Instituto Universitario de Investigación del Automóvil jueves, 14 de mayo de 2015 The influence of heavy goods vehicle traffic on accidents: the analysis

Instituto Universitario de Investigación del Automóvil

martes, 18 de abril de 2023

The influence of heavy goods vehicle The influence of heavy goods vehicle traffic on accidents: the analysis in two traffic on accidents: the analysis in two

transportation corridorstransportation corridors

Blanca Arenas RamírezBlanca Arenas Ramírez


The influence of heavy goods vehicle traffic on accidents: the analysisThe influence of heavy goods vehicle traffic on accidents: the analysisIn two freight transportation corridorsIn two freight transportation corridors

Contents

Methodology

Scenarios

Results in corridor

Conclusions

Results

Freight Transp. corridors

2

Contens

۞ INTERURBAN ROADS OF RCE NETWORK

Methodology developed to analyze the influence of traffic conditions: volume and traffic

composition, on accidents on different types of interurban roads belonging to the Spanish

network, by applying negative binomial models.

۞ HEAVY GOODS VEHICLES TRAFFIC EFFECTS

۞ SPANISH FREIGHT TRANSPORTATION CORRIDORS



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Data

• AP: toll motorways• AV: roads with limited access and free

motorways• C: single carriageway roads• DC: two undivided dual carriageways

Road types:



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Data



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Data

• Increasing trend in goods traffic,

• Increase in mobility on the Spanish network and,

• Greater severity of accidents with the involvement of HGV on interurban roads



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Methodology

• Expression for the regression model:

• General expression for the estimated model:

jjj vkE

M

m jvkXYjE mjm1

loglogˆˆexpˆ 0

: Accident rate

: Exposure

j

jvk

1 with...% , HGVAADTXand mj



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Methodology

• The most general expression for the predicted number of accident:

DCAVAPi

vkHGVRoad

HGVAADTYE

iiii

,,

log%log

%loglogˆexpˆ 210



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Results

• Expressions of the accident rates by road types (i) and segment (j) are calculated to be:

ij

ijij

vk

YEˆ

1639.01111.0

2491.01111.0

0103.01111.0

0638.01111.0

%2402.1ˆ

%3405.0ˆ

%4368.0ˆ

%2736.0ˆ

jjC

jjDC

jjAV

jjAP

HGVAADT

HGVAADT

HGVAADT

HGVAADT

j

j

j

j



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Results


Accident rates λh by road type

Accident rates λha by road type

[IP 95%]

Global AP AV DC C

0.264 0.104 0.150 0.209 0.290

IP (Λ h) [0; 1.001] [0; 0.396] [0; 0.567] [0; 0.804] [0; 1.098]

0.259 0.106 0.162 0.213 0.324

Differences2.13% -1.60% -7.65% -1.92% -10.37%

h

h

site new aat safety of interval prediction :

site new aat safety :

equationsby rateaccident calculated:ˆ

rateaccident observed :

/kilometres-hiclemillion ve 1per people injured with accidents are Rates

h

h

h

h

iTa

IP

vkA i

Results



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Scenarios of AADTHGV changes with and without any change to total vehicular traffic intensity (AADT):

ADDT changes

AADTHGV changes

a:-10%

b: 0% c:10%oo

-20% 20%

A: -10% Aa Ab Ac

B: -20% Ba Bb Bc

Scenarios



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Results


Freight transportation corridor: MB



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Freight transportation corridor: SB



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Freight transportation corridors

PREDICTED (Y_i) AND OBSERVED (ATi) ACCIDENTS IN MADRID- BARCELONA CORRIDOR

UPPER AND LOWER PREDICTION LIMITS (LS(Yij)-LI(Yij) ). YEAR 2002

-1

4

9

14

19

24

29

34

39

44

49

54

59

" " "

AUTOPISTA AP 2 - AP 7 AUTOVIA N 2 CONVENCIONALN 2

TIPO DE VÍA

Nº

AT

LS(Yij) Yi_02 LI(Yij) AT02



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Freight transportation corridorsPREDICTED (Y_i) AND OBSERVED (ATi) ACCIDENTS IN MADRID- BARCELONA

CORRIDORUPPER AND LOWER PREDICTION LIMITS (LS(Yij)-LI(Yij) ). YEAR 2003

-1

9

19

29

39

49

59

" " "

AUTOPISTA AP 2 - AP 7 AUTOVIA N 2 CONVENCIONALN 2

TIPO DE VÍA

Nº

AT

AT03 Yi_03 LS(Yij) LI(Yij)



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HGVs subtruction scenarios in MB corridor • Variation in vk exposure and the number of accidents in the Aa,

Ab and Ac scenarios, over the MB corridor:

Scenarios Ai, i = a,b,c over the MB corridor. Variation in vk exposure and the number of accidents Δvk%; (ΔAT %)

Road type Aa Ab Ac

AP -0.81% 0.81%

(-15.43%) (-14.79%) (-14.16%)

AV -1.05% 1.05%

(-13.58%) (-12.72%) (-11.86%)

C -2.59% 2.59%

(18.18%) (20.96%) (23.72%)

MB corridor -1.09% 1.09%

(-11.20%) (-10.22%) (-9.24%)



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HGVs subtruction scenarios in MB corridor• Variation in vk exposure and the number of accidents in the Ba,

Bb and Bc scenarios, over the MB corridor:

Scenarios Bi, i = a,b,c over the MB corridor. Variation in vk exposure and the number of accidents Δvk%; (ΔAT %)

Road type Ba Bb Bc

AP -1.61% 1.61%

(-16.38%) (-15.11%) (-13.85%)

AV -2.11% 2.11%

(-14.48%) (-12.76%) (-11.04%)

C -5.17% 5.17%

(16.83%) (22.46%) (28.06%)

MB corridor -2.18% 2.18%

(-12.15%) (-10.19%) (-8.23%)



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Results in corridor

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Results


HGVs subtruction scenarios in SB corridor• Variation in vk exposure and the number of accidents in the Aa,

Ab and Ac scenarios, over the SB corridor:

Scenarios Ai, i = a,b,c over the SB corridor. Variation in vk exposure and the number of accidents Δvk%; (ΔAT %)

Road type Aa Ab Ac

AP -0.59% 0.59%

(-9.86%) (-9.38%) (-8.89%)

AV -0.77% 0.77%

(-8.64%) (-8.27%) (-7.79%)

C -0.85% 0.85%

(6.52%) (7.26%) (7.85%)

SB corridor -0.73% 0.73%

(-4.36%) (-3.85%) (-3.34%)



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HGVs subtruction scenarios in SB corridor• Variation in vk exposure and the number of accidents in the Ba,

Bb and Bc scenarios, over the SB corridor:

Scenarios Bi, i = a,b,c over the SB corridor. Variation in vk exposure and the number of accidents Δvk%; (ΔAT %)

Road type Ba Bb Bc

AP -1.18% 1.18%

(-10.53%) (-9.56%) (-8.60%)

AV -1.55% 1.55%

(-9.04%) (-8.31%) (-7.35%)

C -1.69% 1.69%

(6.42%) (7.91%) (9.09%)

SB corridor -1.46% 1.46%

(-4.73%) (-3.71%) (-2.69%)



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Results in MB corridor by HGVs subtruction



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Results in MB corridor by HGVs subtruction



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Results in SB corridor by HGVs subtruction



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Results in SB corridor by HGVs subtruction



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CONCLUSIONS

• For all the scenarios taken into account, on the high capacity roads (AP, AV) there is a significant reduction in the total number of accidents, which varies between 16.38% for the Ba scenario of the MB corridor and 7.35% for the Bc scenario of the SB corridor.

• Likewise, on the sections of single carriageway roads (C) there are significant increases in the total number of traffic accidents, whose maximum and minimum values are:

• 28.06% for the Bc scenario on the MB corridor and 6.52% for the Aa scenario on the SB corridor.



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CONCLUSIONS

• In all cases a reduction in the total number of accidents would occur as a result in the drop in the number of heavy goods transport vehicles (%HGVs). This drop varies between 46 for the SB corridor Bc scenario and 141 for the MB corridor Aa scenario.

• In all cases, the higher the traffic intensity (AADT), as a result of the induction of other vehicular traffic, the higher the number of accidents is, due to the increase in exposure. This effect is greater on single carriageway road segments compared to high capacity roads



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CONCLUSIONS

• The model shows itself to be a useful tool for evaluating the effects of modal transfer policies between road and rail or other forms of transport.

• This type of analysis provides objective elements for evaluating policies that encourage modal shift and road safety enhancement.

Documents

Instituto Universitario de Investigación del Automóvil jueves, 14 de mayo de 2015 The influence of heavy goods vehicle traffic on accidents: the analysis