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This study developed an onboard system to measure the on-road driving pattern for a motorcycle driving cycle in Khon Kaen city, Thailand. The developed system, validated with high accuracy results, could measure and record a driving pattern, i.e. a speed profile of a driving motorcycle. The selected motorcycle was driven along selected routes in Kh...
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... Nevertheless, attempts to test in real operating conditions for Lcategory vehicles have been and are still being made. Due to problems with adapting PEMS equipment for RDE tests of two-wheeled vehicles, numerous researchers have focused on conducting research in real operating conditions and creating representative tests on their basis, which were then reproduced in laboratory stations [37,46,[51][52][53][54][55][56][57][58]. ...
... The analysis of the research methods and results of these works reveals very large differences in terms of cycles, e.g., research routes, equipment used and results obtained ( Figure 10). [37,46,[51][52][53][54][55][56][57][58]. As a result of these studies, research cycles have been developed which are more representative than standardized cycles, but usually reflect the operating conditions for selected cities and agglomerations [37,39,46,48,54,56]. ...
... Figure 10. Analysis of methods and research results included in the mentioned research works [46,51,52,54,55,[57][58][59]. ...
Two-wheeled vehicles, due to their population, constitute a significant share of road vehicles in Europe. Therefore, this article presents an overview and analysis of the applicable legal regulations regarding two-wheeled vehicle engines in terms of toxic exhaust emission tests. For the correct interpretation of emission standards, the authors of this work made the necessary analysis of the categorization of two-wheeled vehicles based on Polish law and the criteria of European regulations. The presented analysis concerns not only the current regulations, but also their development trends over the years. These considerations are supplemented with a literature review, which includes the problems of the ecology, energy consumption and construction of the considered group of vehicles. The work presented in this article also concerns the assessment of the conditions for conducting tests on objects belonging to category L in laboratory conditions on chassis dynamometers. On this basis, considerations were made to evaluate the currently applicable WMTC (World Motorcycle Test Cycle) test by comparing it with the actual operation of two-wheeled vehicles. This resulted in the formulation of conclusions regarding the need to introduce procedures for testing pollutant emissions in road conditions in the approval process.
... e accuracy of GPS depends on the orbit of satellites [32]. GPS may yield a low accuracy because of unclear weather or tall buildings [33][34][35]. Measuring the speed of a motorcycle riding at a low speed may result in a measurement error of approximately 1 m/s. In contrast, a Hall effect sensor uses a magnet as an inductor to generate a pulse signal when a magnetic pole passes through a sensor installed on the wheel axis of a motorcycle. is makes it possible to calculate the speed of a motorcycle's movement every second. ...
... It could measure a distance within 4 m by capturing 400 samples per second. e Hall effect sensor was improved from that of previous studies [33,35] to measure the instant speed per second of the test motorcycle with higher accuracy. Twenty-two steel pins were installed on the front wheel of the test motorcycle with a circumference of 1.73 m. e minimum speed that could be measured was 0.28 km/h. ...
In developing countries, motorcycle riders typically perform lane filtering at signalized urban intersections. This study aims to determine the factors that affect the lateral clearance of motorcycle riders as they travel between two lanes of mixed traffic at signalized urban intersections in developing countries. In this study, an onboard measurement device was developed to measure the lane-filtering behavior of motorcycle riders. It was installed on a test motorcycle to continuously record the lateral clearance, riding behavior, and surrounding traffic conditions. Thirty participants rode the test motorcycle through a signalized urban intersection. Multilevel linear regression was applied to analyze the relationship between lateral clearance and relevant variables at a significance level of 0.05. The instant speed and side of the filtering motorcycle, condition of the lateral vehicle, type of lateral vehicle, and riding frequency of the motorcycle rider significantly influenced the lateral clearance. The findings of this study can contribute to filtering lane management, connected autonomous vehicles, and microscopic traffic simulations for motorcycles traveling in mixed traffic at signalized urban intersections.
... The real-world driving cycle data were collected using three methods: (1) the chasing vehicle technique-measuring the speed of the targeted vehicle, e.g., [13,14], (2) data collection using a global positioning system (GPS), e.g., [8,[15][16][17][18][19][20], and (3) onboard measurements by installing a measuring device on a test vehicle, e.g., [21][22][23][24][25][26]. However, it was difficult for the driver to carry out the chasing in the circumstance of mixed and congested traffic. ...
... This study developed an onboard measurement device based on the authors' previous studies [24,26,29,33], to collect the real-world speed profile and fuel consumption. It was installed on the test motorcycle so that it could collect real-world data, including the speed profile and fuel consumption, while riding on a road network in real time. ...
... This study used the micro-trip method to construct the driving cycle as opposed to the trip segment method, which is appropriate for congested road networks, because the participating riders were able to ride the test motorcycle at their desired speed along the selected uncongested route. The driving cycles were constructed using the algorithm from the authors' previous studies [24,26]. The nine targeted driving parameters were firstly identified, as shown in Table 2. ...
Climate change is a major issue all around the world. The transportation industry currently accounts for most CO2 emissions. The goal of this research is to develop a real-world eco-driving cycle for internal combustion engine motorcycles that can reduce fuel consumption and CO2 emissions. This study developed onboard measuring equipment to measure the speed profile and fuel consumption of a motorcycle driving in real time. A total of 78 motorcycle riders rode a test motorcycle with the onboard equipment along a road network to collect real-world data. All of the collected real-world data were analyzed by cluster analysis based on fuel consumption (km/L) to divide riders into two groups, high-fuel-consumption riders and low-fuel-consumption riders. The collected real-world data of the low-fuel-consumption riders were used to develop a real-world eco-driving cycle, whereas the collected real-world data from the high-fuel-consumption riders were used to develop a real-world non-eco-driving cycle. The CO2 emissions were calculated by the speed profiles of the developed driving cycles. The findings reveal that the real-world eco-driving cycle provided a fuel consumption rate 39.3% lower than the real-world non-eco-driving cycle. In addition, the real-world eco-driving cycle provided a CO2 emission rate 17.4% lower than the real-world non-eco-driving cycle. The application of the developed real-world eco-driving cycle for motorcycles is proposed.
... Another challenge is weaving, creating turbulence, impacting progress, and resulting in low capacity and creating bottlenecks in road systems [96]. The leading cause of death in road traffic accidents [164] is the increased injuries sustained in road crashes [8,12,26,42,66,74,75,118,152,154,[164][165][166][167][168][169][170][171][172]. Previous studies indicated that approximately one-quarter of mortalities from traffic accidents involved motorcycle drivers [33,47,51,159,173,174]. ...
... Furthermore, examining how the spatial and temporal dimensions impact the overall results acquired in some studies might be significant [160], and the findings should be treated with absolute care [49,84]. Other recommendations included comparable results [131,171]. ...
With the continuous emergence of new technologies and the adaptation of smart systems in transportation, motorcyclist driving behaviour plays an important role in the transition towards intelligent transportation systems (ITS). Studying motorcyclist driving behaviour requires accurate models with accurate and complete datasets for better road safety and traffic management. As accuracy is needed in modelling, motorcyclist driving behaviour analyses can be performed using sensors that collect driving behaviour characteristics during real-time experiments. This review article systematically investigates the literature on motorcyclist driving behaviour to present many findings related to the issues, problems, challenges, and research gaps that have existed over the last 10 years (2011–2021). A number of digital databases (i.e., IEEE Xplore®, ScienceDirect, Scopus, and Web of Science) were searched and explored to collect reliable peer-reviewed articles. Out of the 2214 collected articles, only 174 articles formed the final set of articles used in the analysis of the motorcyclist research area. The filtration process consisted of two stages that were implemented on the collected articles. Inclusion criteria were the core of the first stage of the filtration process keeping articles only if they were a study or review written in English or were articles that mainly incorporated the driving style of motorcyclists. The second phase of the filtration process is based on more rules for article inclusion. The criteria of inclusion for the second phase of filtration examined the deployment of motorcyclist driver behaviour characterisation procedures using a real-time-based data acquisition system (DAS) or a questionnaire. The final number of articles was divided into three main groups: reviews (7/174), experimental studies (41/174), and social studies-based articles (126/174). This taxonomy of the literature was developed to group the literature into articles with similar types of experimental conditions. Recommendation topics are also presented to enable and enhance the pace of the development in this research area. Research gaps are presented by implementing a substantial analysis of the previously proposed methodologies. The analysis mainly identified the gaps in the development of data acquisition systems, model accuracy, and data types incorporated in the proposed models. Finally, research directions towards ITS are provided by exploring key topics necessary in the advancement of this research area.
... 355 In (Huang et al., 2017; Pouresmaeili et al., 2018; Shen et al., 2018), one or two roads/loops 356 were considered. In (Adak et al., 2016), only three vehicles were used, and each completed 357only ten successful trips, whereas a single vehicle was used in(Seedam et al., 2015). ...
The driving patterns in developing countries, especially in metropolitan cities, are significantly different from those in developed countries or less-populated cities. However, most of the vehicles driven in these cities are tested using driving cycles that do not match those special driving characteristics, typically resulting in an underestimation or overestimation of the emission rates. In this study, a first driving cycle of passenger cars with gasoline engines is proposed for Greater Cairo, Egypt, based on a very large and diverse dataset of high-resolution onboard measurements, recorded using 87 cars driven in 10 distinctive areas in Greater Cairo. Two global driving cycles have been developed based on the commonly used K-means and the newly suggested K-medoids clustering techniques. The developed cycle based on the K-medoids algorithm, which was found more representative of the collected data, is a time series of speed, ~1500 s, covering a distance of ~5.4 km, with an average speed of 12.480 km/h, where 16.3% of the total duration spent in the idling mode. The superiority of the developed cycle over two commonly used cycles, namely the American transient FTP-75 cycle and the European modal ECE cycle, in terms of estimated fuel consumption and emission rates, is reported.
... These driving parameters become intensive due to the influence of intersection on vehicle speed under heterogeneous traffic conditions. The base driving cycle is segregated into a number of micro-trips and further analysis can be achieved through analysis of speed based parameters (Gunther et al., 2017, Seedam et al., 2015. A candidate driving cycle is constructed by compiling and arranging micro-trips in series.The performance of speed acceleration frequency is employed to examine the validity of candidate cycles (Hung et al., 2007). ...
Road transport is the main contributor of emissions through vehicle exhaust. Vehicle exhaust emissions exclusively depend on vehicle characteristics, road geometry, traffic characteristics, atmospheric conditions, vehicles' age and driving behaviour. In the road network, intersections are crucial elements because of their regulation, traffic composition and geometric features. Generally, the driver has to decrease speed and sometimes stop for a long period of time while approaching the intersections, which cause a high concentration of emissions. It is a prior need to study the speed pattern of vehicles at intersections in the wake of fundamental for air quality analysis. To comprehend the driving characteristics of an individual vehicle and speed variation at the intersection, the driving cycle is an important concept being used from many years. Driving cycle is the speed-time profile of the vehicle in stipulated traffic condition. To represent the driving characteristics of an area or a city, the development of the driving cycle is an appropriate approach. It is the process of generating candidate driving cycles associated with vital driving parameters such as acceleration, deceleration, cruise and idle. Numbers of methods have been proposed for the development of the candidate driving cycles based on the purpose of the analysis. In the present study, micro-trip based driving cycle analysis approach is used for urban intersections of Vadodara city, India. Micro-trips are defined as speed profile of the vehicles from upstream to downstream of the intersection, it is the stretch at which succession driving states deceleration, idle and acceleration observed distinctly in the vicinity of intersections. To collect the speed data, the V-box (Velocity box) is embedded on the test vehicles of motorized three wheelers, motorcycle and car. The result shows that the percentage of time spent in acceleration-deceleration state for motorized three wheelers relatively 45% greater than motorcycle and car as 25%. The idling period is high for motorcycle and car ranges from 42-45%. Validation of candidate driving cycles is accomplished through the sum squared difference between data set.
... Subsequently, driving cycles were developed worldwide to capture local traffic conditions. Major driving cycles include Taipei (Tzeng and Chen, 1998), Delhi (Badusha and Ghosh, 1999), Hong Kong (Tong et al., 1999), Pune (Kamble et al., 2009), Chennai (Nesamani and Subramanian, 2011), Edinburgh (Saleh et al., 2012), Singapore (Ho et al., 2014), Toronto (Amirjamshidi and Roorda, 2015), and Khon Kaen (Seedam et al., 2015). Almost all the driving cycles being constructed in recent past use similar assessment parameters such as average speed, average acceleration, and percentage idle. ...
Driving cycles are used to understand the driving pattern of vehicles and in estimating their emissions. Although several studies exist on driving cycles worldwide, few studies have focused on developing driving cycles for intra-city buses in heterogeneous traffic conditions. In this study, driving cycles for intra-city buses were developed using real-world GPS data collected during peak and off-peak periods in Chennai city, India. The methodology for the construction of the candidate cycle was based on k-means clustering and one-step Markov modelling. For Markov chain modelling, a transition matrix is constructed which is a probability matrix based on one step succession. To understand the effect of duration of the driving cycle, the candidate cycles were developed for different durations ranging from 400 seconds to 2800 seconds. Further, the average error for each duration of the candidate cycles was determined. The duration which corresponds to the least average error was chosen for developing the final driving cycle. Three driving cycles - corresponding to morning peak hour, off-peak hour, and evening peak hour - were developed. Finally, the developed cycles were compared with the existing local and international cycles. The developed driving cycle was found to be significantly different from the existing cycles for buses.
... For instance, Nesamani and Subramanian (2011) developed a driving cycle for buses in Chennai, India, while Arun, Mahesh, Ramadurai, and Nagendra (2017)) developed driving cycles for passenger cars and motorcycles in the same city. In the discussion section of these literatures, some driving cycles are compared with standard driving cycles (Gong et al., 2018;Ho, Wong, & Chang, 2014;Pouresmaeili, Aghayan, & Taghizadeh, 2018), and others are further compared with local driving cycles in other cities (Mayakuntla & Verma, 2018;Brady & O' Mahony, 2016;Tong, 2019;Seedam, Satiennam, Radpukdee, & Satiennam, 2015;Arun et al., 2017;Knez, Muneer, Jereb, & Cullinane, 2014;Nguyen, Nghiem, Le, & Bui, 2019;Amirjamshidi & Roorda, 2015). Significant differences between the driving cycles emphasize the necessity of studying city-specific driving cycles. ...
... e and deceleration) and is considered as a signature of driving characteristics of that city or region. K.S. Nesamani et. al.(2011) discussed the driving characteristics of intra- city buses using a Global Positioning System. The study has revealed that irrespective of road type and time of travel, a higher percentage of time is spent in idle mode.Atthapol Seedam et. al. (2015)developed an onboard system to measure the on-road driving pattern for a motorcycle driving cycle in Khon Kaen city, Thailand. The developed system, validated with high accuracy results, could measure and record a driving pattern, i.e. a speed profile of a driving motorcycle. Fotouhi, ...
Transportation emissions are the main contributor to air pollution and create many environmental problems. To control vehicle emission and to achieve air quality, driving cycle is one of the concepts applied for emission estimation. Driving cycle is fundamentally profile of speed of vehicle versus time or distance. The constitution of a driving cycle is directly related to the accuracy of any air quality analysis, so an accurate analysis of the driving cycle is important for emission estimation. In the present study, driving cycle data has been analyzed to generate candidate driving cycle, which is the single representative cycle used for emission estimation and represents the actual driving activity of the study area. This study highlights the micro-trip-based method for construction of the candidate cycle. Micro-trips are grouped and arranged to get the candidate driving cycle. The best candidate cycle is selected on the basis of cycle assessment parameters. Driving cycle data collection has been carried out in urban corridor of Vadodara city, Gujarat. The study corridor composed of four signalized intersections and one rotary intersection. The numbers of candidate cycles have been generated from the collected base data of driving cycle by the micro-trip method. The selection of the best candidate cycle is done by comparing the driving parameters of base data cycles and generated candidate cycles. The candidate cycle has the least value of root-mean-square error is selected as a final representative cycle and used for the emission estimation. A single parameter average speed is taken to estimate emission at a macroscopic level based on emission factors.
... The study explained that higher percentage of travel time is spent in idle mode while analyzing driving data of real traffic condition. Seedam, Satiennam, Radpukdee, and Satiennam, 2015 have developed on-road driving pattern for driving cycle of motorcycle for Khon Kaen city, Thailand. The results are validated through collected data of speed profile. ...
A driving cycle is a speed-time profile which forms the basis of measurements of vehicle performance and characteristics. Vehicle performance varies in different conditions of temperature, altitude, road geometry and traffic. Driving cycle can be analysed for improving vehicle fuel utilisation and reducing emission level by changing driving patterns. It achieves through traffic engineering and management including road alterations and traffic signal control. At intersections, acceleration and deceleration activities of vehicles occur at high frequency. Driving through an intersection evokes stopping or slowing of vehicles, which results sharp acceleration and promotes high emissions. The methodology adopted in present study is to analyse driving cycle characteristics for five intersections of Vadodara city. Driving cycle profile has been collected to identify the intersection influence zone. Intersection influence zone is the location from which the vehicle forcefully involves under the activity of deceleration, stop and acceleration. It doesn't have choice to move at desire speed, so it is the zone of high pollution, which needs implementation of control strategies to minimise the emissions.
