposes a kind of intelligence electricity for taking into account driving economy Motor-car autonomous driving decision-making technique.
Summary of the invention
According to the above-mentioned deficiencies in the prior art, the problem to be solved in the present invention is: proposing that one kind takes into account driving economy Intelligent electric vehicle autonomous driving decision-making technique, from the driving economy of Driving Decision-making level Intelligent Optimal electric vehicle.
The technical scheme is that a kind of intelligent electric vehicle autonomous driving decision-making technique for taking into account driving economy, Specifically:
(1) firstly, the main program detection current lane level-one of the autonomous driving decision-making technique threatens area to whether there is risk Source, and if it exists, then call subroutine 1;If it does not exist, then further detection current lane second level threatens area to whether there is risk Source;If current lane second level threatens area, there are risk source, call subroutines 2;If current lane second level threatens area that wind is not present Dangerous source, then call subroutine 3;
(2) subprogram 1 can specifically be stated are as follows:
Whether the subprogram needs to carry out lane-change for decision vehicle, firstly, program according to vehicle's current condition parameter and Driving power consumption model calculates vehicle current power consumption and currently minimum with reference to power consumption, if vehicle current power consumption is minimum no more than currently With reference to k times of power consumption, then without carrying out lane-change decision, vehicle carries out driving control according to current driving strategy in current lane System;If vehicle current power consumption is greater than current minimum k times with reference to power consumption, further progress lane-change decision is needed;For this purpose, program is first First according to vehicle's current condition parameter and driving behavior, the value-at-risk in the case of vehicle lane-changing is calculated;If the wind in the case of lane-change Danger value is higher than to threshold value, then without lane-change;Otherwise, lane-change decision is carried out;
(3) subprogram 2 can specifically be stated are as follows:
Whether the subprogram needs to be implemented economy optimization driving strategy for decision vehicle, firstly, program is according to vehicle Current state parameter and driving power consumption model calculate vehicle current power consumption and currently minimum with reference to power consumption, if vehicle current power consumption No more than current minimum k times with reference to power consumption, then vehicle carries out Driving control according to current driving strategy in current lane; If vehicle current power consumption is greater than current minimum k times with reference to power consumption, further progress driving economy Optimal Decision-making is needed;For This, calling economy optimization first refers to driving strategy, refers to driving strategy to determine;Further, it calculates above-mentioned with reference to driving Tactful down train risk change rate;If risk growth rate is greater than 0 and is higher than given value, vehicle is in current lane according to current Driving strategy carry out Driving control;Otherwise, vehicle reference economy optimization Driving Decision-making strategy carries out Decision Control;
(4) subprogram 3 can specifically be stated are as follows:
The subprogram is mainly used for decision vehicle and executes economy optimization driving strategy, firstly, program is current according to vehicle State parameter and driving power consumption model calculate vehicle current power consumption and currently minimum with reference to power consumption, if vehicle current power consumption is little In current minimum k times with reference to power consumption, then vehicle carries out Driving control according to current driving strategy in current lane;If vehicle Current power consumption is greater than current minimum k times with reference to power consumption, then calls economy optimization with reference to driving strategy progress Decision Control.
The present invention has the advantages that
1, it based on control method of making decisions on one's own proposed by the invention, can drive a vehicle from decision-making level's Intelligent Optimal electric vehicle Economy is conducive to extend the continual mileage of intelligent electric motor car;
2, based on control method of making decisions on one's own proposed by the invention, the driving of intelligent electric vehicle can be solved from decision-making level The optimization problem that cooperates with of safety and driving economy improves intelligent electric vehicle overall performance.
Detailed description of the invention
Fig. 1 is a kind of intelligent electric vehicle driving threat level schematic diagram;
Fig. 2 is that a kind of intelligent electric vehicle for taking into account driving economy is made decisions on one's own method main program;
Fig. 3 is that a kind of intelligent electric vehicle for taking into account driving economy is made decisions on one's own method subprogram 1;
Fig. 4 is that a kind of intelligent electric vehicle for taking into account driving economy is made decisions on one's own method subprogram 2;
Fig. 5 is that a kind of intelligent electric vehicle for taking into account driving economy is made decisions on one's own method subprogram 3.
Specific embodiment
The invention will be further described with reference to the accompanying drawing:
The intelligent electric vehicle driving threat level of Fig. 1 includes: that level-one threatens, second level threatens and three-level threatens three kinds of grades Not.Wherein, if current lane level-one threatens in area there are risk source, intelligent electric vehicle needs to carry out lane-change Driving Decision-making; If if current lane level-one, which threatens, is not present the dangerous source of risk source and current lane second level risk area, intelligent electric in area Vehicle needs whether decision executes economy optimization with reference to Driving Decision-making strategy;If current lane level-one and second level threaten in area There is no risk sources, then intelligent electric vehicle executes economy optimization and refers to Driving Decision-making strategy.
Fig. 2 is that a kind of intelligent electric vehicle for taking into account driving economy is made decisions on one's own method main program, it is characterised in that:
Firstly, Programmable detection current lane level-one, which threatens, whether there is risk source in area, if so, call subroutine 1;It is no Then, further detection current lane second level risk area whether there is danger source, if so, call subroutine 2;Otherwise, son is called Program 3.
Fig. 3 is that a kind of intelligent electric vehicle for taking into account driving economy is made decisions on one's own method subprogram 1, it is characterised in that:
(1) firstly, program reads vehicle and critical component state parameter;
(2) the power consumption calculation model secondly, routine call is driven a vehicle;
(3) further, according to above-mentioned state parameter and driving power consumption model, vehicle current power consumption Pl and current minimum is calculated With reference to power consumption Ps;
(4) further, program judges P1 and Ps size relation, if Pl >=kPs is invalid, illustrates that vehicle current power consumption is in Acceptable degree, vehicle execute current Driving Decision-making without carrying out lane-change decision in current lane;If Pl >=kPs at Vertical, illustrating vehicle current power consumption still has reduction space, and vehicle needs to carry out lane-change decision;
(5) when vehicle needs to carry out lane-change decision, routine call first is driven a vehicle risk computation model, and calculates lane-change feelings Value-at-risk S1 under condition;If S1≤Sm is set up, illustrate that, there is no lane-change risk, vehicle executes lane-change decision;Otherwise, vehicle is being worked as Current Driving Decision-making is executed in preceding lane.
Fig. 4 is that a kind of intelligent electric vehicle for taking into account driving economy is made decisions on one's own method subprogram 2, it is characterised in that:
1. firstly, program reads vehicle and critical component state parameter;
2. the power consumption calculation model secondly, routine call is driven a vehicle;
(3) further, according to above-mentioned state parameter and driving power consumption model, vehicle current power consumption Pl and current minimum is calculated With reference to power consumption Ps;
(4) further, program judges P1 and Ps size relation, if Pl >=kPs is invalid, illustrates that vehicle current power consumption is in Acceptable degree, vehicle execute current Driving Decision-making without carrying out economy optimization Driving Decision-making in current lane;If Pl >=kPs is set up, and illustrating vehicle current power consumption still has reduction space, and vehicle needs to carry out economy optimization Driving Decision-making;
(5) when vehicle needs to carry out economy optimization Driving Decision-making, routine call economy optimization first is with reference to driving Strategy, and calculate the driving risk change rate △ S under current reference driving strategy;If 0 < △ S≤△ Sm is set up, illustrate to drive a vehicle Risk variation is in acceptable degree, and vehicle executes economy and optimizes Driving Decision-making;Otherwise, vehicle executes in current lane and works as Preceding Driving Decision-making.
Fig. 5 is that a kind of intelligent electric vehicle for taking into account driving economy is made decisions on one's own method subprogram 3, it is characterised in that:
(1) firstly, program reads vehicle and critical component state parameter;
(2) the power consumption calculation model secondly, routine call is driven a vehicle;
(3) further, according to above-mentioned state parameter and driving power consumption model, vehicle current power consumption Pl and current minimum is calculated With reference to power consumption Ps;
(4) further, program judges P1 and Ps size relation, if Pl >=kPs is invalid, illustrates that vehicle current power consumption is in Acceptable degree, vehicle execute current Driving Decision-making without carrying out economy optimization Driving Decision-making in current lane;If Pl >=kPs is set up, and illustrating vehicle current power consumption still has reduction space, and vehicle calls and executes economy optimization with reference to driving plan Slightly.

Claims (1)

1. a kind of intelligent electric vehicle autonomous driving decision-making technique for taking into account driving economy: it is characterized in that, can be according to not Ad eundem threatens the distribution characteristics of risk source in domain, executes autonomous driving decision adaptable therewith, excellent from the level of making decisions on one's own Change intelligent electric vehicle driving economy, specific rate-determining steps are as follows:
(1) main program rate-determining steps are as follows:
Step S01 is then, to execute step S02 for detecting in 1 grade of threat domain of current lane with the presence or absence of risk source;Otherwise, it holds Row step S03;
Step S02 is used for call subroutine 1;
Step S03 is then, to execute step S04 for detecting in 2 grades of threat domains of current lane with the presence or absence of risk source;Otherwise, it holds Row step S05;
Step S04 is used for call subroutine 2;
Step S05 is used for call subroutine 3;
(2) 1 step of subprogram are as follows:
Step S11 executes the reading vehicle and critical component state parameter of the task;
Step S12 executes the calling driving power consumption calculation model of the task;
Step S13 calculate vehicle current power consumption and it is minimum refer to power consumption;
Step S14 judges current power consumption and the k times of minimum size with reference to power consumption, if current power consumption is minimum less than k times to refer to power consumption, Execute step S15;Otherwise, step S16 is executed;
Step S15 executes the task of current Driving Decision-making;
Step S16 executes the calling driving risk computation model of the task;
Step S17 calculates lane-change situation down train value-at-risk;
Step S18 judges the size of lane-change situation down train value-at-risk Yu given risk reference value, if the driving in the case of lane-change Value-at-risk thens follow the steps S19 no more than given risk reference value;Otherwise, step S110 is executed;
The task of step S19 execution lane-change decision;
Step S110 executes the task of current Driving Decision-making;
(3) 2 step of subprogram are as follows:
Step S21 executes the reading vehicle and critical component state parameter of the task;
Step S22 executes the calling driving power consumption calculation model of the task;
Step S23 calculate vehicle current power consumption and it is minimum refer to power consumption;
Step S24 judges current power consumption and the k times of minimum size with reference to power consumption, if current power consumption is minimum less than k times to refer to power consumption, Execute step S25;Otherwise, step S26 is executed;
Step S25 executes the task of current Driving Decision-making;
Step S26 executes task of economy optimization being called to refer to driving strategy;
Step S27 calculates economy optimization with reference to the driving risk change rate under driving strategy;
Step S28 judges that economy optimization refers to driving risk change rate and given risk change rate reference value under driving strategy Size, if economy optimization with reference to the driving risk change rate under driving strategy is greater than 0 and no more than given risk change rate Reference value thens follow the steps S29;Otherwise, step S210 is executed;
Step S29 executes the task that economy optimization refers to Driving Decision-making;
Step S210 executes the task of current Driving Decision-making;
(4) 3 step of subprogram are as follows:
Step S31 executes the reading vehicle and critical component state parameter of the task;
Step S32 executes the calling driving power consumption calculation model of the task;
Step S33 calculate vehicle current power consumption and it is minimum refer to power consumption;
Step S34 judges current power consumption and the k times of minimum size with reference to power consumption, if current power consumption is minimum less than k times to refer to power consumption, Execute step S35;Otherwise, step S36 is executed;
Step S35 executes the task of current Driving Decision-making;
Step S36 executes the calling driving risk computation model of the task;
Step S37 executes the task that economy optimization refers to Driving Decision-making strategy.
CN201710998555.3A 2017-10-24 2017-10-24 A kind of intelligent electric vehicle autonomous driving decision-making technique for taking into account driving economy Active CN108045374B (en)

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CN102514571B (en) * 2012-01-05 2015-02-04 潍柴动力股份有限公司 Driver driving economy evaluation system and method
CN104376400A (en) * 2014-10-27 2015-02-25 广州市中南民航空管通信网络科技有限公司 Risk assessment method based on fuzzy matrix and analytic hierarchy process
CN105109485B (en) * 2015-08-24 2018-02-16 奇瑞汽车股份有限公司 A kind of drive manner and system
CN107180288B (en) * 2017-07-21 2020-05-01 东软集团股份有限公司 Driving behavior energy consumption measuring and calculating method and device, storage medium and electronic equipment

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