The velocity regulation of power consumption with traffic lights for electric vehicles

2019 ◽  
Vol 233 (9) ◽  
pp. 2312-2322
Author(s):  
Qingwu Liu ◽  
Hongwen He
Keyword(s):  
Power Consumption ◽  
Travel Time ◽  
Electricity Consumption ◽  
Control Unit ◽  
Simulation Software ◽  
Traffic Information ◽  
Level Control ◽  
Long Distance ◽  
Traffic Lights ◽  
Traffic Conditions

Traffic conditions, especially at traffic crossings, have a great impact on the power consumption of vehicles. Regulating velocity using the information between vehicles and traffic systems can decrease the power consumption. This article mainly focuses on an electric vehicle equipped with radar sensors, which can get the traffic information from upto a 100-m-long distance between the controlled vehicle and the traffic lights. Using the information gathered from sensors, the top-level control unit regulates the velocity aiming at lower power consumption. When traveling through crossings, two different traffic conditions are discussed. For the first condition, no other vehicles run between the controlled vehicle and the traffic lights. Only the traffic lights information is considered. For the second condition, the controlled vehicle follows other vehicles to go through the crossing. The information of the nearest front vehicle and traffic lights is taken into consideration. In summary, the traffic lights information, including the controlled vehicle current state, the traffic lights remaining time, and the velocity and distance of the nearest former vehicle (for the second condition) are sent to the top-level control unit. Then, the control unit calculates a velocity list, which will be sent to the vehicle control unit. A simulation is conducted using a traffic simulation software named “Simulation of Urban Mobility” to verify the algorithm. The simulation results indicate that the energy efficiency is improved. For the first condition, the travel time is reduced by 8.27%, and the power consumption is reduced by 18.7%. For the second condition, the power consumption is reduced by 2.96%. Finally, for a 5.8-km driving cycle containing both conditions, the travel time is reduced by 6.9% and electricity consumption is reduced by 9.51%.

scholarly journals Modeling Operational Performance of Urban Roads with Heterogeneous Traffic Conditions

2021 ◽  
Author(s):  
Swapneel R. Kodupuganti ◽  
Sonu Mathew ◽  
Srinivas S. Pulugurtha
Keyword(s):  
North Carolina ◽  
Travel Time ◽  
Queue Length ◽  
Simulation Software ◽  
Heterogeneous Traffic ◽  
Operational Performance ◽  
Travel Time Reliability ◽  
Traffic Conditions ◽  
Vehicle Delay ◽  
Blue Line

The rapid growth in population and related demand for travel during the past few decades has had a catalytic effect on traffic congestion, air quality, and safety in many urban areas. Transportation managers and planners have planned for new facilities to cater to the needs of users of alternative modes of transportation (e.g., public transportation, walking, and bicycling) over the next decade. However, there are no widely accepted methods, nor there is enough evidence to justify whether such plans are instrumental in improving mobility of the transportation system. Therefore, this project researches the operational performance of urban roads with heterogeneous traffic conditions to improve the mobility and reliability of people and goods. A 4-mile stretch of the Blue Line light rail transit (LRT) extension, which connects Old Concord Rd and the University of North Carolina at Charlotte’s main campus on N Tryon St in Charlotte, North Carolina, was considered for travel time reliability analysis. The influence of crosswalks, sidewalks, trails, greenways, on-street bicycle lanes, bus/LRT routes and stops/stations, and street network characteristics on travel time reliability were comprehensively considered from a multimodal perspective. Likewise, a 2.5-mile-long section of the Blue Line LRT extension, which connects University City Blvd and Mallard Creek Church Rd on N Tryon St in Charlotte, North Carolina, was considered for simulation-based operational analysis. Vissim traffic simulation software was used to compute and compare delay, queue length, and maximum queue length at nine intersections to evaluate the influence of vehicles, LRT, pedestrians, and bicyclists, individually and/or combined. The statistical significance of variations in travel time reliability were particularly less in the case of links on N Tryon St with the Blue Line LRT extension. However, a decrease in travel time reliability on some links was observed on the parallel route (I-85) and cross-streets. While a decrease in vehicle delay on northbound and southbound approaches of N Tryon St was observed in most cases after the LRT is in operation, the cross-streets of N Tryon St incurred a relatively higher increase in delay after the LRT is in operation. The current pedestrian and bicycling activity levels seemed insignificant to have an influence on vehicle delay at intersections. The methodological approaches from this research can be used to assess the performance of a transportation facility and identify remedial solutions from a multimodal perspective.

Fuzzy Ramp Metering: Design Overview and Simulation Results

1998 ◽  
Vol 1634 (1) ◽  
pp. 10-18 ◽  
Author(s):  
Cynthia Taylor ◽  
Deirdere Meldrum ◽  
Les Jacobson
Keyword(s):  
Fuzzy Logic ◽  
Travel Time ◽  
Fuzzy Controller ◽  
Simulation Software ◽  
Ramp Metering ◽  
Traffic Conditions ◽  
Total Distance ◽  
Total Travel Time ◽  
Vehicle Delay ◽  
Simulation Results

A fuzzy logic ramp-metering algorithm was designed to overcome the limitations of conventional ramp-metering strategies. The fuzzy controller demonstrated improved robustness, prevented heavy congestion, intelligently balanced conflicting needs, and tuned easily. The objective was to maximize total distance traveled and minimize total travel time and vehicle delay, while maintaining acceptable ramp queues. A multiple-ramp study site from the Seattle I-5 corridor was modeled and tested using the freeway simulation software, FRESIM. For five of the six testing sets, encompassing a variety of traffic conditions, the fuzzy controller outperformed the three other controllers tested.

scholarly journals Dynamic Vehicular Route Guidance Using Traffic Prediction Information

2016 ◽  
Vol 2016 ◽  
pp. 1-11 ◽  
Author(s):  
Kwangsoo Kim ◽  
Minseok Kwon ◽  
Jaegeun Park ◽  
Yongsoon Eun
Keyword(s):  
Travel Time ◽  
Routing Algorithm ◽  
Dynamic Routing ◽  
Routing Algorithms ◽  
Traffic Information ◽  
Traffic Prediction ◽  
Route Guidance ◽  
Traffic Conditions ◽  
Routing Performance ◽  
Prediction Strategy

We propose a dynamic vehicular routing algorithm with traffic prediction for improved routing performance. The primary idea of our algorithm is to use real-time as well as predictive traffic information provided by a central routing controller. In order to evaluate the performance, we develop a microtraffic simulator that provides road networks created from real maps, routing algorithms, and vehicles that travel from origins to destinations depending on traffic conditions. The performance is evaluated by newly defined metric that reveals travel time distributions more accurately than a commonly used metric of mean travel time. Our simulation results show that our dynamic routing algorithm with prediction outperforms both Static and Dynamic without prediction routing algorithms under various traffic conditions and road configurations. We also include traffic scenarios where not all vehicles comply with our dynamic routing with prediction strategy, and the results suggest that more than half the benefit of the new routing algorithm is realized even when only 30% of the vehicles comply.

scholarly journals An Efficient Adaptive Traffic Light Control System for Urban Road Traffic Congestion Reduction in Smart Cities

Information ◽  
2020 ◽  
Vol 11 (2) ◽  
pp. 119
Author(s):  
Dex R. ALEKO ◽  
Soufiene Djahel
Keyword(s):  
Control System ◽  
Travel Time ◽  
Traffic Congestion ◽  
Fixed Time ◽  
City Centre ◽  
Light Control ◽  
Traffic Light ◽  
Long Distance ◽  
Traffic Lights ◽  
Traffic Light Control

Traffic lights have been used for decades to control and manage traffic flows crossing road intersections to increase traffic efficiency and road safety. However, relying on fixed time cycles may not be ideal in dealing with the increasing congestion level in cities. Therefore, we propose a new Adaptive Traffic Light Control System (ATLCS) to assist traffic management authorities in efficiently dealing with traffic congestion in cities. The main idea of our ATLCS consists in synchronizing a number of traffic lights controlling consecutive junctions by creating a delay between the times at which each of them switches to green in a given direction. Such a delay is dynamically updated based on the number of vehicles waiting at each junction, thereby allowing vehicles leaving the city centre to travel a long distance without stopping (i.e., minimizing the number of occurrences of the ‘stop and go’ phenomenon), which in turn reduces their travel time as well. The performance evaluation of our ATLCS has shown that the average travel time of vehicles traveling in the synchronized direction has been significantly reduced (by up to 39%) compared to non-synchronized fixed time Traffic Light Control Systems. Moreover, the overall achieved improvement across the simulated road network was 17%.

scholarly journals Twofold Addressing of Microinstructions in CMCU with Common Memory

2021 ◽  
pp. 86-98
Author(s):  
A. Barkalov ◽  
L. Titarenko ◽  
O. Golovin ◽  
A. Matvienko
Keyword(s):  
Power Consumption ◽  
Control Algorithm ◽  
Design Method ◽  
Optimal Solution ◽  
Control Unit ◽  
Digital Systems ◽  
Level Control ◽  
Chip Area ◽  
Control Circuits ◽  
Common Memory

Introduction. Control unit (CU) is one of the most important blocks of practically any digital system. Its characteristics largely determine the characteristics of a system as a whole. As a rule, to synthesize CUs, the models of Mealy and Moore finite state machines (FSMs) are used. The article is devoted to compositional microprogram control units (CMCUs). A CMCU is a Moore FSM in which a state register is replaced by a microinstruction address counter. The choice of CMCU is an optimal solution for implementing linear control algorithms. When developing FSM circuits, it is necessary to optimize such characteristics as the performance and hardware amount. The methods of optimization depend strongly on logic elements used. Nowadays, FPGA chips are one of the most common logic elements for implementing digital systems. To implement the CMCU circuit, it is enough to use look-up table (LUT) elements, programmable flip-flops, embedded memory blocks, and programmable interconnections. The purpose of the article. In the article, there is proposed a CMCU design method improving such characteristics of CU as the number of logic levels and regularity of programmable interconnections. The main drawback of LUT is a small number of inputs. Modern digital systems can generate signals of logical conditions entering the control unit, the number of which is tens of times greater than the number of LUT inputs. Such a discrepancy between the characteristics of the control algorithm and the number of inputs of the LUT elements leads to multi-level control circuits with an irregular structure of programmable interconnections, and is the reason for a decrease in performance and an increase in chip area and power consumption. Results. A method for double addressing of microinstructions in CMCU with shared memory is proposed. The method is an adaptation of the two-fold state assignment of Mealy FSMs, the circuits of which are implemented with FPGAs. The proposed method makes it possible to obtain a microinstruction addressing circuit with two logic levels and a regular interconnection system. The paper considers an example of the synthesis of the CMCU circuit and analyzes the proposed method. Conclusions. The proposed method allows reducing hardware amount (the number of LUTs and their interconnections), time of delay and power consumption. Moreover, the more complex the control algorithm, the greater the benefit the proposed method gives. Keywords: compositional microprogram control unit, microinstruction, LUT, EMB, synthesis.

scholarly journals Smart Monitoring and Controlling of Appliances Using LoRa Based IoT System

Designs ◽  
2021 ◽  
Vol 5 (1) ◽  
pp. 17
Author(s):  
Nur-A-Alam ◽  
Mominul Ahsan ◽  
Md. Abdul Based ◽  
Julfikar Haider ◽  
Eduardo M. G. Rodrigues
Keyword(s):  
Power Consumption ◽  
Low Power ◽  
Modular Design ◽  
Real Life ◽  
Environmental Data ◽  
Automation System ◽  
Area Network ◽  
Wide Area Network ◽  
Long Distance ◽  
At Home

In the era of Industry 4.0, remote monitoring and controlling appliance/equipment at home, institute, or industry from a long distance with low power consumption remains challenging. At present, some smart phones are being actively used to control appliances at home or institute using Internet of Things (IoT) systems. This paper presents a novel smart automation system using long range (LoRa) technology. The proposed LoRa based system consists of wireless communication system and different types of sensors, operated by a smart phone application and powered by a low-power battery, with an operating range of 3–12 km distance. The system established a connection between an android phone and a microprocessor (ESP32) through Wi-Fi at the sender end. The ESP32 module was connected to a LoRa module. At the receiver end, an ESP32 module and LoRa module without Wi-Fi was employed. Wide Area Network (WAN) communication protocol was used on the LoRa module to provide switching functionality of the targeted area. The performance of the system was evaluated by three real-life case studies through measuring environmental temperature and humidity, detecting fire, and controlling the switching functionality of appliances. Obtaining correct environmental data, fire detection with 90% accuracy, and switching functionality with 92.33% accuracy at a distance up to 12 km demonstrated the high performance of the system. The proposed smart system with modular design proved to be highly effective in controlling and monitoring home appliances from a longer distance with relatively lower power consumption.

scholarly journals Energetic Aspects of Turfgrass Mowing: Comparison of Different Rotary Mowing Systems

Agriculture ◽  
2019 ◽  
Vol 9 (8) ◽  
pp. 178
Author(s):  
Michel Pirchio ◽  
Marco Fontanelli ◽  
Fabio Labanca ◽  
Mino Sportelli ◽  
Christian Frasconi ◽  
...  
Keyword(s):  
Power Consumption ◽  
Tall Fescue ◽  
Energy Requirement ◽  
Electricity Consumption ◽  
Primary Energy ◽  
Electric Motors ◽  
Full Throttle ◽  
Nitrogen Rates ◽  
Over Time ◽  
Primary Energy Requirement

Turfgrass mowing is one of the most important operations concerning turfgrass maintenance. Over time, different mowing machines have been developed, such as reel mowers, rotary mowers, and flail mowers. Rotary mowers have become the most widespread mowers for their great versatility and easy maintenance. Modern rotary mowers can be equipped with battery-powered electric motors and precise settings, such as blade rpm. The aim of this trial was to evaluate the differences in power consumption of a gasoline-powered rotary mower and a battery-powered rotary mower. Each mower worked on two different turfgrass species (bermudagrass and tall fescue) fertilized with two different nitrogen rates (100 and 200 kg ha−1). The battery-powered mower was set at its lowest and highest blade rpm value, while the gasoline-powered mower was set at full throttle. From the data acquired, it was possible to see that the gasoline-powered mower had a much higher primary energy requirement, independent of the turf species. Moreover, comparing the electricity consumption of the battery-powered mower over time, it was possible to see that the power consumption varied according to the growth rate of both turf species. These results show that there is a partial waste of energy when using a gasoline-powered mower compared to a battery-powered mower.

scholarly journals Detecting Different Road Infrastructural Elements Based on the Stochastic Characterization of Speed Patterns

2017 ◽  
Vol 2017 ◽  
pp. 1-11 ◽  
Author(s):  
Mario Muñoz-Organero ◽  
Ramona Ruiz-Blázquez
Keyword(s):  
Total Variation ◽  
Traffic Congestion ◽  
Automatic Detection ◽  
Mass Function ◽  
Total Variation Distance ◽  
Statistical Moments ◽  
Probability Mass Function ◽  
Traffic Lights ◽  
Traffic Conditions ◽  
Variation Distance

The automatic detection of road related information using data from sensors while driving has many potential applications such as traffic congestion detection or automatic routable map generation. This paper focuses on the automatic detection of road elements based on GPS data from on-vehicle systems. A new algorithm is developed that uses the total variation distance instead of the statistical moments to improve the classification accuracy. The algorithm is validated for detecting traffic lights, roundabouts, and street-crossings in a real scenario and the obtained accuracy (0.75) improves the best results using previous approaches based on statistical moments based features (0.71). Each road element to be detected is characterized as a vector of speeds measured when a driver goes through it. We first eliminate the speed samples in congested traffic conditions which are not comparable with clear traffic conditions and would contaminate the dataset. Then, we calculate the probability mass function for the speed (in 1 m/s intervals) at each point. The total variation distance is then used to find the similarity among different points of interest (which can contain a similar road element or a different one). Finally, a k-NN approach is used for assigning a class to each unlabelled element.

scholarly journals Energy Demand Analysis and Design of a Hybrid Power System in Bawean Islands, Indonesia

2018 ◽  
Vol 164 ◽  
pp. 01038
Author(s):  
Ridho Hantoro ◽  
Cahyun Budiono ◽  
Ronald Kipkoech Ketter ◽  
Nyoman Ade Satwika
Keyword(s):  
Power Systems ◽  
Energy Demand ◽  
Peak Load ◽  
Electricity Consumption ◽  
Simulation Software ◽  
Diesel Generator ◽  
Time Step ◽  
Analysis And Design ◽  
Optimum System ◽  
Hybrid Power

Over 70 000 000 people in Indonesia have no access to electricity. This study was carried out in Bawean Islands which are located in the Java Sea about 150 km North of Surabaya, the headquarters of East Java. The study to determine the energy services available in the Bawean Island was done through interviewing a random sample of 72 households in two villages namely Komalasa and Lebak. Based on the average monthly electricity consumption of the sampled households connected to the grid, a hybrid renewable energy based electrical supply system was designed for Gili Timur Island, one of the satellite islands around Bawean Island. The system was designed with the aid of a time step simulation software used to design and analyze hybrid power systems. A sensitivity analysis was also carried out on the optimum system to study the effects of variation in some of the system variables. HOMER suggests that for the expected peak load of 131 kW, an optimum system will consist of 150 kW from PV array, two wind turbines each rated 10 kW, a 75 kW diesel generator and batteries for storage.

Multi-itinerary optimization as cloud service

2021 ◽  
Vol 64 (11) ◽  
pp. 121-129
Author(s):  
Alexandru Cristian ◽  
Luke Marshall ◽  
Mihai Negrea ◽  
Flavius Stoichescu ◽  
Peiwei Cao ◽  
...  
Keyword(s):  
Travel Time ◽  
Time Windows ◽  
Algorithm Design ◽  
Cloud Service ◽  
Multiple Agents ◽  
Solution Quality ◽  
Traffic Conditions ◽  
Time Distance ◽  
And Performance ◽  
Vehicle Capacity

In this paper, we describe multi-itinerary optimization (MIO)---a novel Bing Maps service that automates the process of building itineraries for multiple agents while optimizing their routes to minimize travel time or distance. MIO can be used by organizations with a fleet of vehicles and drivers, mobile salesforce, or a team of personnel in the field, to maximize workforce efficiency. It supports a variety of constraints, such as service time windows, duration, priority, pickup and delivery dependencies, and vehicle capacity. MIO also considers traffic conditions between locations, resulting in algorithmic challenges at multiple levels (e.g., calculating time-dependent travel-time distance matrices at scale and scheduling services for multiple agents). To support an end-to-end cloud service with turnaround times of a few seconds, our algorithm design targets a sweet spot between accuracy and performance. Toward that end, we build a scalable approach based on the ALNS metaheuristic. Our experiments show that accounting for traffic significantly improves solution quality: MIO finds efficient routes that avoid late arrivals, whereas traffic-agnostic approaches result in a 15% increase in the combined travel time and the lateness of an arrival. Furthermore, our approach generates itineraries with substantially higher quality than a cutting-edge heuristic (LKH), with faster running times for large instances.

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