# US 2014/0195093 A1 · Autonomous Driving Merge Management System

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- Number: US 2014/0195093 A1
- Document ID: US20140195093A1
- Status: Published application
- Kind: A1
- Application number: 13/733,919
- Filed: 2013-01-04
- Published: 2014-07-10
- Earliest claimed: 2013-01-04
- Assignees: Carnegie Mellon University; GM Global Technology Operations LLC
- Applicants: GM Global Technology Operations LLC; Carnegie Mellon University
- Inventors: BAKHTIAR BRIAN LITKOUHI; JUNQING WEI; JOHN M. DOLAN
- Web page: https://patentgrep.com/patent/US20140195093A1

## CPC

- B62D 15/0255: {Automatic changing of lane, e.g. for passing another vehicle}
- B60W 30/18163: {Lane change; Overtaking manoeuvres}
- G08G 1/167: {Driving aids for lane monitoring, lane changing, e.g. blind spot detection}
- B62D: MOTOR VEHICLES; TRAILERS (steering, or guiding on a desired track, of agricultural machines or implements A01B69/00; wheels, castors, axles, increasing wheel adhesion B60B; vehicle tyres, tyre inflation or tyre changing B60C; connections between vehicles of a train or the like B60D; vehicles for use on rail and road, amphibious or convertible vehicles B60F; suspension arrangements B60G; heating, cooling, ventilating or other air treating devices B60H; windows, windscreens, non-fixed roofs, doors or similar devices, protective coverings for vehicles not in use B60J; propulsion plant arrangements, auxiliary drives, transmissions, controls, instrumentation or dashboards B60K; electric equipment or propulsion of electrically-propelled vehicles B60L; power supply for electrically-propelled vehicles B60M; passenger accommodation not otherwise provided for B60N; adaptations for load transportation or to carry special loads or objects B60P; arrangement of signalling or lighting devices, the mounting or supporting thereof or circuits therefor, for vehicles in general B60Q; vehicles, vehicle fittings or vehicle parts not otherwise provided for B60R; servicing, cleaning, repairing, supporting, lifting, or manoeuvring, not otherwise provided for, B60S; brake arrangements, brake control systems or parts thereof B60T; air-cushion vehicles B60V; motor-cycles, accessories therefor B62J, B62K; testing of vehicles G01M)
- B60W: CONJOINT 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
- G08G: TRAFFIC CONTROL SYSTEMS (guiding railway traffic, ensuring the safety of railway traffic B61L; arrangement of road signs or traffic signals E01F9/00; radar or analogous systems, sonar systems, lidar systems specially adapted for traffic control G01S13/91, G01S15/88, G01S17/88; {radar or analogous systems, sonar systems, lidar systems specially adapted for anti-collision purposes G01S13/93, G01S15/93, G01S17/93})

## Abstract

An autonomous driving merge management system includes an autonomous driving control device and an intention decision management system. The management system includes a candidate strategy subsystem generating a plurality of candidate driving strategies, a merging vehicle behavior recognition subsystem predicting a merging intention of a merging vehicle; an intention-based interactive prediction subsystem predicting future merging scenarios between the host vehicle and merging vehicle as a function of inputs by the merging vehicle behavior recognition subsystem and inputs by the candidate strategy subsystem, and a cost function-based evaluation subsystem determining a cost for each future merging scenario generated by the intention-based interactive prediction subsystem. A processor selects a merge strategy of the host vehicle based on intention-based prediction results and cost function-based evaluation results. The autonomous driving control device applies the merge strategy to the host vehicle for allowing the merging vehicle to cooperatively merge with the host vehicle.

## Claims

### Claim 1

An autonomous driving merge management system comprising:
an autonomous driving control device for autonomously controlling accelerations of a host vehicle;
an intention decision management system comprising:
a candidate strategy subsystem generating a plurality of candidate driving strategies, each candidate driving strategy being a potential driving strategy executable by the host vehicle;
a merging vehicle behavior recognition subsystem predicting a merging intention of a merging vehicle; the merging intention relating to a positive acceleration or a negative acceleration of the merging vehicle;
an intention-based interactive prediction subsystem predicting future merging scenarios between the host vehicle and merging vehicle as a function of inputs by the merging vehicle behavior recognition subsystem and inputs by the candidate strategy subsystem;
a cost function-based evaluation subsystem determining a cost for each future merging scenario generated by the intention-based interactive prediction subsystem; and
a processor for selecting a merge strategy of the host vehicle based on intention-based prediction results and cost function-based evaluation results;
wherein the autonomous driving control device applies the merge strategy to the host vehicle for allowing the merging vehicle to cooperatively merge with the host vehicle.

### Claim 2 (depends on 1)

The autonomous driving merge management system of claim 1 wherein the cost function-based evaluation subsystem determines the cost for each scenario based on a progress cost, a comfort cost, a safety cost, and fuel consumption cost associated with a respective scenario.

### Claim 3 (depends on 2)

The autonomous driving merge management system of claim 2 wherein the progress cost includes an efficiency of completing a task during a merging maneuver.

### Claim 4 (depends on 2)

The autonomous driving merge management system of claim 2 wherein the comfort cost includes avoiding excessive accelerations of the vehicle to complete the merging maneuver.

### Claim 5 (depends on 2)

The autonomous driving merge management system of claim 2 wherein the safety cost includes maintaining a respective distance to the merging vehicle and maintaining a braking distance based on the velocity of the host vehicle and merging vehicle.

### Claim 6 (depends on 2)

The autonomous driving merge management system of claim 2 wherein the fuel consumption cost includes an amount of fuel expended to complete a merging maneuver.

### Claim 7 (depends on 2)

The autonomous driving merge management system of claim 2 wherein the cost function-based evaluation subsystem determines the cost for a respective scenario based on the following formula:
Csce=μ1Cprogress+μ2Ccomfort+μ3Csafety+μ4Cfuel (8)
where Cprogress is the progress cost, Ccomfort is the comfort cost, Csafety is the safety cost, Cfuel fuel consumption cost, and μ1, μ2, μ3, and μ4 represent weight factors.

### Claim 8 (depends on 7)

The autonomous driving merge management system of claim 7 wherein a cost for a respective strategy for a respective intention is represented by the following formula:
C
str

(
i
)

I
=
∑
t
=
0
t
Predict


(
C
sce
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(
i
,
t
)

I
where Csce(i,t) is a cost of an ith scenario for a respective time t, I is an intention, and tPredict is a duration of time over which system will predict the respective scenario.

### Claim 9 (depends on 8)

The autonomous driving merge management system of claim 8 wherein a cost for a respective strategy given a respective probability of an intention is represented by the following formula:
Cstr(i)=p(I=Y)Cstr(i)|Y+p(I=N)Cstr(i)|N
where p(I=Y) is a probability of the remote vehicle yielding during the merging maneuver, p(I=Y)Cstr(i)|Y is the cost associated to the host vehicle given the probability as a result of the merging vehicle yielding to the host vehicle, p(I=N) is a probability of the merging vehicle not yielding during the merging maneuver, and p(I=N)Cstr(i)|N is the cost associated to the host vehicle given the probability as a result of the merging vehicle not yielding to the host vehicle.

### Claim 10 (depends on 1)

The autonomous driving merge management system of claim 1 wherein the merging vehicle behavior recognition subsystem utilizes a statistical merging vehicle model for determining a vehicle behavior of the merging vehicle.

### Claim 11 (depends on 1)

The autonomous driving merge management system of claim 1 wherein statistical merging vehicle model is represented by the following formula:
p
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p
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where p(Y|B|) is the probability of merging vehicle's intention to yield (Y) given an observed behavior B, and p(B|Y) and p(B|N) are respectively probabilities of the same behavior given intention Y or N.

### Claim 12 (depends on 10)

The autonomous driving merge management system of claim 10 wherein the statistical merging vehicle model is derived from a deterministic model utilizing a Gaussian distribution.

### Claim 13 (depends on 10)

The autonomous driving merge management system of claim 10 wherein the statistical merging vehicle model is represented by the following equations:
dyield=dC−(dmin+kvvhost)
dnyield=dC+(dmin+kvvhost)
Δt=(dyield,nyield−dmerge)/vmerge−(dC−dhost)/vhost
accmerge=cgainΔt
where dyield is the distance from C to Dyield, dnyield the distance from C to Dnyield, dmin is the minimum desired distance to the leading vehicle, k is a gain causing the desired distance to grow with the host vehicle's speed, dmerge and dhost are the positions of the merging and host vehicles at any given instance of time, accmerge is a desired control command for the merging vehicle, Δt is a time difference between the host vehicle and merging vehicle arrivals at C, and cgain is the proportional gain converting the time difference into the acceleration command of the merging vehicle.

### Claim 14 (depends on 1)

The autonomous driving merge management system of claim 1 wherein the autonomous driving control device includes a speed controller device.

### Claim 15 (depends on 1)

The autonomous driving merge management system of claim 1 wherein the intention decision management system determines an intention of the merging vehicle to merge relative to the host vehicle when transitioning from an entrance ramp to a primary driven road traveled by the host vehicle.

### Claim 16 (depends on 1)

The autonomous driving merge management system of claim 1 wherein the intention decision management system determines an intention of the merging vehicle relative to the host vehicle when changing lanes from an adjacent lane to a primary driven lane of the host vehicle.

### Claim 17

A method for autonomously controlling a vehicle speed during a merging maneuver between a host vehicle and a merging vehicle, the method comprising the steps of:
obtaining speed data and position data of the host vehicle and the remote data;
generating a plurality of candidate driving strategies by a processor, each candidate driving strategy being a potential driving strategy executable by the host vehicle;
predicting an intention of the merging vehicle to merge forward or rearward of the host vehicle by the processor,
generating a plurality of merging scenarios between the host vehicle and merging vehicle by the processor as a function of the predicted merging intention of the merging vehicle and the plurality of candidate driving strategies;
determining a cost for each merging scenario by the processor based on a cost function evaluation analysis technique;
selecting a merge strategy of the host vehicle by the processor based on the cost function evaluation results; and
autonomously controlling accelerations of a host vehicle using an autonomous driving control device, wherein the autonomous driving control device applies the merge strategy to the host vehicle for cooperatively allowing the merging vehicle to cooperatively merge with the host vehicle.

### Claim 18 (depends on 17)

The method of claim 17 wherein processor determines the cost for each scenario based on a progress cost, a comfort cost, a safety cost, and fuel consumption cost associated with a respective scenario.

### Claim 19 (depends on 18)

The method of claim 18 wherein the processor determines the cost for a respective scenario based on the following formula:
Csce=μ1Cprogress+μ2Ccomfort+μ3Csafety+μ4Cfuel (8)
where Cprogress is the progress cost, Ccomfort is the comfort cost, Csafety is the safety cost, Cfuel fuel consumption cost, and μ1, μ2, μ3, and μ4 represent weight factors.

### Claim 20 (depends on 19)

The method of claim 19 wherein a cost for a respective strategy for a respective intention is represented by the following formula:
C
str

(
i
)

I
=
∑
t
=
0
t
Predict


(
C
sce

(
i
,
t
)

I
where Csce(i,t) is a cost of an ith scenario for a respective time t, I is an intention, and tPredict is a duration of time over which system will predict the respective scenario.

### Claim 21 (depends on 20)

The method of claim 20 wherein a cost for a respective strategy given a respective probability of an intention is represented by the following formula:
Cstr(i)=p(I=Y)Cstr(i)|Y+p(I=N)Cstr(i)|N
where p(I=Y) is a probability of the remote vehicle yielding during the merging maneuver, p(I=Y)Cstr(i)|Y is the cost associated to the host vehicle given the probability as a result of the merging vehicle yielding to the host vehicle, p(I=N) is a probability of the merging vehicle not yielding during the merging maneuver, and p(I=N)Cstr(i)|N is the cost associated to the host vehicle given the probability as a result of the merging vehicle not yielding to the host vehicle.