Energies

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18 pages, 8702 KiB

Open AccessArticle

Aerodynamic Drag Analysis of Autonomous Electric Vehicle Platoons

by Sai Teja Kaluva, Aditya Pathak and Aybike Ongel

Energies 2020, 13(15), 4028; https://doi.org/10.3390/en13154028 - 4 Aug 2020

Cited by 28 | Viewed by 4871

Vehicle platooning has been proposed as one of the potential technologies for intelligent transport systems to improve transportation and energy efficiency in urban cities. Despite extensive studies conducted on the platooning of heavy-duty trucks, literature on the analysis of urban vehicle platoons has [...] Read more.

Vehicle platooning has been proposed as one of the potential technologies for intelligent transport systems to improve transportation and energy efficiency in urban cities. Despite extensive studies conducted on the platooning of heavy-duty trucks, literature on the analysis of urban vehicle platoons has been limited. To analyse the impact of platooning in urban environments, this paper studies the influence of intervehicle distance, platoon size and vehicle speed on the drag coefficient of the vehicles in a platoon using computational fluid dynamics (CFD). Two vehicle models—a minibus and a passenger car—are analysed to characterise the drag coefficients of the respective platoons. An analysis of energy consumption is conducted to evaluate the energy savings with platooning using a longitudinal dynamics simulation. The results showed a reduction in the average drag coefficient of the platoon of up to 24% at an intervehicle distance of 1 m depending on the number of vehicles in the platoon. With a larger intervehicle distance of 4 m, the reduction in the drag coefficient decreased to 4% of the drag coefficient of the isolated vehicle. Subsequently, energy savings with platooning were calculated to be up to 10% depending on the driving cycle, intervehicle distance and platoon size. Full article

(This article belongs to the Special Issue Intelligent Transportation Systems)

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19 pages, 7739 KiB

Open AccessArticle

A Canopen-Based Gateway and Energy Monitoring System for Electric Bicycles

by Van-Tung Bui, Chyi-Ren Dow, Yu-Chi Huang, Pei Liu and Vu Duc Thai

Energies 2020, 13(15), 3766; https://doi.org/10.3390/en13153766 - 22 Jul 2020

Cited by 5 | Viewed by 3115

Abstract

The limitation of battery capacity is a cause of range anxiety that reduces the wide use of electric bicycles (e-bikes). Therefore, many works have developed systems that provide assistance to cyclists to deal with the range anxiety problem. However, these systems may have [...] Read more.

The limitation of battery capacity is a cause of range anxiety that reduces the wide use of electric bicycles (e-bikes). Therefore, many works have developed systems that provide assistance to cyclists to deal with the range anxiety problem. However, these systems may have limited applications since they can only work with the e-bike manufacturers’ hardware and communication protocols. This paper proposes an energy monitoring system (EMS) for e-bikes, which is based on EnergyBus, a standardized hardware and communication protocol for e-bikes. EnergyBus standard is based on controller area network (CAN) bus and CANopen protocols. EMS comprises a gateway connected to EnergyBus of e-bike and an EMS application installed on a smart device that connects to the gateway via Bluetooth. The gateway provides CAN bus monitoring and CANopen device data access services to the smart device. These services are modeled to determine gateway parameters to ensure the efficient performance of the gateway and to keep the working status of the monitored e-bike safe. The EMS application provides the cyclist information about battery status, rider efforts, and other related information such as distance and speed. Experimental results show that the proposed gateway can monitor data in real-time and ensure monitored system safety. Full article

(This article belongs to the Special Issue Intelligent Transportation Systems)

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17 pages, 3168 KiB

Open AccessArticle

A Multi-Class Multi-Movement Vehicle Counting Framework for Traffic Analysis in Complex Areas Using CCTV Systems

by Khac-Hoai Nam Bui, Hongsuk Yi and Jiho Cho

Energies 2020, 13(8), 2036; https://doi.org/10.3390/en13082036 - 19 Apr 2020

Cited by 34 | Viewed by 5437

Abstract

Traffic analysis using computer vision techniques is attracting more attention for the development of intelligent transportation systems. Consequently, counting traffic volume based on the CCTV system is one of the main applications. However, this issue is still a challenging task, especially in the [...] Read more.

Traffic analysis using computer vision techniques is attracting more attention for the development of intelligent transportation systems. Consequently, counting traffic volume based on the CCTV system is one of the main applications. However, this issue is still a challenging task, especially in the case of complex areas that involve many vehicle movements. This study performs an investigation of how to improve video-based vehicle counting for traffic analysis. Specifically, we propose a comprehensive framework with multiple classes and movements for vehicle counting. In particular, we first adopt state-of-the-art deep learning methods for vehicle detection and tracking. Then, an appropriate trajectory approach for monitoring the movements of vehicles using distinguished regions tracking is presented in order to improve the performance of the counting. Regarding the experiment, we collect and pre-process the CCTV data at a complex intersection to evaluate our proposed framework. In particular, the implementation indicates the promising results of our proposed method, which achieve accuracy around 80% to 98% for different movements for a very complex scenario with only a single view of the camera. Full article

(This article belongs to the Special Issue Intelligent Transportation Systems)

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16 pages, 4471 KiB

Open AccessArticle

Evaluating Line Capacity with an Analytical UIC Code 406 Compression Method and Blocking Time Stairway

by Ruxin Wang, Lei Nie and Yuyan Tan

Energies 2020, 13(7), 1853; https://doi.org/10.3390/en13071853 - 10 Apr 2020

Cited by 9 | Viewed by 4099

Abstract

Railways around the world are experiencing growth in traffic flow, but the problem concerning how to optimize the utilization of capacity is still demands significant research. To accommodate the increasing traffic demand, the high-speed railway operator in China is interested in understanding the [...] Read more.

Railways around the world are experiencing growth in traffic flow, but the problem concerning how to optimize the utilization of capacity is still demands significant research. To accommodate the increasing traffic demand, the high-speed railway operator in China is interested in understanding the potential benefit of adopting reasonable headway to balance the safety and efficiency of train operations. In this study, a compress timetable scheduling model based on the UIC Code 406 method is presented to evaluate the line capacity. In this model, train headway is not pre-fixed as in the existing research, but considers the actual operating conditions and is calculated using actual running data. The results of the case study show that refined headway calculations generally have positive capacity effects. Full article

(This article belongs to the Special Issue Intelligent Transportation Systems)

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18 pages, 4321 KiB

Open AccessArticle

The Capacity of the Road Network: Data Collection and Statistical Analysis of Traffic Characteristics

by Vladimir Shepelev, Sergei Aliukov, Kseniya Nikolskaya and Salavat Shabiev

Energies 2020, 13(7), 1765; https://doi.org/10.3390/en13071765 - 7 Apr 2020

Cited by 33 | Viewed by 3722

Abstract

The possibilities of collecting the necessary information using multi-touch cameras and ways to improve road traffic data collection are considered. An increase in the number of vehicles leads to traffic jams, which in turn leads to an increase in travel time, additional fuel [...] Read more.

The possibilities of collecting the necessary information using multi-touch cameras and ways to improve road traffic data collection are considered. An increase in the number of vehicles leads to traffic jams, which in turn leads to an increase in travel time, additional fuel consumption and other negative consequences. To solve this problem, it is necessary to have a reliable information collection system and apply modern effective methods of processing the collected information. The technology considered in the article allows taking into account pedestrians crossing the intersection. The purpose of this article is to determine the most important traffic characteristics that affect the traffic capacity of the intersection, in other words, the actual number of passing cars. Throughput is taken as a dependent variable. Based on the results of the regression analysis, a model was developed to predict the intersection throughput taking into account the most important traffic characteristics. Besides, this model is based on the fuzzy logic method and using the Fuzzy TECH 5.81d Professional Edition computer program. Full article

(This article belongs to the Special Issue Intelligent Transportation Systems)

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12 pages, 214 KiB

Open AccessArticle

Do People Drive Light Cars Carefully? A Comparative Study of Risky Driving Behaviors between Light Cars and Others

by Yanning Zhao and Toshiyuki Yamamoto

Energies 2020, 13(7), 1593; https://doi.org/10.3390/en13071593 - 1 Apr 2020

Cited by 1 | Viewed by 1772

Abstract

The first aim of this study was to examine whether people drive light cars carefully in comparison with standard-sized cars. The second aim was to evaluate the factors that influence these risky driving indicators. Data were collected from 49 drivers in Aichi Prefecture, [...] Read more.

The first aim of this study was to examine whether people drive light cars carefully in comparison with standard-sized cars. The second aim was to evaluate the factors that influence these risky driving indicators. Data were collected from 49 drivers in Aichi Prefecture, Japan, from November 2014 to January 2015. Risky driving behaviors included; (1) speeding, (2) high speed on a non-expressway, (3) high speed on an expressway, (4) high right/left turn rate, (5) long travel, (6) driving at night, (7) driving on an expressway, and (8) driving frequency. At first, the frequency or number of these indicators was compared between the light car group and the standard size car group by a t-test. Second, regression models were established to evaluate the influence of age, gender, living area, and car classification on each risky indicator. The t-test results showed that there was no significant difference in risky driving behaviors between the light car group and the others. The regression models confirmed that car classification did not significantly influence risky driving behaviors. Although age might affect car size selection, an interaction effect between these two factors was not observed. The results of the comparison and regression analysis revealed that drivers of light cars did not drive more carefully than drivers of standard size cars. The risky driving behaviors may partially contribute to the high injury and fatality rates of light cars. Therefore, we suggest that automakers and policymakers should provide more safety education and driving assistance for drivers of light cars. Full article

(This article belongs to the Special Issue Intelligent Transportation Systems)

16 pages, 6930 KiB

Open AccessArticle

Active Shock Absorber Control Based on Time-Delay Neural Network

by Alexander Alyukov, Yuri Rozhdestvenskiy and Sergei Aliukov

Energies 2020, 13(5), 1091; https://doi.org/10.3390/en13051091 - 2 Mar 2020

Cited by 4 | Viewed by 3260

Abstract

A controlled suspension usually consists of a high-level and a low-level controller. The purpose the high-level controller is to analyze external data on vehicle conditions and make decisions on the required value of the force on the shock absorber rod, while the purpose [...] Read more.

A controlled suspension usually consists of a high-level and a low-level controller. The purpose the high-level controller is to analyze external data on vehicle conditions and make decisions on the required value of the force on the shock absorber rod, while the purpose of the low-level controller is to ensure the implementation of the desired force value by controlling the actuators. Many works have focused on the design of high-level controllers of active suspensions, in which it is considered that the shock absorber can instantly and absolutely accurately implement a given control input. However, active shock absorbers are complex systems that have hysteresis. In addition, electro-pneumatic and hydraulic elements are often used in the design, which have a long response time and often low accuracy. The application of methods of control theory in such systems is often difficult due to the complexity of constructing their mathematical models. In this article, the authors propose an effective low-level controller for an active shock absorber based on a time-delay neural network. Neural networks in this case show good learning ability. The low-level controller is implemented in a simplified suspension model and the simulation results are presented for a number of typical cases. Full article

(This article belongs to the Special Issue Intelligent Transportation Systems)

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16 pages, 1806 KiB

Open AccessArticle

A CAV Platoon Control Method for Isolated Intersections: Guaranteed Feasible Multi-Objective Approach with Priority

by Chen Wang, Yulu Dai and Jingxin Xia

Energies 2020, 13(3), 625; https://doi.org/10.3390/en13030625 - 1 Feb 2020

Cited by 20 | Viewed by 2790

Abstract

This paper proposed a multi-objective guaranteed feasible connected and autonomous vehicle (CAV) platoon control method for signalized isolated intersections with priorities. Specifically, we prioritized the intersection throughput and traffic efficiency under a pre-defined signal cycle, based on which we minimized fuel consumption and [...] Read more.

This paper proposed a multi-objective guaranteed feasible connected and autonomous vehicle (CAV) platoon control method for signalized isolated intersections with priorities. Specifically, we prioritized the intersection throughput and traffic efficiency under a pre-defined signal cycle, based on which we minimized fuel consumption and emissions for CAV platoons. Longitudinal safety was also considered as a necessary condition. To handle the aforementioned targets, we firstly designed a vehicular sub-platoon splitting algorithm based on Farkas lemma to accommodate a maximum number of vehicles for each signal green time phase. Secondly, the CAV optimal trajectories control algorithm was designed as a centralized cooperative model predictive control (MPC). Moreover, the optimal control problem was formulated as discrete linear quadratic control problems with constraints with receding predictive horizons, which can be efficiently solved by quadratic programming after reformulation. For rigor, the proofs of the recursive feasibility and asymptotic stability of our proposed predictive control model were provided. For evaluation, the performance of the control algorithm was compared against a non-cooperative distributed CAV control through simulation. It was found that the proposed method can significantly enhance both traffic efficiency and energy efficiency with ensured safety for CAV platoons at urban signalized intersections. Full article

(This article belongs to the Special Issue Intelligent Transportation Systems)

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