CONNECTED AUTONOMOUS VEHICLE

CONTROL OPTIMIZATION AT

INTERSECTIONS

Guohui Zhang

University of New Mexico

Department of Civil Engineering

December 11, 2015

CONTENT

Background Information

Connected Autonomous Vehicle System Operation

Autonomous Intersection Control Optimization

Interoperable Arterial Management

Summary

From: Google

3

CONGESTION IS A WORLDWIDE PROBLEM

What Beijing's 62-Mile, Nine-Day Traffic Jam

Means For China's Turbulent Future of the Car? Source: http://www.popsci.com/science/article/62-mile-nine-day-traffic-jam-spells-disaster-communter-promise-chinas-auto-industry

CONGESTION IS A WORLDWIDE PROBLEM

Traffic congestion in

Albuquerque at 5 pm.

Delays at intersections

Account for 15% to 30% of all

traffic delays

295 million vehicle-hours of

delay on major roadways

Traffic Volume Map in Albuquerque at 5 pm

INTERSECTION SAFETY PERFORMANCE

Intersection Safety Issue in New Mexico

40.2% of all crashes are

intersection-related in 2011.

46.3% of urban crashes occurred

around intersections

(From: Albuquerque Journal) (From: New Mexico Traffic Crash Annual Report 2011)

Crashes in Albuquerque in 2011

INTERSECTION SAFETY PERFORMANCE

Intersection Safety Issues

90% roadway crashes are caused by human errors

Fail to yield right of way

Passed stop sign

Disregarded traffic signal

Use cellphone

Driver Fatigue

Alcohol involved, etc.

From: Google

WHAT ARE CVS AND AVS? Connected Vehicle are

technologies and applications that use wireless communications to provide connectivity: Among vehicles (V2V)

Between vehicles and infrastructure (V2I)

Between vehicles and hand held devices (V2D)

Autonomous Vehicle (AV) Google car

Automation includes incremental features such as adaptive cruise control, lane centering, automated braking

CAV-ENABLED TRAFFIC OPERATIONS

Autonomous Vehicle

Also known as a driverless vehicle, self-driving

vehicle and robotic vehicle

Capable of sensing its environment and navigating

without human input

According to the U.S. Department of Transportation

(USDOT) Research and Innovative Technology

Administration (RITA), 81% of all vehicle-involved

crashes can be avoided or mitigated based on

connected vehicle technologies. navigating without

human input

THE VEHICLE IS CONNECTED

Vehicle location

Destination

Traffic

Speed

Road surface

Weather…• Traffic lights will be eliminated

• 75% of vehicles will be autonomous vehicles by 2040.

• NHTSA plans to mandate inter-vehicle

communication technologies on every single vehicle by

2016

NHTSA LEVELS OF AUTOMATION

Automation Level Forecasted Range

Zero No Automation Now

I Function-Specific Now

II Combined Function Now to 3 years away

III Limited Self-Driving 3 to 10+ years away

IV Full Self-Driving 7 to 12+ years away

RESEARCH OBJECTIVES

Research Objectives

Innovative autonomous intersection control mechanism

Optimize autonomous vehicle operations at intersection

without signal control

Increase Intersection Capacity

Reduce Traffic Delay at intersection

Improve safety performance of intersections

Interoperable arterial management

From: USDOT

CAV CONTROL OPTIMIZATION AT

INTERSECTIONS

Basic Setting

Intersection

4-way

3 lane in each direction

Lane width: 12 feet

No left/right turning bay

No signal

Vehicles can go straight,

turn left/right through

every lane

CAV CONTROL OPTIMIZATION AT

INTERSECTIONS

Conflict Points (188 points)

CAV CONTROL OPTIMIZATION AT

INTERSECTIONS

Conflict Point Detection A crash will happen if

V1 and V2 arrived at the conflict point at the same time

∆𝑡 = 𝑡1 − 𝑡2 = 0

If we use time as the 3rd axis, and the vehicle is assumed to go through

the intersection with the same speed, then

CAV CONTROL OPTIMIZATION AT

INTERSECTIONS

Rolling-horizon-based Intersection Control Optimization

Formulate the problems

𝑥𝑖𝑗𝑘 = 𝑁 ∙ 𝐿 − 𝑟𝑖𝑗𝑘 ∙ 𝑐𝑜𝑠𝜃𝑖𝑗𝑘𝑦𝑖𝑗𝑘 = 𝑟𝑖𝑗𝑘 ∙ 𝑠𝑖𝑛𝜃𝑖𝑗𝑘

𝑡𝑖𝑗𝑘 =𝑁−𝑗+0.5 ∙𝐿∙𝑎𝑟𝑐𝑡𝑎𝑛

𝑦𝑖𝑗𝑘

𝑁∙𝐿−𝑥𝑖𝑗𝑘

𝑣𝑖𝑗𝑘+ 𝑡0𝑖𝑗𝑘

𝑁− 𝑗 ∙ 𝐿 ≤ 𝑟𝑖𝑗𝑘 ≤ (𝑁 − 𝑗 + 1) ∙ 𝐿

0 ≤ 𝜃𝑖𝑗𝑘 ≤ 𝜋/2

Scheduling optimization to minimize vehicle movement confliction

Search sample subdivision

Dynamic programming techniques

𝑥𝑖𝑗𝑘 = 𝑟𝑖𝑗𝑘 ∙ 𝑐𝑜𝑠𝜃𝑖𝑗𝑘𝑦𝑖𝑗𝑘 = 𝑟𝑖𝑗𝑘 ∙ 𝑠𝑖𝑛𝜃𝑖𝑗𝑘

𝑡𝑖𝑗𝑘 =

𝑗 − 0.5 ∙ 𝐿 ∙ 𝑎𝑟𝑐𝑡𝑎𝑛𝑦𝑖𝑗𝑘𝑥𝑖𝑗𝑘

𝑣𝑖𝑗𝑘+ 𝑡0𝑖𝑗𝑘

𝑗 − 1 ∙ 𝐿 ≤ 𝑟𝑖𝑗𝑘 ≤ 𝑗 ∙ 𝐿

0 ≤ 𝜃𝑖𝑗𝑘 ≤ 𝜋 2

CAV CONTROL OPTIMIZATION AT

INTERSECTIONS

Intersection Control Protocol

Centralized intersection controller

Accept vehicle requests

Calculate and check conflict points among vehicles

Determine the passing sequence of all vehicles

Follow the principal: first come first serve

CAVs

Send requests

Follow the order of sequence to go through the intersection

SIMULATION

Simulation-based Analysis

Simulation-based investigation on traffic system operations

provides a cost-effective, risk-free means of

Exploring optimal management strategies,

Identifying potential problems,

Evaluating various alternatives.

From: Google

SIMULATION

Software--------PTV Vissim

PTV Vissim is a microscopic multi-

modal traffic flow simulation software

package developed by PTV Planung

Transport Verkehr AG in Karlsruhe,

Germany.

The name is derived from "Verkehr In

Städten - SIMulationsmodell" (German

for "Traffic in cities - simulation

model").

VISSIM was first developed in 1992

and is today a global market leader.

From: Google

SIMULATION

Simulation Video

SIMULATION

Simulation Results

Traffic Delay (second)

The proposed algorithm

(RHICO) can significantly

improve the efficiency of

intersections than traffic

signals.

South

band

East

band

North

band

West

bandOverall LOS

Optimized Signalized Control 48.0 84.8 232.5 44.3 98.5 F

RHICO 16.0 12.4 17.2 12.8 14.8 B

0.0

50.0

100.0

150.0

200.0

250.0

South band East band North band West band Overall

Optimized Signalized Control DFROC

MOBILITY UNDER CAV ENVIRONMENT ON

ARTERIALS

Arterial CAV Operation Strategy

Arterial traffic operation coordination

Dynamic routing

Speed harmonization

Transit priority signal control

Reversible lanes

Managed lane systems

Coordinated corridor management

SUMMARY ON KEY ISSUES

Autonomous Intersection and Arterial Management

Different types of vehicle: truck, bus, pickup, van, etc.

Different traffic scenarios: evaluate the performance

Allow acceleration / deceleration in the intersection

Advanced control coordination strategy optimization

Mixed traffic composition demand

Q & A