The Influence of Telematics Device on Driving Behaviour of - - PowerPoint PPT Presentation

The Influence of Telematics Device on Driving Behaviour of Commercial Vehicles Across Long and Short Haul Drivers

Atilze Digital Mohd Azman Ismail

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Abstract

This paper reviews the effect of Advanced Driver Assistance System (ADAS) on driver’s behaviour who drive commercial vehicles for both the long haul group and short haul group. It is known that for the drivers that drives long distance, the exposure to negligent driving behaviour such as sudden braking and tendency of speeding are higher compared to the short distanced drivers due to reduced focus and fatigue ADAS was used as an instrument to measure various data points that makes up the driving

• behaviour. ADAS helps in improving the driving style by alerting the drivers whenever a

dangerous driving behaviour is detected thus helping the driver to correct the behaviour The driver’s behaviour is measured using the Malaysia Driver Score (MDS) which was published by MIROS

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Introduction

It is commercially known that Advanced Driver Assistance System(ADAS) is proven to significantly reduce the number of road accidents in general. A recent study done by MIROS also establishes that driver behaviour of passenger vehicles fitted with ADAS shows greater improvement than those without the device, in terms of lower number of logged incidents. Road accidents may result from human factors, environment and/or design of roads and vehicles factors. However, human factor often plays the greatest role in causing road accidents Human factor can be measured using the driver score model which will help to determine risk profile of drivers -whether the driver falls in the good score or a bad score band according to their driving behaviour Research objective of this paper is to prove differences in driver score between long haul driver and short haul driver group. Scope of study for this analysis are three logistics companies based in Klang Valley which trips covers both long haul and short haul travels across Peninsular Malaysia.

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Actual Losses

533,875

road accidents 2017

RM5.38 bil

motor insurance claims paid 2017 6,740

deaths 2017

28 Million Registered Vehicles in 2017

Passenger Cars

13,288,797 1,959,364 12,933,042

Commercial Vehicles/Others

Motorcycles An Average of 2 cars + 2 Motorcycles per Household

Source: Traffic Investigation and Enforcement Department, Bukit Aman Source: PIAM

Malaysian Road Accident Statistics

Road Accidents Risk Factors

VEHICLE ROAD CONDITIONS HUMAN BEHAVIOUR Statistics Book 2017 Edition – Jabatan Keselamatan Jalan Raya (JKJR) quoting MIROS statistics

What is ADAS?

DRIVER BEHAVIOUR & SAFETY

ROAD SAFETY ROAD SAFETY

Why we need Malaysia Driver Score?

VEHICLE SAFETY

To address the missing gap

New Car Assessment Program for Southeast Asian Countries (ASEAN NCAP) is a Automobile Safety Rating Program Star-rating based on the level of safety compliance by bus

• perators

International Road Assessment Programme Malaysia Driver Score – to address risk associated with driver’s behaviour on the road

A score between 1-100 that accesses a driver’s likelihood of getting into a collision Caters to two different segments:

• Private Passenger Vehicles
• Commercial Vehicles

Speeding Forward Collision Warning (FCW) Hard Braking Lane Departure Warning (LDW) Hard Cornering Speeding (SPD) Encompasses 3 predictive driving behaviour parameters (based on MIROS’s study) normalized against mileage travelled (km) that will help determine the different sets of risk profile of drivers

What is Malaysia Driver Score, MDS?

For the purpose of this study, independent t-test was used to ascertain the differences in driver score means for the two groups of drivers This research study uses secondary data as a method of analysis. Data set was obtained for one month period for trips and events for each vehicle In total there were 33 drivers who did trips for the whole month of February 2019 from three logistics

• companies. These drivers were categorized into two groups; long haul and short haul drivers

Driver Score Atilze Digital Sdn Bhd

Methodology

Methodology

Independent Sample t-test

The independent sample t-test compares the means of two independent groups which in this study is long-haul and short-haul driver group in order to determine whether there is statistical evidence that the associated population mean are significantly different. Below are the hypotheses for independent sample t-test used in this study:

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Methodology

H0 = There is no difference in mean driver score between long haul and short haul drivers H1 = There is difference in mean driver score between long haul and short haul driver

Descriptive statistics for Trip Distance

149522 56412 Long Short

Total Distance Travelled (km)

Total 15 18 Long Short

Total Vehicles by Category

Total 5837 18 16348 5034 9968 3134 Long Short

Minimum, Maximum and Average Values for Distance Travelled (km) by Category

Min of Trip Distance Max of Trip Distance Average of Trip Distance

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Sample size description

64.8 18.12 99.09 93.51 85.17 79.76 Long Short

Minimum, Maximum and Average Values for Driving Score (%) by Category

Min of Total Score Max of Total Score Average of Total Score 20 40 60 80 100 120

Driving Score Distribution

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Descriptive statistics for Driver Score

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The event triggered by the two categories of drivers. Lane Departure Warning (LDW) was the highest event triggered with 89% of the all event triggered, followed by Forward Collision Warning (FCW) with 7% and the lowest event triggered was Speed (SPD) which accounted for 5%.

Results

The average distance travelled for those two groups of driver was 6240.44 km. There was a noticeable gap in between the minimum distance travelled accounting for only 17.93km while the maximum distance travelled was a whopping 16347.56 km To explain and support the argument for the differences in driving score between long and short haul drivers, independent t-test was used. Independent t-test was analysed using r software and below is the result: Two Sample t-test t = 1.0412, df = 22.861, p-value = 0.3087 From the analysis, we can see that the independent sample t-test analysis showed that p-value is 0.3087 and we accept H null. Hence, we can conclude that there is no difference in driver score mean between long haul and short haul drivers

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Results

There are no noticeable difference of MDS score between long haul and short haul group. ADAS is known to help to reduce the risk of the two haul group in dangerous driving, thus reducing the chance of negligent driving This finding shows that the long-haul driving group, especially, has significant benefit in using ADAS as it lowers their risk factors to the same level as short haul drivers. ADAS is known to help reduce the risk of the two haul group in dangerous driving, thus reducing the chance of negligent driving. The ADAS alarm & notification system has helped to notify the driver when dangerous or negligent driving behaviour is observed, and the drivers can use it to retroactively correct their driving style within the trip.

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Discussion & Conclusion

Source: BNM

Future Usage Based Insurance, UBI

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References