AP-R353/10

Classification of Motorcycles as a Distinct Vehicle Class

AUSTROADS RESEARCH REPORT

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Classification of Motorcycles as aDistinct Vehicle Class

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Classification of Motorcycles as a Distinct Vehicle Class First Published April 2010

Austroads Ltd. 2010

This work is copyright. Apart from any use as permitted under the Copyright Act 1968,no part may be reproduced by any process without the prior written permission of Austroads.

Classification of Motorcycles as a Distinct Vehicle Class ISBN 978-1-921709-10-4

Austroads Project No. SS1419

Austroads Publication No. APR353/10

Project Manager Arthur Bass, RTA NSW

Published by Austroads Ltd. Level 9, Robell House 287 Elizabeth Street

Sydney NSW 2000 Australia Phone: +61 2 9264 7088

Fax: +61 2 9264 1657 Email: austroads@austroads.com.au

www.austroads.com.au

Austroads believes this publication to be correct at the time of printing and does not accept responsibility for any consequences arising from the use of information herein. Readers should

rely on their own skill and judgement to apply information to particular issues.

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Classification of Motorcycles as aDistinct Vehicle Class

Sydney 2010

vAustroads profile Austroads purpose is to contribute to improved Australian and New Zealand transport outcomes by:

providing expert advice to SCOT and ATC on road and road transport issues facilitating collaboration between road agencies promoting harmonisation, consistency and uniformity in road and related operations undertaking strategic research on behalf of road agencies and communicating outcomes promoting improved and consistent practice by road agencies.

Austroads membership Austroads membership comprises the six state and two territory road transport and traffic authorities, the Commonwealth Department of Infrastructure, Transport, Regional Development and Local Government, the Australian Local Government Association, and NZ Transport Agency. Austroads is governed by a Board consisting of the chief executive officer (or an alternative senior executive officer) of each of its eleven member organisations:

Roads and Traffic Authority New South Wales Roads Corporation Victoria Department of Transport and Main Roads Queensland Main Roads Western Australia Department for Transport, Energy and Infrastructure South Australia Department of Infrastructure, Energy and Resources Tasmania Department of Planning and Infrastructure Northern Territory Department of Territory and Municipal Services Australian Capital Territory Department of Infrastructure, Transport, Regional Development and Local Government Australian Local Government Association New Zealand Transport Agency.

The success of Austroads is derived from the collaboration of member organisations and others in the road industry. It aims to be the Australasian leader in providing high quality information, advice and fostering research in the road sector.

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CONTENTS

1 INTRODUCTION ............................................................................................................ 11.1 Austroads vehicle classification system.......................................................................... 1

1.2 Metrocount and ARX classification system..................................................................... 1

2 METHODOLOGY ........................................................................................................... 22.1 Method and location ....................................................................................................... 2

2.2 Observation period ......................................................................................................... 2

2.3 Evaluation ....................................................................................................................... 2

3 DATA ANALYSIS........................................................................................................... 33.1 Comparison of Metrocount and Videocount observations .............................................. 3

3.2 Missed Motorcycles ........................................................................................................ 4

4 DISCUSSION ................................................................................................................. 74.1 Accuracy......................................................................................................................... 7

4.2 Reliability ........................................................................................................................ 7

5 FINDINGS....................................................................................................................... 85.1 Accuracy......................................................................................................................... 8

5.2 Reliability ........................................................................................................................ 8

5.3 Survey Site Variables ..................................................................................................... 8

5.4 Device Improvement....................................................................................................... 8

6 CONCLUSION................................................................................................................ 97 RECOMMENDATIONS ................................................................................................ 10APPENDIX A AUSTROADS CLASSIFICATION SYSTEM .................................... 11APPENDIX B ARX CLASSIFICATION SCHEME.................................................. 12

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FIGURESFigure 1 Survey Location City West Link Westbound..................................................... 2

Figure 2(a) Video footage ..................................................................................................... 4

Figure 2(b) Metrocount data ................................................................................................. 4

Figure 3(a) Video footage ..................................................................................................... 5

Figure 3(b) Metrocount data ................................................................................................. 5

Figure 4(a) Video footage ..................................................................................................... 5

Figure 4(b) Metrocount data ................................................................................................. 6

Figure 5(a) Video footage ..................................................................................................... 6

Figure 5(b) Metrocount data ................................................................................................. 6

TABLES

Table 1 Comparison between the ATC & Video camera ...................................................... 3

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1 INTRODUCTIONAustroads project SS1419 Classification of Motorcycles as a distinct vehicle class aims to test whether Motorcycles can be identified as a separate class of vehicle based on distance between axles.

Motorcycles are currently classified as light vehicles within the Austroads Vehicle Classification system. As a result, it is not possible to report separately on motorcycle numbers or speeds when reviewing traffic and safety performance on a length of road when using the Austroads vehicle classification system. Therefore, the Roads and Traffic Authority of NSW commissioned TCS Instruments Pty Ltd and Skyhigh Traffic Data Australia Pty Ltd to test whether motorcycles can be identified as a separate class of vehicle.

1.1 Austroads vehicle classification system The Austroads vehicle classification system provides vehicle classification by axle configuration. The classification system by axle configuration specifies that vehicles be classified into 12 classes or bins. Classes 1 and 2 are designated as Light Vehicles and the other ten classes as Heavy Vehicles (HV). In general, the axle-based classification of the 1994 system has been found stable over the years and is well accepted by road authorities and equipment manufacturers. The Austroads classification system is attached to this report as Appendix A.

The Austroads classification system is defined on vehicle classification by vehicle length and allows for overlaps between some classes. Motorcycles are currently classified as light vehicles within the Austroads vehicle classification system. As both cars and motorcycles have a short wheelbase and only two axles, the only possible separation between the two classes is the distance between the two axles.

1.2 Metrocount and ARX classification system The ARX classification system is a modification of the Austroads classification system. ARX is an abbreviation for Aust Roads X Factor. The ARX classification system was developed by Metrocount. The ARX system removes class 12, moves all other classes up by one, and inserts a motorcycle class as class 1. The ARX classification system is attached to this report as AppendixB. This system has been adopted by many Asian road authorities, based on its ability to distinguish between motorcycles and light vehicles.

Metrocount vehicle loggers are widely used in Australia to record traffic volume, vehicle classification and speed data. The loggers are attached to amphometer tubes placed on the road. The Metrocount loggers are able to classify the vehicle in accordance with the Austroads classification system. The Metrocount loggers also have the capability to classify the vehicles using other classification systems.

Classification of Motorcycles as a Distinct Vehicle Class

2 METHODOLOGY

2.1 Method and location Metrocount logger and ARX classification system were used for this survey. Amphometer tubes were placed on the road in the usual manner together with a Metrocount logging device to record vehicle classification. The survey was conducted on the City West Link (adjacent to Pretoria St), Sydney, NSW, in the west bound direction. The site was chosen as it was known to have a high motorcycle volume that would produce a robust sample. The two lanes of west bound traffic had two sets of tubes and counters installed, (one per lane). A hi-mast camera was installed adjacent to the tubes, in order to verify accuracy and reliability of amphometer measurements and classifications.

Figure 1 Survey Location City West Link Westbound

2.2 Observation periodThe surveys were carried out over a 9-day survey period from Saturday 30th May to Sunday 7th June 2009. There were gaps in the data collection due to vandalism, which might have affected the quality of data described as confidence interval (please refer to Section 3.1). The gaps are:

Sunday 31st May between 01:30 and 13:30

Monday 1st June between 00:00 and 11:30

Thursday 4th June between 00:00 and 15:30

2.3 EvaluationThe ARX classification scheme defines a motorcycle as a vehicle with a wheelbase of less than 1.7m between 2 axles. The motorcycle output from the Metrocount loggers was compared to the video camera observations. This report summarises the comparison of the two data sets as well as explaining why a difference occurred between the two data sets. This report examines the accuracy and reliability of the Metrocount loggers to identify motorcycles as a separate class. Accuracy was measured by comparing the total number of motorcycles (identified by the video audit) with the total number of motorcycles identified by the amphometer classification system. Reliability was measured by examining whether the motorcycles identified by the amphometer classification system were in fact motorcycles.

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3 DATA ANALYSIS

3.1 Comparison of Metrocount and Videocount observations This section provides a comparison of the Metrocount logger motorcycle data output and the video data output. Table 1 shows the comparison between the two data sets. The accuracy of the Metrocount loggers classifying motorcycles is shown in the right side second last column. Across the 9 days 77.5% of motorcycles were identified correctly. Of the 2493 motorcycles, 1933 were identified by the Metrocount logger. 560 motorcycles were seen on the video but not recognised as a motorcycle by the Metrocount logger. 42 vehicles were wrongly classified by the Metrocount logger as a motorcycle.

Day Date Video Count1

Recorded by ATC*

and Video2

Recorded by Video

Only3

Recorded by ATC Only4

Accuracy5(%)

Reliability6(%)

a b c d e f g=d/c h=(d-f)/d

Sat 30/05/09 187 150 37 1 80.2 99.3

Sun 31/05/09 114 93 21 2 81.6 97.9

Mon 1/06/09 298 214 84 11 71.8 94.9

Tue 2/06/09 298 252 46 0 84.6 100.0

Wed 3/06/09 305 251 54 2 82.3 99.2

Thu 4/05/09 262 182 80 0 69.5 100.0

Fri 5/06/09 458 314 144 9 68.6 97.1

Sat 6/06/09 320 269 51 9 84.1 96.7

Sun 7/06/09 251 208 43 8 82.9 96.1

9 Days 2493 1933 560 42 77.5 97.8

Table 1 Comparison between the ATC & Video camera

Notes:*ATC = Automatic Traffic Counter, or (amphometer classification system). 1. Video Count = Motorcycles identified from the video survey. 2. Recorded by ATC and Video = Motorcycles identified by both the video survey and the amphometer classification system. 3. Recorded by video only = Motorcycles identified by the video survey but not the amphometer classification system. 4. Recorded by ATC Only = Motorcycles identified by the amphometer classification system that were in fact not motorcycles. 5. Accuracy = Number of motorcycles correctly identified by the amphometer classification system divided by the total number of motorcycles. 6 Reliability = The reliability of the amphometer classification system is measured by how dependable the data is when the motorcycle is identified.

At a 95% confidence level the confidence interval is 0.7 percentage points. In other words the probability is 95% that the accuracy is between 76.8% and 78.2%.

Classification of Motorcycles as a Distinct Vehicle Class

3.2 Missed Motorcycles Attached to this report is the two database sets (mc auto.xls). In total 560 motorcycles were missed by the Metrocount loggers. The pictures below have been sampled from the video survey. The Figures 2(a) to 5(a) show the video footage of instances, where the Metrocount loggers did not record them as motorcycles. The survey time can be seen in the top left hand corner of the picture. The individual vehicle report for the same period of time is shown in Figures 2(b) to 5(b). In all of the examples shown below, the motorcycle has been misclassified as a car with a trailer except for Figure 2(b) where it was misclassified as a truck (Austroads 94 Classification 7). The Metrocount logger classified the motorcycle and the vehicle in front as one vehicle. Therefore instead of correctly classifying as two vehicles, the Metrocount logger classified the two vehicles as one vehicle. As you can see from the Metrocount individual vehicle output, this was normally a truck or a car and trailer classification.

Figure 2(a) Video footage

Figure 2(b) Metrocount data

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Classification of Motorcycles as a Distinct Vehicle Class

Figure 3(a) Video footage

Figure 3(b) Metrocount data

Figure 4(a) Video footage

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Figure 4(b) Metrocount data

Figure 5(a) Video footage

Figure 5(b) Metrocount data

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4 DISCUSSIONThe survey was not conducted at the optimal time for capturing motorcycle riders. However, the large sample size was sufficient to calculate confidence intervals. During the survey, substantial rain was experienced. Therefore the survey originally set down 5 days, was increased to 9 days to increase the sample size.

4.1 Accuracy The accuracy of the amphometer classification method is measured by how accurate it is in identifying motorcycles in the traffic mix. During the 9-day survey 2493 motorcycles were observed. 1933 motorcycles were correctly identified by the amphometer method, being 77.5% of the total motorcycles.

The survey site was a complex traffic environment with multi-lanes, heavy traffic volume and a broad range of vehicle types. This type of traffic environment is a major factor in the low motorcycle classification accuracy experienced during the survey. Nevertheless, this location is typical of where such information is required.

If the survey was conducted at a simpler location with lower volumes and larger headways between vehicles a more accurate identification of motorcycles could be expected.

Therefore both the classification scheme and survey instrument need to be expanded in order to justify confidence in using the vehicle classification scheme that separates motorcycles from light vehicles. It is understood that as the only variable measurement to separate motorcycles from light vehicles is the axle distance, no scheme will achieve a perfect result. However, the subject survey has concluded that the Metrocount loggers missed 22.5% of all motorcycles. This error rate is considered too high.

The missed motorcycles were standard motorcycles. The majority of the misclassification was caused by joining to vehicles together. For example a car and a motorcycle were joined to be classified as a car and trailer or a truck.

4.2 Reliability The reliability of the amphometer classification method is measured by how dependable the data is when the motorcycle is identified. Of the 1975 motorcycles identified by the amphometer classification method, 42 were in fact not motorcycles. Therefore 97.9% of the motorcycles identified by the amphometer classification system were motorcycles, and 2.1% were not motorcycles.

There was no pattern to the small 2.1% error and therefore could be attributed to random errors experienced using amphometer tubes to classify vehicle.

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5 FINDINGS

5.1 Accuracy Based on the comparing Metrocount logger data and video data Metrocount loggers recorded 77.5% of the motorcycles correctly. At a 95% confidence level the confidence interval was 0.7%. Therefore based on the sample size the accuracy level is between 76.8% and 78.2% with a 95% level of confidence.

The accuracy level was very stable over all 9 days. The lowest accuracy level was 68.6% and the highest was 84.1%. The most common error was the misclassifying of motorcycles because the classification system joined the motorcycle to the vehicle ahead (or behind) of it. The misclassification of motorcycles in the study was caused by short headways between vehicles. Further examination of the algorithm used to classify the vehicles would establish the exact cause.

5.2 Reliability Of the 1975 motorcycles identified by the amphometer classification method, 42 were not motorcycles. Therefore 97.9% of the motorcycles identified by the amphometer classification method were motorcycles, and 2.1% were not motorcycles.

Therefore based on the sample size the reliability level is between 97.2% and 98.6% with a 95% level of confidence.

5.3 Survey Site Variables The survey was carried out on a two lane (one direction) section of road in inner Sydney. The vehicle volumes at this site were high and the headway between vehicles was often quite short. The accuracy and reliability of separating motorcycles from other vehicle classifications will vary according to the traffic volumes and the level of saturation. The speed data should not be affected by the misclassification of the motorcycles.

5.4 Device Improvement Based on the analysis of the survey data it is recommended that a copy of the report be presented to Microcom (Metrocount owners and developers). As a common problem in classifying motorcycles is the headway allowance between vehicles, a modification to the classification algorithm may be possible.

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6 CONCLUSIONAustroads project SS1419 Classification of Motorcycles as a distinct vehicle class aims to test whether Motorcycles can be identified as a separate class of vehicle based on distance between axles. It was found that motorcycles could be identified as a separate class of vehicle with high level (between 97.2% and 98.6%) reliability. However, the ARX classification is unsuitable for accurately identifying motorcycles in complex traffic circumstances.

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7 RECOMMENDATIONS It is recommended that the same survey be carried out across a number of different road scenarios. These scenarios should vary by vehicle volume, lane configuration and vehicle headway (congestion).

It is also recommended to conduct further research on other available classification systems nationally and/or internationally for identifying motorcycles, given the limitation in the current ARX classification system.

Classification of Motorcycles as a Distinct Vehicle Class

APPENDIX A AUSTROADS CLASSIFICATION SYSTEM

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APPENDIX B ARX CLASSIFICATION SCHEME

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INFORMATION RETRIEVAL

Austroads 2010, Classification of Motorcycles as a Distinct Vehicle Class,Sydney, A4, 20pp, AP-R353/10

Key Words :

Austroads classification system, motorcycle, motorcycle speeding, axle configuration, ARX classification, vehicle length, light vehicles, Austroads Vehicle Classification system, complex traffic circumstances, separate class of vehicle

Abstract

The Austroads classification system provides vehicle classification by axle configuration or by vehicle length. The classification system by axle configuration specifies that vehicles be classified into 12 classes or bins. Classes 1 and 2 are designated as Light Vehicles and the other ten classes as Heavy Vehicles. This system is less defined on vehicle classification by vehicle length and allows for overlaps between some classes. Motorcycles are currently classified as light vehicles within the Austroads Vehicle Classification system.

This research was instigated to study the feasibility to update the classification system and based on ongoing issues with motorcycle safety such as road toll, increasing motorcycle use, difficulty in accurately assessing and monitoring extent of motorcycle use and speeding on key routes (including effectiveness of safety programs).

This project aimed to test whether motorcycles can be identified as a separate class of vehicle based on distance between axles. The study included the production of a report based on in-depth investigations of a number of motorcycles and light vehicles passing a section of a road in metropolitan area. The report documented examples of the metropolitan area and included photographs from the surveillance camera as evidence of accurate representation of two different distinct types of vehicle (motorcycles and light vehicles).

This study revealed that motorcycles could be identified as a separate class of vehicle with a high level of reliability. However, the classification system is unsuitable for accurately identifying motorcycles in complex traffic circumstances.

AP-R353/10 Classification of Motorcycles as a Distinct Vehicle ClassAustroads profileCONTENTSFIGURESTABLES1 INTRODUCTION1.1 Austroads vehicle classification system1.2 Metrocount and ARX classification system

2 METHODOLOGY2.1 Method and location2.2 Observation period2.3 Evaluation

3 DATA ANALYSIS3.1 Comparison of Metrocount and Videocount observations3.2 Missed Motorcycles

4 DISCUSSION4.1 Accuracy4.2 Reliability

5 FINDINGS5.1 Accuracy5.2 Reliability5.3 Survey Site Variables5.4 Device Improvement

6 CONCLUSION7 RECOMMENDATIONSAPPENDIX A AUSTROADS CLASSIFICATION SYSTEMAPPENDIX B ARX CLASSIFICATION SCHEMEINFORMATION RETRIEVAL