Готові списки джерел за темами / Truck driving

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Добірка наукової літератури з теми "Truck driving"

Автор: Grafiati
Опубліковано: 4 червня 2021
Оновлено: 28 липня 2024

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Статті в журналах з теми "Truck driving"

1

Lee, Yongki, Taewon Ahn, Chanhwa Lee, Sangjun Kim, and Kihong Park. "A Novel Path Planning Algorithm for Truck Platooning Using V2V Communication." Sensors 20, no. 24 (December 8, 2020): 7022. http://dx.doi.org/10.3390/s20247022.

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Анотація:
In truck platooning, the leading vehicle is driven manually, and the following vehicles run by autonomous driving, with the short inter-vehicle distance between trucks. To successfully perform platooning in various situations, each truck must maintain dynamic stability, and furthermore, the whole system must maintain string stability. Due to the short front-view range, however, the following vehicles’ path planning capabilities become significantly impaired. In addition, in platooning with articulated cargo trucks, the off-tracking phenomenon occurring on a curved road makes it hard for the following vehicle to track the trajectory of the preceding truck. In addition, without knowledge of the global coordinate system, it is difficult to correlate the local coordinate systems that each truck relies on for sensing environment and dynamic signals. In this paper, in order to solve these problems, a path planning algorithm for platooning of articulated cargo trucks has been developed. Using the Kalman filter, V2V (Vehicle-to-Vehicle) communication, and a novel update-and-conversion method, each following vehicle can accurately compute the trajectory of the leading vehicle’s front part for using it as a target path. The path planning algorithm of this paper was validated by simulations on severe driving scenarios and by tests on an actual road. The results demonstrated that the algorithm could provide lateral string stability and robustness for truck platooning.
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2

Sollins, Brandon, Dar-Wei Chen, Lauren Reinerman-Jones, and Ron Tarr. "Truck Driving Distractions." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 58, no. 1 (September 2014): 2171–75. http://dx.doi.org/10.1177/1541931214581456.

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3

Geng, Zhaoshi, Xiaofeng Ji, Rui Cao, Mengyuan Lu, and Wenwen Qin. "A Conflict Measures-Based Extreme Value Theory Approach to Predicting Truck Collisions and Identifying High-Risk Scenes on Two-Lane Rural Highways." Sustainability 14, no. 18 (September 7, 2022): 11212. http://dx.doi.org/10.3390/su141811212.

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Collision risk identification and prediction is an effective means to prevent truck accidents. However, most existing studies focus only on highways, not on two-lane rural highways. To predict truck collision probabilities and identify high-risk scenes on two-lane rural highways, this study first calculated time to collision and post-encroachment time using high-precision trajectory data and combined them with extreme value theory to predict the truck collision probability. Subsequently, a traffic feature parameter system was constructed with the driving behavior risk parameter. Furthermore, machine learning algorithms were used to identify critical feature parameters that affect truck collision risk. Eventually, extreme value theory based on time to collision and post-encroachment time incorporated a machine learning algorithm to identify high-risk truck driving scenes. The experiments showed that bivariate extreme value theory integrates the applicability of time to collision and post-encroachment time for different driving trajectories of trucks, resulting in significantly better prediction performances than univariate extreme value theory. Additionally, the horizontal curve radius has the most critical impact on truck collision; when a truck is driving on two-lane rural highways with a horizontal curve radius of 227 m or less, the frequency and probability of collision will be higher, and deceleration devices and central guardrail barriers can be installed to reduce risk. Second is the driving behavior risk: the driving behavior of truck drivers on two-lane rural highways has high-risk, and we recommend the installation of speed cameras on two-lane rural roads to control the driving speed of trucks and thus avoid dangerous driving behaviors. This study extends the evaluation method of truck collisions on two-lane rural highways from univariate to bivariate and provides a basis for the design of two-lane rural highways and the development of real-time dynamic warning systems and enforcement for trucks, which will help prevent and control truck collisions and alleviate safety problems on two-lane rural highways.
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4

Zuo, Yong Gang, Zhu Xin Li, Jun Chen, Jing Yang, and Zhen Zhang. "Study on Driving Safety of Refueling Truck." Advanced Materials Research 774-776 (September 2013): 433–37. http://dx.doi.org/10.4028/www.scientific.net/amr.774-776.433.

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In this paper,lateral slip, longitudinal slip, lateral overturning and longitudinal overturning of refueling truck are studied according to petroleum sloshing of refueling truck tank driving on road,the rules that driving safety of refueling truck changes with related parameters variation when Refueling Truck is been driven on ramp is analyzed, the unsafe factors causing driving instability is found.
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5

Abdelkareem, Mohamed AA, Mina MS Kaldas, Mohamed Kamal Ahmed Ali, and Lin Xu. "Analysis of the energy harvesting potential–based suspension for truck semi-trailer." Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering 233, no. 11 (November 17, 2018): 2955–69. http://dx.doi.org/10.1177/0954407018812276.

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As the articulated trucks are mainly used for long distance transportations, the design of the suspension system became a major concern and a research hotspot not only for ride comfort and driving safety but also for energy consumption. Therefore, the objective of this study is to conduct a comprehensive parametrical–based conflict analysis between the ride comfort and road holding together with the potential power of the shock absorbers. The simulation analysis is performed using a 23 degree-of-freedom full truck semi-trailer mathematical model with random road surface model. The bounce and combined excitation modes for the truck model are applied to present the pro and contra of the simplified and realistic analysis. The bounce mode is applied for a road Class C and truck driving speed of 20 m/s, while the combined mode is performed with the same truck-speed but considering a Class C road for the left track and Class D road for the right track considering the time delay between the truck axles. The truck dynamics including the mean potential power, average dynamic tire load and bounce, and pitch and roll accelerations is comprehensively combined in the conflict analysis–based suspension and driving parameters. The obtained simulation results showed that the articulated truck suspension should be designed considering a realistic excitation condition. In contrast to the bounce mode, under the combined road input, the tractor ride quality and road handling performances are improved when a heavily damped suspension is considered. Furthermore, the otherwise dissipated energy through the damping events can reach an overall value between 2 and 4 kW.
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6

Wang, Qun, Ruixin Zhang, Yangting Wang, and Shuaikang Lv. "Machine Learning-Based Driving Style Identification of Truck Drivers in Open-Pit Mines." Electronics 9, no. 1 (December 24, 2019): 19. http://dx.doi.org/10.3390/electronics9010019.

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The significance in constructing a driving style identification model for open-pit mine truck drivers is to reduce diesel consumption and improve training. First, we developed a driving behavior and mining truck condition monitoring system for an open-pit mine. Under heavy-load and no-load conditions of a mining truck, based on the same experimental truck and haulage road, the data of driving behavior and truck status of different drivers were collected. The driving style characteristic parameters of mining trucks under heavy-load and no-load conditions were constructed through Pearson correlation analysis. Using a k-means clustering algorithm, driving style can be divided into three types: normal type, soft type, and aggressive type, and we verified the validity of this driving style classification with a box plot. On this basis, the parameters of random forest, k-nearest neighbor, support vector machine, and neural network models were optimized and the accuracy was compared through a cross-validation grid search, and then a driving style identification model based on the random forest method was finally proposed. Driving style parameter weight values were obtained based on the Gini coefficient. Last, the fuel consumption characteristics of different driving styles were calculated. The results show that the driving style identification models based on random forest can effectively identify different driving styles when the mining truck is operating under heavy load and no load, and the overall accuracy of the model is 95.39% and 90.74% respectively. The fuel consumption of the aggressive driving style was the largest and was 10% higher than the average fuel consumption. The research results provide data support and new ideas for operation training and fuel-saving driving of mining trucks in open-pit mines.
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7

Grinin, Valeriy, Evgeniy Shkarupelov, Aleksandr Muravev, Aleksandr Kartashov, Sergey Nazarenko, and Aleksandr Klimov. "Method for applying vehicle driving cycles to assess the durability of electromechanical transmissions of trucks." E3S Web of Conferences 402 (2023): 10008. http://dx.doi.org/10.1051/e3sconf/202340210008.

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Анотація:
The article discusses the relevance of the problem of calculating the elements of electromechanical transmissions of trucks for strength and durability. The main methods used for the formation of load conditions on electromechanical transmissions of trucks are given. The driving cycles of trucks used to obtain loads when calculating the durability of the elements of electromechanical transmissions are given. The universal driving cycles of vehicles obtained on the basis of the collection of statistical data on the movement of trucks are considered. A simulation model of the movement of a truck used to determine the loads on the electromechanical transmission while overcoming driving cycles of trucks is presented. The durability of the gears of the electromechanical transmission of a truck is analyzed on the basis of load cyclograms obtained during simulation modeling of movement. Numerical results of the safety factors of one of the gear stages are obtained. Conclusions are drawn about the optimality of the use of existing driving cycles of trucks in strength calculations. Conclusions are worded about the need to synthesize driving cycles of trucks based on the collection of statistical data on the movement of truck vehicles on the territory of the region under consideration.
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8

Kudo, Takahiko, and Michael H. Belzer. "Safe rates and unpaid labour: Non-driving pay and truck driver work hours." Economic and Labour Relations Review 30, no. 4 (October 15, 2019): 532–48. http://dx.doi.org/10.1177/1035304619880406.

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Анотація:
In the trucking industry, truck drivers’ duties include not only driving trucks but also non-driving labor. However, non-driving work is not necessarily paid. This article analyses how the payment for non-driving duties (non-driving pay) affects truck drivers’ work hours. Using the National Institute for Occupational Safety and Health Long-Haul Truck Driver survey, the study finds that remunerating drivers for non-driving duties decreases drivers’ work hours. Drivers who are paid for their non-driving labor may reach their target earnings in fewer work hours, leading them to refrain from working extremely long hours and more willingly comply with working time regulations. The policy implication is that paying for non-driving labor can prevent drivers from working excessively long hours, mitigating fatigue, and consequent accidents. Thus, pay for non-driving labor may enhance their safety and health.JEL Codes: J33, J28, J31
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9

Xin, Tian, Jinliang Xu, Chao Gao, and Zhenhua Sun. "Research on the speed thresholds of trucks in a sharp turn based on dynamic rollover risk levels." PLOS ONE 16, no. 8 (August 20, 2021): e0256301. http://dx.doi.org/10.1371/journal.pone.0256301.

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Анотація:
Truck rollover is a problem that seriously endangers the safety of human life. Under special conditions, when the driver takes a sharp turn, the truck is most prone to rollover. Speed seriously affects the driving stability of the truck in a sharp turn, but the calculation of the safe speed is not accurate enough at present. The aim of this paper is to develop a more accurate safe speed calculation method to avoid the truck rollover in a sharp turn. Firstly, the calculation formula of the rollover threshold was derived based on a theoretical model, then, the simulation tests were carried out. We selected a 4-axle truck with a total weight of 30t as the subject, simulated the dynamic process of the truck rollover in a sharp turn with TruckSim, evaluated the dynamic rollover risk levels of the truck during this process, and verified the accuracy of the simulation results by results of the theoretical model. Finally, by analyzing the steering principle of the vehicle, the safe speed threshold and the limit speed threshold of the truck in a sharp turn were calculated according to the lateral acceleration corresponding to the rollover risk levels. The results show that no matter what the loading condition of the truck is, when the rollover margin is reduced to about 0.15g, the truck just reaches the risk level of critical rollover; the result provides an accurate algorithm for speed thresholds of the truck when turning radius is less than 250 m. The research provides a calculation method for safe speed of trucks from a dynamic perspective. The research results can be applied to the speed warning system of trucks, which can make drivers better control the rollover risk of trucks in the process of driving and improve driving safety.
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10

Akay, Abdullah E. "Determination of the Safest Route for Logging Trucks Based on Road Types and Conditions." Environmental Sciences Proceedings 3, no. 1 (November 13, 2020): 5. http://dx.doi.org/10.3390/iecf2020-08068.

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Анотація:
Hauling of wood-based forest products is a complex problem that requires evaluation of many alternative routes. Forest transportation has been generally done by using logging trucks with high carrying capacity. Logging truck driving is one of the dangerous occupations in forestry, particularly in Turkey, where forest lands are mostly located in mountainous regions with steep slopes. The safety risk of truck driving mainly depends on the road standards and conditions. The majority of the forest roads in Turkey have low standards that limit the maneuverability of logging trucks. In such conditions, forest transportation should be planned by considering not only transportation costs but also the safety of logging truck driving. In this study, the GIS-based network analysis method was used to develop the optimum transportation plans for two scenarios. In the first scenario, an optimum plan that minimized the total transportation cost was developed, while a transportation plan that ensured the safest logging truck driving was optimized in the second scenario. A safety score was assigned to each road section based on the road type (asphalt, gravel, forest road) and road conditions (good, medium, poor). In the study area, located in the city of Bursa in Turkey, there were three forest depots and five landings. The results indicated that the transportation cost increased by 15.76% when the safety of logging truck driving was prioritized. In this scenario, forest products from three landings were transported to different depots, compared to the first scenario.
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Дисертації з теми "Truck driving"

1

Mabbott, Nicholas. "Monitoring device for early warning signs of operator fatigue in open cut mines /." Access via Murdoch University Digital Theses Project, 2006. http://wwwlib.murdoch.edu.au/adt/browse/view/adt-MU20060809.93310.

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2

Douglas, Matthew Aaron Swartz Stephen M. "Commercial motor vehicle driver safety an application of ethics theory /." [Denton, Tex.] : University of North Texas, 2009. http://digital.library.unt.edu/permalink/meta-dc-11048.

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3

Desai, Anup. "Obstructive sleep apnoea and driver performance prevalence, correlates, and implications for driver fatigue /." Connect to full text, 2002. http://hdl.handle.net/2123/589.

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Анотація:
Thesis (Ph. D.)--University of Sydney, 2003.
Includes tables and questionnaires. Title from title screen (viewed Apr. 29, 2008). Submitted in fulfilment of the requirements for the degree of Doctor of Philosophy to the Faculty of Medicine. Degree awarded 2003; thesis submitted 2002. Includes bibliography. Also available in print form.
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4

Mohamedshah, Yusuf M. "Correlation of truck accidents with highway geometry /." This resource online, 1991. http://scholar.lib.vt.edu/theses/available/etd-10222009-125005/.

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5

Isaksson, Palmqvist Mia. "Model Predictive Control for Autonomous Driving of a Truck." Thesis, KTH, Skolan för elektro- och systemteknik (EES), 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-187668.

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Анотація:
Platooning and cooperative driving can decrease the emissions of greenhouse gases and increase the traffic capacity of the roads. The Grand Cooperative Driving Challenge, GCDC, is a competition that will be held in May 2016 focusing on cooperative driving. A cornerstone in the cooperative driving is autonomous driving. The main objective of this thesis is to design a Model Predictive Control for a truck so it autonomously can perform the following tasks: follow a straight road, make a lane change and make a turn. Constraints are added to the vehicle states and the control signals. Additionally, a constraint is added to make the vehicle keep a safe distance to preceding vehicles. A Linear Time-Varying (LTV) MPC for reference tracking is derived. To use the MPC for reference tracking references for all the states and control signals are derived. For the lane change and turn scenario Bezier curves are used to obtain the position references. The controller is implemented in MATLAB and validated through simulations. For the simulations both a bicycle model of the vehicle and a more complicated four wheel model are used. The latter is implemented in Simulink. The bicycle model is on-line linearised around the references in order to be used as the prediction model for the LTV-MPC. The simulations show that the controller can make the vehicle perform the above mentioned tasks. With a horizon of 18 the time in average to perform one iteration of the control loop is 0.02 s. The maximum deviation in the lateral direction is 0.10 m and occurs for the turn scenario when the four wheel model is used for the simulations. Simulations are also done with a preceding vehicle. The controller is able to make the vehicle keep a safe distance to the preceding vehicle. If the preceding vehicle is driving slower than the controlled vehicle the controller is able to decrease the velocity of the controlled vehicle. In addition to the above mentioned, simulations are also done where disturbances and noise, separately, are added. As a disturbance an error in the start position is used. The vehicle can start 1.3 m from the real start position, in the lateral direction, and still find its way back to the trajectory. The noise is added as white noise to the position updates. The controller can deal with noise with a standard deviation up to 0.3 m.
Kolonnkörning och kooperativkörning kan minska utsläppen av växthusgaser och öka trafikkapaciteten på vägarna. The Grand Cooperative Driving Challenge, GCDC, är en tävling med fokus på kooper-ativkörning som kommer att hållas i maj 2016. En hörnsten i kooperativkörning är autonomkörning. Det huvudsakliga målet med det här examensarbetet ¨ar att designa en MPC för en lastbil så att den autonomt kan genomföra följande: följa en rak väg, göra ett filbyte samt göra en sväng. Begränsningar är lagda på fordonets tillstånd och kontrollsignalerna. Utöver det begränsas avståndetet till framförvarande fordon. En linjär tidsvariant (LTV) MPC för referensföljning tas fram. För att använda MPC:n för referensföljning härleds referenser för fordonets tillstånd och kontrollsignaler. För filbytet och svängen används Bezier kurvor för att få fram positionsreferenserna. Regulatorn implementeras i MATLAB och valideras genom simuleringar. För simuleringarna används både en cykelmodell av fordonet och en mer komplicerad fyrhjuls-modell. Den senare implementeras i Simulink. Cykelmodellen linjäriseras online kring referenserna i syfte att användas som prediktionsmodell för LTV-MPC. Simuleringarna visar att regulatorn kan få fordonet att genomföra de ovan nämnda uppgifterna. Med en horisont på 18 ¨ar tiden det tar att genomföra en iteration av regulator-loopen i genomsnitt 0.02 sekunder. Den maximala avvikelsen i den laterala riktningen ¨ar 0.10 meter och uppstår när simuleringar görs för en sväng med fyrhjuls-modellen som fordonsmodell. Simuleringar görs även med ett framförvarande fordon. Regulatorn kan få fordonet att hallå ett säkerhetsavstånd till fordonet framför. Regulatorn kan vidare få fordonet att sänka hastigheten om det framförvarande fordonet kör långsammare. Utöver de ovan nämnda simuleringarna görs simuleringar där störningar och brus, var för sig, introduceras. Som störning används ett fel i startpositionen. Fordonet kan starta 1.3 meter från den korrekta startpositionen, i den laterala riktningen, och hitta tillbaks till referensbanan. Bruset adderas som vitt brus på positionsuppdateringarna. Regulatorn kan hantera vitt brus med en stan-dardavvikelse på upp till 0.3 meter.
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6

Mancino, Francesco. "An embedded model predictive controller for optimal truck driving." Thesis, KTH, Reglerteknik, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-205649.

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An embedded model predictive controller for velocity control of trucks is developed and tested. By using a simple model of a heavy duty vehicle and knowledge about the slope of the road ahead, the fuel consumption while traveling near a set speed is diminished by almost 1% on an example road compared to a rule based speed control system. The problem is formulated as a look-ahead optimization problem were fuel consumption and total trip time have to be minimized. To find the optimal solution dynamic programming is used, and the whole code is designed to run on a Scania gearbox ECU in parallel with all the current software. Simulations were executed in a Simulink environment, and two test rides were performed on the E4 motorway.
En algoritm för hastighetsstyrning baserad på modell-prediktiv reglering har utvecklats och testats på befintlig styrsystem i ett Scania lastbil. Genom att använda en enkel modell av fordonet och kunskap om lutningen på vägen framför den kunde man sänka bränsleförbrukningen med nästan 1% i vissa sträckor, jämfört med en regelbaserad farthållare. Problemet är formulerat som en optimerings-problem där bränsleförbrukning och total restid måste minimeras. För att hitta den optimala lösningen användes dynamisk programmering och hela koden är skriven så att den kan exekveras på en Scania styrenehet. Koden är kan köras parallellt med den mjukvara som är installerad på styrenheten. Simuleringar utfördes i en miljö utvecklad i Simulink. Två test-körningar på E4 motorvägen utfördes.
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7

Chan, Sau Yin. "Cross-border truck driving : negotiating work control and gendering work identity /." View Abstract or Full-Text, 2003. http://library.ust.hk/cgi/db/thesis.pl?SOSC%202003%20CHAN.

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Анотація:
Thesis (M. Phil.)--Hong Kong University of Science and Technology, 2003.
Includes bibliographical references (leaves 95-104). Also available in electronic version. Access restricted to campus users.
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8

Tanner, Deborah Brae. "No margin for error driving the east shore of Flathead Lake /." Diss., [Missoula, Mont.] : The University of Montana, 2009. http://etd.lib.umt.edu/theses/available/etd-12302009-133705.

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9

Mohamedshah, Yusaf M. "Correlation of truck accidents with highway geometry." Thesis, Virginia Tech, 1991. http://hdl.handle.net/10919/45243.

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Анотація:
Growth trends in vehicle transportation for the year 1989 showed that truck travel has increased from 400 billion vehicle miles of travel to 600 billion vehicle miles from 1980 to 1989, a staggering 50% increase. If this trend continues, then truck travel will reach 800 billion vehicle miles by the end of the year 2000. This increase in truck travel poses operational and safety problems for both passenger vehicles and trucks. To improve the existing highway facilities for trucks as well as to determine the design standards for new truck facilities, an understanding of the relationship between truck accidents and highway geometry is required. A number of models have been developed in the past but none of them consider all of the geometric features of the highway which are crucial for truck travel and the causation of truck accidents. The objectives of this study were to identify the roadway variables that affect truck accidents and to develop mathematical models which would determine truck involvement rates, per mile, per year. Data from the Highway Safety Information System (HSIS) was used in this analysis. The HSIS is a new data base developed by FHWA which contains accident, roadway and traffic data from five States. Models for truck accidents on Interstates, 2 lane rural roads, and for over turning accidents on Interstates were developed. The models indicate that truck accidents are primarily affected by horizontal curvature and vertical gradient albeit their values are different for Interstates and 2 lane rural roads. The number of truck accidents decreases on 2 lane rural roads as the shoulder width increases, and the model indicates that gradient has no effect on truck accidents on these roads and this, may be due to the inadequacy of the data. The Interstate model indicates that the higher the degree of curvature and the percentage of gradient, the greater the number of truck accident, as well as overturning truck accident involvement rates.
Master of Science
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10

Anibas, Judith. "A study of virtual simulation in a truck driver training program." Online version, 2008. http://www.uwstout.edu/lib/thesis/2008/2008anibasj.pdf.

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Анотація:
Thesis PlanB (M.S.)--University of Wisconsin--Stout, 2008.
ONLINE VERSION INCOMPLETE: APPENDIX A, P. 51; APPENDIX B, P. 52; APPENDIX I, P. 59; & APPENDIS J, P. 6 MISSING. Includes bibliographical references.
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Книги з теми "Truck driving"

1

Royston, Angela. Truck trouble. New York, N.Y: DK Pub., 1998.

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2

Tudor, Ted N. Professional truck driving manual. Casper, WY: IAP, 1993.

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3

Clement, Nathan. Drive. Asheville, N.C: Front Street, 2008.

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4

Clement, Nathan. Drive. Asheville, N.C: Front Street, 2008.

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5

Truck trouble. London: Dorling Kindersley, 1998.

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6

California. Heavy Commercial Vehicle and Driver Safety Task Force. Status report on truck and truck driver safety: A report to the Governor and the Legislature, January 1991. [Sacramento, CA ] (PO Box 942898 Sacramento, 94298-0001): California Highway Patrol, 1991.

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7

Radlauer, Ed. Truck tech talk. Chicago: Childrens Press, 1986.

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8

Radlauer, Ed. Truck tech talk. Chicago: Childrens Press, 1986.

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9

Savage, Jeff. Truck and tractor pulling. Minneapolis: Capstone Press, 1996.

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10

Safety, Canada Road. Driving behaviour and characteristics of heavy duty truck operators in Canada. Ottawa: Transport Canada,Safety, 1987.

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Частини книг з теми "Truck driving"

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Turri, Valerio, Jonas Mårtensson, and Karl H. Johansson. "Automated Truck Driving." In Encyclopedia of Systems and Control, 106–15. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-44184-5_100117.

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Turri, Valerio, Jonas Mårtensson, and Karl H. Johansson. "Automated Truck Driving." In Encyclopedia of Systems and Control, 1–10. London: Springer London, 2021. http://dx.doi.org/10.1007/978-1-4471-5102-9_100117-1.

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de Bruin, Gerrit Jan, Cor J. Veenman, H. Jaap van den Herik, and Frank W. Takes. "Understanding Dynamics of Truck Co-Driving Networks." In Complex Networks and Their Applications VIII, 140–51. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-36683-4_12.

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de Bruijn, Freek, and Jacques Terken. "Truck Drivers as Stakeholders in Cooperative Driving." In Lecture Notes in Computer Science, 290–98. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-14112-1_23.

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Kuhn, Andreas, José Carmona, and Elvira Thonhofer. "Research Design and Evaluation Strategies for Automated Driving." In Energy-Efficient and Semi-automated Truck Platooning, 41–54. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-88682-0_4.

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AbstractAutomated driving, in general, and platooning, in particular, represent a highly active field of research. The idea to automate traffic is closely related to high expectations in both individual and public transport. However, the complexity of automated driving requires methods beyond the traditional development approaches. This chapter describes a state-of-the-art methodology to organise and systematically address a comprehensive set of research questions in the context of truck platooning. Following best practices, an evaluation design is presented, which ensures the alignment of research efforts with the actual research agenda, that is, to answer the right questions. Specifically, the benefits of automated driving and their conflicting relationships are explored and the entities that affect automated driving performance and their interactions are presented. Finally, a solution concept that adequately addresses the complexity and the stochastic nature of the problem is presented. The solution concept consists of several key methods such as scenario-based design and stochastic simulation, data mining and complexity and robustness management.
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Kuhn, Andreas, José Carmona, and Elvira Thonhofer. "Research Design and Evaluation Strategies for Automated Driving." In Energy-Efficient and Semi-automated Truck Platooning, 41–54. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-88682-0_4.

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Анотація:
AbstractAutomated driving, in general, and platooning, in particular, represent a highly active field of research. The idea to automate traffic is closely related to high expectations in both individual and public transport. However, the complexity of automated driving requires methods beyond the traditional development approaches. This chapter describes a state-of-the-art methodology to organise and systematically address a comprehensive set of research questions in the context of truck platooning. Following best practices, an evaluation design is presented, which ensures the alignment of research efforts with the actual research agenda, that is, to answer the right questions. Specifically, the benefits of automated driving and their conflicting relationships are explored and the entities that affect automated driving performance and their interactions are presented. Finally, a solution concept that adequately addresses the complexity and the stochastic nature of the problem is presented. The solution concept consists of several key methods such as scenario-based design and stochastic simulation, data mining and complexity and robustness management.
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Bruin, Gerrit Jan de, Cor J. Veenman, H. Jaap van den Herik, and Frank W. Takes. "Understanding Behavioral Patterns in Truck Co-driving Networks." In Studies in Computational Intelligence, 223–35. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-05414-4_18.

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Du, Junmin, Hui Lu, Weiyu Sun, Xin Zhang, Huimin Hu, and Yang Liu. "Investigation on Driving Habits of Chinese Truck Driver." In Communications in Computer and Information Science, 526–31. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-58750-9_73.

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Gan, Jiahua, Meng Zhang, and Yun Xiao. "Multidimensional Data Analysis Based on LOGIT Model." In Proceeding of 2021 International Conference on Wireless Communications, Networking and Applications, 303–15. Singapore: Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-2456-9_32.

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AbstractLogit Model is an important method for empirical analysis of multi-source data. In order to explore the traffic safety mechanism, The Paper taked traffic behavior data as an example, researched personal characteristics of truck drivers, Analyzed the influence of the driver’s personal traits on traffic violations. Based on the binary logistics regression model, the analysis model of traffic violations was established. The results show that personality, driver’s license level, daily driving time, transportation route, vehicle ownership, and occupational disease are important factors that affect drivers’ violations. Further data analysis shows that truck drivers with bile personalities, driving for more than 12 h per day, no fixed transportation routes, and vehicles with loans have the highest probability of violations. The data analysis conclusion provides data basis for truck driver management and improving truck traffic safety.
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Fassih, Mohamed, Anne-Sophie Capelle-Laizé, Philippe Carré, and Pierre-Yves Boisbunon. "Reinforcement Learning for Truck Eco-Driving: A Serious Game as Driving Assistance System." In Advanced Concepts for Intelligent Vision Systems, 299–310. Cham: Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-45382-3_25.

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Тези доповідей конференцій з теми "Truck driving"

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Parkes, Andrew M. "Truck Driver Training Using Simulation in England." In Driving Assessment Conference. Iowa City, Iowa: University of Iowa, 2005. http://dx.doi.org/10.17077/drivingassessment.1094.

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Richardson, Natalie Tara, Michael Sinning, Michael Fries, Sonja Stockert, and Markus Lienkamp. "Highly automated truck driving." In AutomotiveUI '15: The 7th International Conference on Automotive User Interfaces and Interactive Vehicular Applications. New York, NY, USA: ACM, 2015. http://dx.doi.org/10.1145/2809730.2809733.

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Hoskins, A., M. El-Gindy, R. Vance, N. Hiller, and C. Goodhart. "Truck Driving Simulator Effectiveness." In ASME 2002 International Mechanical Engineering Congress and Exposition. ASMEDC, 2002. http://dx.doi.org/10.1115/imece2002-32964.

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The Pennsylvania Truck Driving Simulator (PTDS) has been implemented in several different studies. The effectiveness of utilizing the simulator for training heavy truck operators was investigated through a study with the Pennsylvania Department of Transportation (PENNDOT). Thirty-four highway equipment operator trainees from PENNDOT completed a series of driving tasks in the simulator. The driving tasks were developed as five independent driving scenarios within the simulator each requiring different skills. Measures of driver performance included ratings from professional driving instructors and numerical records from the simulator’s recording capability. These were analyzed to determine if a) students improved their driving through completing the driving scenarios, and b) the two sets of data agreed in the assessment of driver performance. This paper presents the results of this study, which showed that students’ driving skill did improve as they completed the driving tasks. The vehicle dynamics response measurement data also largely agreed with the instructors’ evaluation.
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Chen, Chi-Chun, Shang-Lin Tien, Yan-Ting Lin, Chung-Chen Teng, and Meng-Hua Yen. "Truck Driving Assistance System." In 2021 IEEE/ACIS 22nd International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD). IEEE, 2021. http://dx.doi.org/10.1109/snpd51163.2021.9704970.

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Allen, Talleah, and Ronald Tarr. "Driving Simulators for Commercial Truck Drivers - Humans in the Loop." In Driving Assessment Conference. Iowa City, Iowa: University of Iowa, 2005. http://dx.doi.org/10.17077/drivingassessment.1181.

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Krishnamoorthy, Bharathi, and S. Gopalakrishnan. "Truck Driver's Driving Performance Assessment." In Commercial Vehicle Engineering Congress & Exhibition. 400 Commonwealth Drive, Warrendale, PA, United States: SAE International, 2008. http://dx.doi.org/10.4271/2008-01-2700.

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Knipling, Ronald R. "Car-Truck Crashes in the National Motor Vehicle Crash Causation Survey." In Driving Assessment Conference. Iowa City, Iowa: University of Iowa, 2015. http://dx.doi.org/10.17077/drivingassessment.1588.

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Knipling, Ronald R. "Threats to Scientific Validity in Truck Driver Hours-of-Service Studies." In Driving Assessment Conference. Iowa City, Iowa: University of Iowa, 2017. http://dx.doi.org/10.17077/drivingassessment.1662.

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Maguire, Daniel J. "Value Assessment and Implementation Tradeoffs for Production-Heavy Truck Active Noise Control." In Driving Assessment Conference. Iowa City, Iowa: University of Iowa, 2001. http://dx.doi.org/10.17077/drivingassessment.1075.

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Knipling, Ronald R. "Three Large Truck Crash Categories: What They Tell Us About Crash Causation." In Driving Assessment Conference. Iowa City, Iowa: University of Iowa, 2009. http://dx.doi.org/10.17077/drivingassessment.1299.

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Звіти організацій з теми "Truck driving"

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Iwao, Mayumi, and Motoyuki Akamatsu. Driving Attitude/Workload Consciousness of Truck Drivers. Warrendale, PA: SAE International, May 2005. http://dx.doi.org/10.4271/2005-08-0300.

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Al-Qadi, Imad, Egemen Okte, Aravind Ramakrishnan, Qingwen Zhou, and Watheq Sayeh. Truck Platooning on Flexible Pavements in Illinois. Illinois Center for Transportation, May 2021. http://dx.doi.org/10.36501/0197-9191/21-010.

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Truck platoons have many benefits over traditional truck mobility. Truck platoons have the potential to improve safety and reduce fuel consumption between 5% and 15%, based on platoon configuration. In Illinois, trucks carry more than 50% of freight tonnage and constitute 25% of the traffic on interstates. Therefore, expected fuel savings would be significant for trucks. Deployment of truck platoons within interstate highways may have a direct effect on flexible pavement performance, as the time between consecutive axle loads (i.e., resting time) is expected to decrease significantly. Moreover, platoons could potentially accelerate pavement damage accumulation due to trucks’ channelized position, decreasing pavement service life and increasing maintenance and rehabilitation costs. The main objective of this project was to quantify the effects of truck platoons on pavements and to provide guidelines to control corresponding potential pavement damage. Finite-element models were utilized to quantify the impact of rest period on pavement damage. Recovered and accumulated strains were predicted by fitting exponential functions to the calculated strain profiles. The results suggested that strain accumulation was negligible at a truck spacing greater that 10 ft. A new methodology to control pavement damage due to truck platoons was introduced. The method optimizes trucks’ lateral positions on the pavements, and an increase in pavement service life could be achieved if all platoons follow this optimization method. Life cycle assessment and life cycle cost analysis were conducted for fully autonomous, human-driven, and mixed-traffic regimes. For example, for an analysis period of 45 years, channelized truck platoons could save life cycle costs and environmental impacts by 28% and 21% compared with human-driven trucks, respectively. Furthermore, optimum truck platoon configuration could reduce life cycle costs and environmental impacts by 48% and 36%, respectively, compared with human-driven trucks. In contrast, channelized traffic could increase pavement roughness, increasing fuel consumption by 15%, even though platooning vehicles still benefit from reduction in air drag forces. Given that truck platoons are expected to be connected only in the first phase, no actions are required by the agency. However, in the second phase when truck platoons are also expected to be autonomous, a protocol for driving trends should be established per the recommendation of this study.
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Shaver, Greg, and Miles Droege. Develop and Deploy a Safe Truck Platoon Testing Protocol for the Purdue ARPA-E Project in Indiana. Purdue University, 2021. http://dx.doi.org/10.5703/1288284317314.

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Hilly terrain poses challenges to truck platoons using fixed set speed cruise control. Driving the front truck efficiently on hilly terrain improves both trucks fuel economies and improves gap maintenance between the trucks. An experimentally-validated simulation model was used to show fuel savings for the platoon of 12.3% when the front truck uses long horizon predictive cruise control (LH-PCC), 8.7% when the front truck uses flexible set speed cruise control, and only 1.2% when the front truck uses fixed set speed cruise control. Purdue, Peloton, and Cummins have jointly configured two Peterbilt 579 trucks for relevant combinations of: (1) coordinated shifting, (2) constant or variable platoon gap controls, (3) flexible or constant speed setpoint cruise control of the front trucks, and (4) long-horizon predictive cruise control (LHPCC) of the front truck. Confirmation of this functionality during platooning was demonstrated at the Continental Test track in Uvalde, Texas. In Indiana, on-road experiments were limited to single truck operation with long-horizon predictive cruise control, flexible set speed cruise control, and constant setpoint cruise control. Data from all of the above was used to improve the fidelity of simulations used to arrive at the fuel savings and gap control findings for hilly terrain per what is summarized in the findings section. Additionally, in early summer 2020, Purdue submitted to, and received improvement from, INDOT for a safe truck platoon testing protocol (located in this report’s appendix), which could not be implemented in Indiana before the end of the project because of COVID-19. Presentations of the subject matter at COMVEC, MAASTO, Purdue Road School, and the Work Truck Show are listed in the appendix.
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Lascurain, Mary Beth, Oscar Franzese, Gary J. Capps, Adam Siekmann, Neil Thomas, Tim J. LaClair, Alan M. Barker, and Helmut E. Knee. Medium Truck Duty Cycle Data from Real-World Driving Environments: Final Report. Office of Scientific and Technical Information (OSTI), November 2012. http://dx.doi.org/10.2172/1081995.

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Franzese, Oscar, Mary Beth Lascurain, and Gary J. Capps. Medium Truck Duty Cycle Data from Real-World Driving Environments: Project Interim Report. Office of Scientific and Technical Information (OSTI), January 2011. http://dx.doi.org/10.2172/1081683.

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Walker, Jasmine, Yujie Li, Maria A. Chung Li, Sikai Chen, Samuel Labi, Jon D. Fricker, and Kumares C. Sinha. Integrating Transformative Technologies in Indiana’s Transportation Operations. Purdue University, 2024. http://dx.doi.org/10.5703/1288284317651.

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New and emerging transportation technologies, driven by automation, connectivity, and electrification, could potentially help address the transportation sector’s persistent and pervasive problems, including those associated with safety, mobility, and energy use. For this reason, the state of Indiana, uniquely positioned to serve interstate truck traffic, sought ways to identify and incorporate these new technologies on Indiana’s highways. This report addressed the challenges and opportunities regarding the integration of transformative technologies in Indiana’s truck operations, with a particular focus on truck platooning. This report started with a review of current literature about disruptive technologies in general and truck platooning specifically. This included published information on the impacts of platooning on transportation outcomes—energy use, mobility, safety, truck operators’ comfort, infrastructure condition/longevity, emissions, and other impacts. Regarding these impacts, this report presents existing simulation models for analyzing/evaluating truck platooning. Driver comfort, in terms of the platoon inter-truck headways, was investigated using a driving simulation study in the Center for Connected and Automated Center (CCAT) human factors laboratory at Purdue. This report also identified and discussed opportunities and challenges to truck platooning, and a process was developed to identify truck-platooning sections and a multi-criteria framework for ex poste or ex ante evaluation of platooning segments. Finally, the report discusses the future trends of freight transportation in Indiana (including challenges and opportunities) in truck platooning policy and development.
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Meidani, Hadi, and Amir Kazemi. Data-Driven Computational Fluid Dynamics Model for Predicting Drag Forces on Truck Platoons. Illinois Center for Transportation, November 2021. http://dx.doi.org/10.36501/0197-9191/21-036.

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Fuel-consumption reduction in the truck industry is significantly beneficial to both energy economy and the environment. Although estimation of drag forces is required to quantify fuel consumption of trucks, computational fluid dynamics (CFD) to meet this need is expensive. Data-driven surrogate models are developed to mitigate this concern and are promising for capturing the dynamics of large systems such as truck platoons. In this work, we aim to develop a surrogate-based fluid dynamics model that can be used to optimize the configuration of trucks in a robust way, considering various uncertainties such as random truck geometries, variable truck speed, random wind direction, and wind magnitude. Once trained, such a surrogate-based model can be readily employed for platoon-routing problems or the study of pavement performance.
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Liu, Tong, and Hadi Meidani. Artificial Intelligence for Optimal Truck Platooning: Impact on Autonomous Freight Delivery. Illinois Center for Transportation, August 2023. http://dx.doi.org/10.36501/0197-9191/23-017.

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The advancements in autonomous- and connected-vehicle technologies bring drastic changes in freight delivery. Vehicle-to-vehicle and vehicle-to-infrastructure communication has become a reality with the help of autonomous and connected vehicles. One of the most notable changes is the formation of truck platoons. Despite the numerous benefits of truck platooning, such as reduced fuel consumption and increased traffic efficiency, this approach requires a significant amount of computational resources to obtain aerodynamic performance under different scenarios. To overcome this challenge, a data-driven surrogate model was proposed to predict the drag force and fuel-consumption rate of truck platoons. The surrogate model improves computational efficiency, as compared to traditional methods, and provides a valuable tool for evaluating the performance of truck platoons. To demonstrate the benefits of truck platooning, a 161-km (100-mi) corridor in Illinois on I-57 highway was selected to conduct fuel-consumption analysis and delivery-cost analysis for a three-truck platoon. The results showed that the average fuel savings achieved can be up to 10%, depending on the headway between the trucks. The delivery cost of the truck platoon was reduced by 30%, as compared with conventional line-haul delivery. These findings highlighted the importance of truck platooning as a solution for reducing fuel consumption and improving delivery economy in the freight industry.
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Research Institute (IFPRI), International Food Policy. On the fast track: Driving down stunting in Vietnam. Washington, DC: International Food Policy Research Institute, 2016. http://dx.doi.org/10.2499/9780896295889_15.

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Muelaner, Jody, ed. Unsettled Issues in Commercial Vehicle Platooning. SAE International, November 2021. http://dx.doi.org/10.4271/epr2021027.

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Platooning has the potential to reduce the energy consumption of commercial vehicles while improving safety; however, both advantages are currently difficult to quantify due to insufficient data and the wide range of variables affecting models. Platooning will significantly reduce the use of energy when compared to trucks driven alone, or at a safe distance for a driver without any automated assistance. Platooning will also reduce stopping distances—multiple states in the US have passed laws authorizing truck platoons to operate at shorter gaps than are authorized for normal, human-driven trucks. However, drivers typically do not currently leave the recommended gaps and, therefore, already gain much of the potential energy savings by drafting lead vehicles, albeit illegally. The automated systems associated with platooning cannot be programmed to flout safety recommendations in the way that human drivers routinely do. Therefore, actual energy savings may be minimal while safety may be greatly improved. More data will be needed to conclusively demonstrate a safety gain. Recommended safe gaps are currently highly generalized and must necessarily assume worst-case braking performance. Using a combination of condition monitoring and vehicle-to-vehicle communications, platooning systems will be able to account for the braking performance of other vehicles within the platoon. If all the vehicles in a platoon have a high level of braking performance, the platoon will be able to operate in a more efficient, tighter formation. Driver acceptance of platooning technology will increase as the systems become more effective and do not displace jobs. The increased loading of infrastructure must also be considered, and there may be requirements for upgrades on bridges or restrictions on platooning operation.
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