2.2. luís gonçalo campos, paulo fernandes, margarida c. coelho

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Scientists for Cycling Colloquium November 17-19, 2016 05-07-2022 1 Safer cycling routes to the university: Analysis of conflicts between motor vehicles and bicycles Luís Gonçalo Campos, Paulo Fernandes , Margarida C. Coelho University of Aveiro, R&D Group on Transportation Technology, Centre for Mechanical Technology and Automation (TEMA) / Department of Mechanical Engineering

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Page 1: 2.2. luís gonçalo campos, paulo fernandes, margarida c. coelho

Scientists for Cycling Colloquium November 17-19, 2016

01-05-2023 1

Safer cycling routes to the university: Analysis of conflicts between motor

vehicles and bicycles

Luís Gonçalo Campos, Paulo Fernandes, Margarida C. CoelhoUniversity of Aveiro, R&D Group on Transportation Technology, Centre for

Mechanical Technology and Automation (TEMA) / Department of Mechanical Engineering

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Scientists for Cycling Colloquium November 17-19, 2016

01-05-2023 2

IntroductionCyclists in cities?

Portugal recorded 7,697 accidents involving bicycles in 2010-2014 period, which resulted in 307 fatalities (ANSR, 2016)

The increasing number of bicycles on the road infrastructure causes more conflicts with motor vehicles;

An argument concerning the use of bicycles in cities deals with safety and concerns with the presence and unexpected behaviors of motorized users.

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Scientists for Cycling Colloquium November 17-19, 2016

01-05-2023 3

Objectives

How do the number of conflicts and the probability of collisions between vehicles and bicycles vary with different bicycle facilities, and variations in bicycle demands and speeds?

How do the design features of a specific bicycle route affect the spatial distribution of road safety indicators?

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Scientists for Cycling Colloquium November 17-19, 2016

01-05-2023 4

Methodology – Case Study

Source: https://maps.google.com/

Route A 2.4 km Route B 2.3 km Route C 3.95 km

Origin: Aveiro Train StationDestination: University of Aveiro (Rectory)

Origin

Destination

Origin

Destination

Origin

DestinationDedicate bicycle path

Route A

Dedicate bicycle path

Route B

Dedicate bicycle path

Route C

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Scientists for Cycling Colloquium November 17-19, 2016

01-05-2023 5

Methodology – Data Collection

• Traffic and Bicycle volumes;• Vehicle GPS traces;• Origin-Destination Matrices;• Road and Intersection

geometry.Dedicate

bicycle path Bicycle

counts point

Source: https://maps.google.com/

Origin

Destination

Morning peak conditions(7:30-9:00 a.m.)

780 vehicles13 cyclists

690 vehicles17 cyclists

630 vehicles25 cyclists

490 vehicles15 cyclists

650 vehicles25 cyclists

340 vehicles18 cyclists

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Scientists for Cycling Colloquium November 17-19, 2016

01-05-2023 6

Methodology – Traffic and Safety Modeling

• Time to Collision (TTC)• Post-Encroachment Time (PET);• Initial Deceleration Rate (DR);• Maximum speed (MaxS);• Maximum relative speed difference

(DeltaS);• Types and location of the conflicts.

SSAM Model

Vehicles Trajectories(Files *.trj)

• Car Fleet;• Bicycle Volumes;• Routes Definition;• Driving behavior patterns;• Speed and Acceleration;

Inputs(VISSIM)

• Delay• Vehicle

Stops

Traffic Outputs (VISSIM)

Safety Outputs (SSAM)

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01-05-2023 7

Methodology – Safety Modeling

If during an interaction TTC and PET drop below 1.5 s and 5.0 s

Types of Conflicts

if 0º < conflict angle < 30°

if 30º <conflict angle < 85°

if 85º <conflict angle < 180°

Rear endCrossing

Lane Changing

Conflict

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Scientists for Cycling Colloquium November 17-19, 2016

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Methodology – Alternative Scenarios

Baseline Network-specific traffic and bicycling demands

Scenario 1 (S1) Dedicated bicycle lanes along the entire routes and = number of bicycles;

Scenario 2 (S2) Increase the number of bicycles in 10x and = number of bicycles;

Scenario 3 (S3) Speed limit of 30 km/h on the roads alongside of routes and = number of bicycles.

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Scientists for Cycling Colloquium November 17-19, 2016

01-05-2023 9

Results – Traffic Performance

Baseline Scenario

S1 S2 S30

5,000

10,000

15,000

20,000

25,000

7072747678808284868890

Number of stops Number of Vehicles Delay

Num

ber o

f sto

ps

Dela

y [S

econ

ds]

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Results – Number of Conflicts

Route Scenario Crossing Rear End Lane Change Total

A

Baseline 7.7 244.1 61.1 312.9S1 -3% -29% -23% -27%S2 -4% 17% 20% 17%S3 0% 1% -3% 0%

B

Baseline 7.7 244.1 61.1 312.9S1 -10% -29% -24% -28%S2 -6% 20% 22% 20%S3 1% 4% -4% 2%

C

Baseline 7.7 244.1 61.1 312.9S1 29% -5% -3% -4%S2 243% 12% 39% 19%S3 143% 28% 22% 27%

Lowest value among scenariosHighest value among scenarios

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Results – Hotspot Conflicts LocationRoute A Route B Route C

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Conclusions

S2 and S3 resulted in more delay and vehicles stops while S1 improved traffic performance compared to the baseline;

There was not a consensus about the safest route;

S1 reduced the number and the severity conflicts for all routes, but S3 was associated with the lowest severity of resulting crashes;

Hotspot conflicts locations were located near multi-lane roundabouts and signalized intersections.

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Transportation Technology Research Group - Centre for Mechanical Technology and Automation (TEMA), University of Aveiro,

[email protected]

Thank you for your attention.