Future Transportation最新文献_第7页

Analysis of Deep Convolutional Neural Network Models for the Fine-Grained Classification of Vehicles 车辆细粒度分类的深度卷积神经网络模型分析

Future Transportation Pub Date : 2023-01-31 DOI: 10.3390/futuretransp3010009

Danish ul Khairi, Ferheen Ayaz, Nagham Saeed, K. Ahsan, Syed Zeeshan Ali

{"title":"Analysis of Deep Convolutional Neural Network Models for the Fine-Grained Classification of Vehicles","authors":"Danish ul Khairi, Ferheen Ayaz, Nagham Saeed, K. Ahsan, Syed Zeeshan Ali","doi":"10.3390/futuretransp3010009","DOIUrl":"https://doi.org/10.3390/futuretransp3010009","url":null,"abstract":"Intelligent transportation systems (ITS) is a broad area that encompasses vehicle identification, classification, monitoring, surveillance, prediction, management, reduction of traffic jams, license plate recognition, etc. Machine learning has practical and significant applications in ITS. Intelligent transportation systems rely heavily on vehicle classification for traffic management and monitoring. This research uses convolutional neural networks to classify cars at fine-grained classifications (make and model). Numerous obstacles must be overcome in order to complete the task, the greatest of which are intra- and inter-class similarities between the manufacturer and model of vehicles, different lighting effects, the shape and size of the vehicle, shadows, camera view angle, background, vehicle speed, colour occlusion and environmental conditions. This paper studies various machine learning algorithms used for the fine-grained classification of vehicles and presents a comparative analysis in terms of accuracy and the size of the implemented deep convolutional neural network (DCNN). Specifically, four DCNN models, mobilenet-v2, inception-v3, vgg-19 and resnet-50, are evaluated with three datasets, BMW-10, Stanford Cars and PAKCars. The evaluation results show that mobileNet-v2 is the smallest model as it is not computationally intensive due to depthwise separable convolution. However, resnet-50 and vgg-19 outperform inception-v3 and mobilenet-v2 in terms of accuracy due to their complex structure.","PeriodicalId":238233,"journal":{"name":"Future Transportation","volume":"85 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126236067","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

These Boots Are Made for Walking: A Qualitative Study on the Perceived Barriers to Pedestrian Mobility in Madrid 这些靴子是为步行而做的:对马德里行人流动性感知障碍的定性研究

Future Transportation Pub Date : 2023-01-16 DOI: 10.3390/futuretransp3010008

M. López-Lambas, Andrea Alonso, Alba Ramírez-Saiz, Andrés Pereira

引用次数: 0

Acknowledgment to the Reviewers of Future Transportation in 2022 感谢2022年未来交通的审稿人

Future Transportation Pub Date : 2023-01-13 DOI: 10.3390/futuretransp3010007

引用次数: 0

The Construction of Xi’an Urban Bus Driving Cycle: A Case Study 西安市城市公交运行周期构建——以西安为例

Future Transportation Pub Date : 2023-01-11 DOI: 10.3390/futuretransp3010006

Y. Li, Dengwang Zhai, Hong Ding, Rajibul Islam

引用次数: 0

Design and Concept of Renewable Energy Driven Auto-Detectable Railway Level Crossing Systems in Bangladesh 孟加拉国可再生能源驱动自动检测铁路平交道口系统的设计与概念

Future Transportation Pub Date : 2023-01-04 DOI: 10.3390/futuretransp3010005

Iftekharuzzaman Iftekharuzzaman, Susmita Ghosh, M. K. Basher, Mohammad Aminul Islam, Narottam Das, M. Nur-E-Alam

{"title":"Design and Concept of Renewable Energy Driven Auto-Detectable Railway Level Crossing Systems in Bangladesh","authors":"Iftekharuzzaman Iftekharuzzaman, Susmita Ghosh, M. K. Basher, Mohammad Aminul Islam, Narottam Das, M. Nur-E-Alam","doi":"10.3390/futuretransp3010005","DOIUrl":"https://doi.org/10.3390/futuretransp3010005","url":null,"abstract":"Bangladesh’s railway system mostly uses typical manual railway crossing techniques or boom gates through its 2955.53 km rail route all over the country. Accidents frequently happen at railway crossings due to the lack of quickly operating gate systems, and to fewer safety measures at the railway crossing as well. Currently, there are very few automatic railway crossing systems available (without obstacle detectors). Additionally, all of them are dependent on the national power grid, without a backup plan for any emergency cases. Bangladesh is still running a bit behind in generating enough power for its consumption; hence, it is not possible to have a continuous power supply at all times all over the countryside. We aim to design and develop a smart railway crossing system with an obstacle detector to prevent common types of accidents at railway crossing points. We use two infrared (IR) sensors to operate the railway crossing systems, which are controlled by an Arduino Uno. This newly designed level crossing system is run with the help of sustainable renewable energy, which is cost-effective and eco-friendly, and applied under the national green energy policy towards achieving sustainable development in Bangladesh as a part of the global sustainable goal to face climate change challenges. We have summarized the simulated the results of several renewable energy sources, including a hybrid system, and optimized the Levelized Cost of Energy (LCOE) and the payback periods.","PeriodicalId":238233,"journal":{"name":"Future Transportation","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130194928","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

A Qualitative Assessment of the Deployment of Zero-Emission Heavy-Duty Trucks in Logistics—Deriving Recommendations for Action from a Socio-Technical Approach on the Regional Level 对在物流中部署零排放重型卡车的定性评估——从区域一级的社会技术方法得出行动建议

Future Transportation Pub Date : 2023-01-03 DOI: 10.3390/futuretransp3010004

Christoph Müller

引用次数: 1

Simulative Study of an Innovative On-Demand Transport System Using a Realistic German Urban Scenario 基于真实德国城市场景的创新按需交通系统模拟研究

Future Transportation Pub Date : 2022-12-30 DOI: 10.3390/futuretransp3010003

Shen Wang, T. Weber, D. Schramm

{"title":"Simulative Study of an Innovative On-Demand Transport System Using a Realistic German Urban Scenario","authors":"Shen Wang, T. Weber, D. Schramm","doi":"10.3390/futuretransp3010003","DOIUrl":"https://doi.org/10.3390/futuretransp3010003","url":null,"abstract":"Trams are a meaningful means of public transport in urban traffic. However, trams have some well-known disadvantages. These include, for example, possibly long distances to the stop, long waiting times, and lack of privacy, among others. The innovative mobility concept “FLAIT-Train” offers solutions to the problems mentioned. The FLAIT-train operates on ordinary roads and is intended to offer DOOR-2-DOOR transport. In the first application phase, the FLAIT-train runs on exclusive lanes but in the future can mix with other traffic. They are designed as vehicles with 2 seats and 1 m width. The vehicle technology of FLAIT-trains is similar/identical to battery-electric autonomous vehicles. This paper uses traffic simulations to investigate whether FLAIT trains are a suitable alternative to conventional trams, taking simulated/theoretical transport capacities in passenger-kilometers per day into account. Using the software SUMO (“Simulation of Urban Mobility”), a realistic traffic scenario is generated. In this scenario, the operation of the FLAIT-Trains and the trams are simulated under the same conditions and based on statistical data. Based on the simulation results, the performances of the FLAIT-Trains and the trams are compared.","PeriodicalId":238233,"journal":{"name":"Future Transportation","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131316519","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Port Efficiency Based on the Super-Efficiency EBM-DEA-SDM Model: Empirical Evidence from China 基于超效率EBM-DEA-SDM模型的港口效率:来自中国的经验证据

Future Transportation Pub Date : 2022-12-27 DOI: 10.3390/futuretransp3010002

Yimiao Gu, Wanwan Liu, Hui Shan Loh

引用次数: 0

Driving Behaviour and Usability: Should In-Vehicle Speed Limit Warnings Be Paired with Overhead Gantry? 驾驶行为和可用性:车内限速警告是否应该与架空门架配对?

Future Transportation Pub Date : 2022-12-26 DOI: 10.3390/futuretransp3010001

William Payre, C. Diels

引用次数: 1

Multi-Task Vehicle Platoon Control: A Deep Deterministic Policy Gradient Approach 多任务车辆排控制:一种深度确定性策略梯度方法

Future Transportation Pub Date : 2022-12-12 DOI: 10.3390/futuretransp2040057

M. Berahman, M. Rostami-Shahrbabaki, K. Bogenberger

{"title":"Multi-Task Vehicle Platoon Control: A Deep Deterministic Policy Gradient Approach","authors":"M. Berahman, M. Rostami-Shahrbabaki, K. Bogenberger","doi":"10.3390/futuretransp2040057","DOIUrl":"https://doi.org/10.3390/futuretransp2040057","url":null,"abstract":"Several issues in designing a vehicle platoon control system must be considered; among them, the speed consensus and space/gap regulation between the vehicles play the primary role. In addition, reliable and fast gap-closing/opening actions are highly recommended for establishing a platoon system. Nonetheless, the lack of research on designing a single algorithm capable of simultaneously coping with speed-tracking and maintaining a secure headway, as well as the gap-closing/opening problems, is apparent. As deep reinforcement learning (DRL) applications in driving strategies are promising, this paper develops a multi-task deep deterministic policy gradient (DDPG) car-following algorithm in a platoon system. The proposed approach combines gap closing/opening with a unified platoon control strategy; as such, an effective virtual inter-vehicle distance is employed in the developed DRL-based platoon controller reward. This innovative new distance definition, which is based on the action taken by the ego-vehicle, leads to a precise comprehension of the agent’s actions. Moreover, by imposing a specific constraint on a variation of the ego-vehicle’s relative speed with respect to its predecessor, the speed chattering of the ego-vehicle is reduced. The developed algorithm is implemented in the realistic traffic simulator, SUMO (Simulation of Urban Mobility), and the performance of the developed control strategy is evaluated under different traffic scenarios.","PeriodicalId":238233,"journal":{"name":"Future Transportation","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131052092","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1