Digital Tachograph Research Articles

Using vehicle data as a surrogate for highway accident data

Many studies have tried to use the surrogate safety measures (SSM) estimated from the microscopic traffic simulations. However, it is difficult to adopt these developed SSM to reflect real-world traffic conditions when the developed network in the simulation is not calibrated and validated accordingly. This paper proposed a method to develop the pattern-based surrogate safety measure (PSSM) using individual vehicle trajectory data. The PSSM can be estimated based on the pattern of hazardous driving behaviour (HDB). Using digital tacho graph data collected from the commercial vehicles, HDB patterns were obtained. Various PSSMs were developed and validated with the observed crash data using Random Forest. Then, the surrogate safety performance function was estimated based on the frequency of HDB. To enhance model performance, machine learning and data mining techniques were applied. The results show that sudden deceleration, sudden lane change, sudden overtaking and sudden U-turn are related to traffic crashes during HDB. The results also show that high potential for safety improvement was identified in the road section linking the urban and suburban areas. The findings from this study can provide new approach to adopt real-time individual vehicle trajectory data to evaluate safety performance of network levels.

Analysis on Accuracy of GPS installed in Digital Tachograph of Commercial vehicles

Analysis on Accuracy of GPS installed in Digital Tachograph of Commercial vehicles

Analysis of commercial truck drivers’ potentially dangerous driving behaviors based on 11-month digital tachograph data and multilevel modeling approach

This study analyzed the potentially dangerous driving behaviors of commercial truck drivers from both macro and micro perspectives. The analysis was based on digital tachograph data collected over an 11-month period and comprising 4373 trips made by 70 truck drivers. First, different types of truck drivers were identified using principal component analysis (PCA) and a density-based spatial clustering of applications with noise (DBSCAN) at the macro level. Then, a multilevel model was built to extract the variation properties of speeding behavior at the micro level. Results showed that 40% of the truck drivers tended to drive in a substantially dangerous way and the explained variance proportion of potentially extremely dangerous truck drivers (79.76%) was distinctly higher than that of other types of truck drivers (14.70%˜34.17%). This paper presents a systematic approach to extracting and examining information from a big data source of digital tachograph data. The derived findings make valuable contributions to the development of safety education programs, regulations, and proactive road safety countermeasures and management.

Digital Recording Devices is Element of Safety of the Road Transport

Abstract The duty of applying recorders in the road transport was implemented in states of the European Union on regulations (EWG) no. 3820 / 85 on harmonizations of some social welfare legislation referring to the transport, which was changing with regulation (EWG) no. 3821/85 on recorders applied in the road transport. The duty of implementation of the digital tachograph is also considered in the context of improving road safety. Through the analysis of the records of the registering devices can be defined in each specific case of speeding by more than the allowable value in the area. Technical requirements for your device recorded in the resolution, which defines the main parameters, are measured, among things other, the traversed path length of the car, speed, time driving, other periods of work, politeness of the driver and the correct operation of the check authorized for those authorities. At present led Regulation (EU) No 165/2014 of European Parliament establishing requirements concerning structure, checking, installation, use and repairs of tachographs and their building blocks is implementing the second generation of the digital tachographs connected with the device GNSS (Global Navigation Satellite System). Organizing the early detection from a distance is showing data officers from the digital tachograph and information concerning mass and mass falling on the wasp of the entire team of vehicles. Experience in work, economic pressures and competition in transport has led the drivers through a transport company in the event noncompliance, and in particular, in relation to the driving time and breaks. This article contains responsibilities after part rest on the drivers of vehicles takes the issues of system security and optimum performance of recording devices.

Use of Cryptography Principles in Digital Registration Devices

Abstract Cryptography is a field of science necessary to solve problems with encryption of classified messages. The security of electronic information is an integral part of the digital tachography system. From year to year, there is a noticeable increase in electronic data logging systems in many aspects of life. The control measures created for the purpose of performing roadside checks are not sufficient to detect all violations in the recording equipment. Many violations that have occurred during the use of the vehicle are stored in the device’s memory. The article describes the basic mathematical rules illuminating cryptography. The hazards to which the motion sensor installed in the vehicle may be exposed are described. Breaking safety in transport systems may lead to incorrect results of inspections carried out while the vehicle is stopped by authorized services. The article also provides information on the authorities responsible for issuing cards for digital tachographs. Nowadays, documents are increasingly issued with the use of a digital signature. The digital signature of its origin is based on the principles of cryptography. The security key seems to be complicated for the average user. The article discusses the topic of tachograph construction, in particular the schematic responsible for information encryption.

Analysis of Bus Drivers’ Working Environment and Accidents by Route-Bus Categories : Using Digital TachoGraph Data

Analysis of Bus Drivers’ Working Environment and Accidents by Route-Bus Categories : Using Digital TachoGraph Data

Mitigating Greenhouse Gas Emissions from Passenger Transport Sector in Megacities: A case of Ho Chi Minh City

This research aims to propose mitigation measures to reduce the greenhouse gas emissions from passenger transport sector for Ho Chi Minh City, Vietnam. The Extended Snapshot tool is used to calculate the socio-economic development indicators and transport demand for base year 2013, and then estimate the transport demand based on the socio-economic development in target year 2030. In the base year 2013, the air pollutants (NO2, CO, PM10, Pb, etc.) are monitored at the six main stations to analyse the air pollution situation due to transportation activities. In the target year 2030, two scenarios are developed with the same socio-economic development and transport demand projections. Business-as-usual scenario does not consider the mitigation measures to reduce the greenhouse gas emissions while the countermeasure scenario does. Among the 940.5 kt CO2-eq reduction (15.0 % of emissions from passenger transport in 2030’s business-as-usual scenario), the promotion of energy-efficient vehicles helps to reduce 631.0 kt CO2-eq, followed by 146.7 kt CO2-eq reduction by modal shift from motorbike to mass rapid transports. The shift from fuel-motorbike to electric motorbike helps to reduce 83.2 kt CO2-eq, together with 41.4 kt CO2-eq reduction by shifting from conventional bus to compressed natural gas bus. The promotion of eco-driving with digital tachograph in passenger car helps to reduce 38.2 kt CO2-eq. As the co-benefit, the air pollution due to transportation activities might be reduced thanks to the implementation of mitigation measures to reduce the greenhouse gas emissions.

디지털운행기록을 활용한 우천시 주요 운전행동과 사고와의 상관성 분석 : 서울시 택시 운행자료를 중심으로

교통안전 증진을 위한 지속적인 노력으로 국내 교통사고수는 감소하는 추세를 보이고 있다. 하지만 여전히 OECD 국가 평균 대비 높은 사망자를 발생시키고 있으며, 이를 해결하기 위해 지속적인 연구가 수행되고 있다. 특히 최근 데이터 수집기술의 발달로 운전자의 운전행동에 대한 연구가 활발히 수행이 되고 있다. 운전자의 운전행동은 주행하고 있는 도로의 환경, 기상상황 등에 큰 영향을 받기 때문에 주변환경을 고려하여 운전행동을 분석할 필요성이 있으며, 이에 본 연구에서는 서울지역 택시의 디지털 운행기록계로부터 수집된 2013년 9월 중 10일간의 운행기록자료를 활용하여 기상상황에 따른 운전 행동을 분석하였다. 기상청 자료를 이용하여 운행기록일별로 우천시와 맑음 상황을 구분하였고, 클러스터링 분석을 활용하여 총 12가지의 대표운전행동을 각각의 기상상황에 따라 비교 분석하였다. 또한, 과거 사고와의 공간분석을 통해 우천시 사고가 운전행동과 높은 양의 상관관계를 가짐을 보이고, 우천시 사고 다발지점에서의 주요 운전행동이 급제동과 급출발 행동이었음을 도출하였다. 본 연구는 대용량의 운행기록자료를 이용하여 기상상황에 따른 운전행동의 차이를 도출하고 운전행동과 교통사고 간의 상관관계를 증명하였다는 점에서 의의가 있다. 추후 분석 데이터양과 기간을 늘린다면 보다 일반화된 각 기상상황에 따른 운전행동과 사고 간의 관계에 관한 연구가 가능하다. 이를 통해 기상상황에 따른 사고 위험 행동들을 도출하여 선제적인 교통안전 대책 수립 및 안전운행정보 고도화가 가능할 것으로 판단된다.

Decisions on truck parking place and time on expressways: an analysis using digital tachograph data

With the objective of deriving useful insights into measures against traffic congestion at service areas (SAs) and parking areas (PAs) on expressways and ensuring efficient use of SAs/PAs, this study investigated the decisions on where a truck is parked (i.e., choice of an SA or a PA), how long it is parked (i.e., parking time), and their influential factors. To this end, this study used the trajectory data of 1600 trucks recorded in 6-min intervals by in-vehicle digital tachographs on the Sanyo and Chugoku Expressways in Japan from October 2013 to March 2014. First, the aspect of repeated choice of each truck (i.e., habitual behavior) toward a specific SA/PA was clarified. Next, a multilevel discrete–continuous model (Type II Tobit model) was developed to reveal the factors affecting the above decisions. The modeling results confirmed the existence of habitual behavior and showed that trucks were more likely to be parked a longer time at an SA/PA when it is closer to the destination. It appears that truck drivers may adjust their time at the SA/PA close to the destination to comply with the arrival time, which is often predetermined by the owner of the transported goods. Furthermore, the availability of restaurants and shops, and the number of parking spaces available for trucks and trailers are important determinants of parking time, whereas the existence of a convenience store is important to the choice of the SA/PA. Parking experience has an extremely strong positive effect on the parking choice and use. Moreover, increasing the number of parking lots may induce its longer use.

Speed Consistency in the Smart Tachograph.

In the transportation sector, safety risks can be significantly reduced by monitoring the behaviour of drivers and by discouraging possible misconducts that entail fatigue and can increase the possibility of accidents. The Smart Tachograph (ST), the new revision of the Digital Tachograph (DT), has been designed with this purpose: to verify that speed limits and compulsory rest periods are respected by drivers. In order to operate properly, the ST periodically checks the consistency of data from different sensors, which can be potentially manipulated to avoid the monitoring of the driver behaviour. In this respect, the ST regulation specifies a test procedure to detect motion conflicts originating from inconsistencies between Global Navigation Satellite System (GNSS) and odometry data. This paper provides an experimental evaluation of the speed verification procedure specified by the ST regulation. Several hours of data were collected using three vehicles and considering light urban and highway environments. The vehicles were equipped with an On-Board Diagnostics (OBD) data reader and a GPS/Galileo receiver. The tests prescribed by the regulation were implemented with specific focus on synchronization aspects. The experimental analysis also considered aspects such as the impact of tunnels and the presence of data gaps. The analysis shows that the metrics selected for the tests are resilient to data gaps, latencies between GNSS and odometry data and simplistic manipulations such as data scaling. The new ST forces an attacker to falsify data from both sensors at the same time and in a coherent way. This makes more difficult the implementation of frauds in comparison to the current version of the DT.

차량 운행기록정보와 통행배정 모형을 이용한 교차로 영향권의 공간적 패턴에 관한 연구

차량 운행기록정보와 통행배정 모형을 이용한 교차로 영향권의 공간적 패턴에 관한 연구

Regulated applications for the road transportation infrastructure: The case study of the smart tachograph in the European Union

The Digital Tachograph (DT) is an equipment intended for installation in road commercial vehicles to display, record, print, store and output automatically or semi-automatically details of the vehicle movement and details of certain periods of activity of the drivers. It is used in the European Union to check the driving times of drivers and enforce the legislation on social rules (rest period, driving time limits), in relation with the road safety objective of reducing the number of accidents and fatalities in the EU. Each driver is equipped with a personal card (s)he has to introduce in the tachograph to be personally identified. The DT is a very important application in Europe in the road transportation sector as it is obligatory to install a DT in commercial vehicles having a mass of more than 3,5 tonnes (in goods transport) and carrying more than 9 persons including the driver (in passenger transport). Thus this regulation impacts millions of vehicles. The legal and technical framework has been recently revised according to Council Regulation (EU) No. 165/2014, which introduced support for wireless communication, positioning by Global Positioning Satellite Systems (GNSS) and new security measures for the DT system. This led to the revision of the existing DT technical specifications to a new set of specifications discussed with law enforcers, manufacturers and service providers. The new technical specifications are hundreds of pages long and they cover many different technical aspects. The goal of this paper is to describe the key elements of the new design of the smart tachograph and how it addresses the limitations of the existing DT.

Analysis of Risk Driver Discrimination Considering Driver's Behavior Based on Digital TachoGraph(DTG)

Analysis of Risk Driver Discrimination Considering Driver's Behavior Based on Digital TachoGraph(DTG)

CAN network in real time on board systems

The network system of data exchange between the various components is an inherent element of every car. Because of the specific and different requirements for data transfer between specific devices, currently used communication protocols have different properties of performance, security, and degree of determinism. The paper presents the increasing complexity of the data exchange system based on the example of the latest requirements for digital tachographs. The article describes also the data transmission initialization methods in the context of network data exchange organization. The hybrid use of time triggering and event triggering mechanisms has been presented in relation to the operation of the CAN network under increased real-time conditions requirements implemented as TTCAN (time triggered CAN).

A basis of spatial big data analysis with map-matching system

The data collection of vehicle trajectories becomes the basis of big data analysis and prediction for a variety of purposes, such as vehicle navigation and movement analysis. A digital tachograph (DTG) is pre-installed on most commercial vehicles in South Korea and is highly valuable for analyzing eco-driving metrics such as safe driving and fuel consumption estimates. In order to properly analyze a large amount of GPS location information, it is necessary to find the exact match of the location data in space to the link in the digital road network data. We previously discovered the road information of the GPS coordinates using the commonly utilized map-matching technique. However, such a navigation map-matching technique requires a lot of supplementary corrections in order to rapidly and accurately navigate a large amount of data. In this study, we applied enhanced map-matching logics with Geohash as spatial index, long link vertex division, speed filtering, azimuth filtering, and map-matching weight logics. Also, we established and implemented a distributed analysis environment for the big data map-matching with HBase (a Hadoop-based NoSQL DB). This paper shows a spatial analysis system using the map-matching logics on the Hadoop MapReduce mechanism, which improved its performance.

화물차 DTG 데이터를 활용한 고속도로 졸음운전 위험구간 분석

화물차 DTG 데이터를 활용한 고속도로 졸음운전 위험구간 분석

Big data pre-processing methods with vehicle driving data using MapReduce techniques

A huge amount of sensing data are generated by a large number of pervasive IoT devices. In order to find meaningful information from the big data, it is essential to perform pre-processing, in which many outlier data points need to be removed, because they deteriorate as time passes. Although pre-processing is essential in the big data field, there has been a significant lack of research works with case studies. In this paper, big data pre-processing methods are investigated and proposed. To evaluate the pre-processing methods for accurate analysis, we used a collection of digital tachograph (DTG) data. We obtained DTG sensing data of 6198 driving vehicles over a year. We studied five kinds of pre-processing methods: filtering ranges, excluding meaningless values, comparing filters from variables, applying statistical techniques, and finding driving patterns. In addition, we developed a MapReduce program using a Hadoop ecosystem and deployed big data to perform the pre-processing analysis. Through the pre-processing steps, we confirmed that the proportion of DTG sensing data points including any errors was up to 27.09%. Compared to the traditional brute-force way to detect, ours had 71.1% additional detection effect. In addition, we confirmed that outlier data points, which are difficult to detect through simple range error pre-processing, could be well detected.

Determining locations of charging stations for electric taxis using taxi operation data

ABSTRACTThe adequate provision of charging infrastructure is critical for the effective deployment of electric taxis. This study attempts to locate charging stations for electric taxis reflecting real-world taxi travel patterns identified from taxis equipped with digital tachographs. Data for one week are processed in order to estimate their charge demand. The estimated temporal distribution of charge demand indicates that it varies day-by-day and hour-by-hour. The maximum set covering model is applied for determining the locations of charging stations. The results show that the pre-specified service distance and service coverage rate (defined by the proportion of total demand served) can be critical factors for determining the number and location of charging stations. These factors should be carefully specified by considering the tradeoff between operational efficiency of charging facilities and user convenience.

Digital tachograph in traffic accident investigations

The author provides an overview of how digital tachographs can be used in traffic accident scene investigtions.

Critical aggressive acceleration values and models for fuel consumption when starting and driving a passenger car running on LPG

ABSTRACTThe models based on vehicle speed have been used to estimate fuel consumption and CO2 emissions. However, these models could not properly estimate the change in fuel consumption and CO2 emissions as the speed changes. As for the alternative method, people try to consider using acceleration instead of speed. Although acceleration has been seriously considered, determining critical aggressive acceleration value in relation to fuel consumption and CO2 emissions is difficult to find. In this study, evaluation models of fuel consumption were developed using instantaneous acceleration, and we defined the critical aggressive acceleration values for different states of the vehicle from the viewpoints of fuel consumption and emissions. We used a mid-sized Liquefied Petroleum Gas (LPG) passenger car and obtained instantaneous data from a digital tachograph installed in the car while it accelerates. We developed two fuel consumption models and found critical aggressive accelerations, respectively: a model of starting vehicle that measures range of speed required to overcome the inertia during acceleration from stop state, and the other model for the driving state. We used Classification and Regression Tree (CART) analysis to find the critical aggressive accelerations at which the increments of fuel consumption change abruptly. As a result, the critical aggressive accelerations causing abrupt change in the increments of fuel consumption were found to be 2.598 m/s2 for the starting of vehicles and 1.4705 m/s2 when driving them. We also found that the increments of fuel consumption can be explained through quadratic and exponential functions with instantaneous acceleration.