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6th International Conference on Traffic engineering and transportation System, ICTETS 2022

作者： Xu, Wanhui Liu, Yugang Yi, Hongbo Liu, Gang School of Transportation and Logistics Southwest Jiaotong University Sichuan Province Chengdu610031 China National Engineering Laboratory of Integrated Transportation Big Data Application Technology Southwest Jiaotong University Sichuan Province Chengdu610031 China National United Engineering Laboratory of Integrated and Intelligent Transportation Southwest Jiaotong University Sichuan Province Chengdu610031 China Institute of Transportation Development Strategy and Planning of Sichuan Province Sichuan Province Chengdu610000 China

ISBN: (纸本)9781510663053

Autonomous driving vehicle will come reality more and more possible along with prosperity of relevant technologies. However, autonomous driving vehicles and artificial driving vehicles will coexist for a long time until full connected and autonomous traffic environment achieved. To modeling lane-changing decision of autonomous driving vehicles, which can be regard as non-cooperative static game under complete information, we establish the game theory-based lane-changing model with combined driving style (GLCD model). Then we conduct a series of simulation experiments to evaluate indicators of the GLCD model, which include the number of lane-changing, the number of accidents, the number of vehicle passes and, the average passing time, compared with the cellular automata model, also compared with the general game theory-based lane-changing model. Results show that the developed model (GLCD model) can improve the efficiency of vehicle driving and ensure stability on the road under the premise of ensuring safety. Furthermore, this model can provide a feasible vehicle lane-change decision in a mixed traffic flow environment in the future. © 2023 SPIE.

关键词： Game theory

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Personal mobility carbon credits trading schemes considering dynamic price evolution 6

Personal mobility carbon credits trading schemes considering...

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6th International Conference on Traffic engineering and transportation System, ICTETS 2022

作者： Wan, Qing Liu, Yugang Fan, Linqiang Zheng, Shuai School of Transportation and Logistics Southwest Jiaotong University Sichuan Province Chengdu610031 China National Engineering Laboratory of Integrated Transportation Big Data Application Technology Southwest Jiaotong University Sichuan Province Chengdu610031 China National United Engineering Laboratory of Integrated and Intelligent Transportation Southwest Jiaotong University Sichuan Province Chengdu610031 China Institute of Transportation Development Strategy and Planning of Sichuan Province Sichuan Province Chengdu610000 China

ISBN: (纸本)9781510663053

Considering the subway, private cars, and cycling, the Personal Mobility Carbon Credits Trading scheme is explored in a super network with homogeneous travelers to discuss the impact on travel mode split rate and system carbon emissions. The Personal Mobility Carbon Credits Trading scheme includes the travel route choice behavior and the dynamic credits price evolution, which affect each other. The former is modeled in a super network. The Dial-MSA algorithm is used for flow distribution, and the results are fed back to the dynamic credits price evolution model. Accordingly, the result of dynamic credits price evolution, in turn, affects travel cost and finally governs the result of traffic flow allocation. The results show that the system will reach a stable state in a finite time range. The convergent equilibrium price has nothing to do with the initial price but is related to the number of total credits and the credits allocation scheme. Compared with the equivalent distribution scheme, proportional distribution is more equitable. © 2023 SPIE.

关键词： Carbon

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Signal timing optimization of exit lanes for left-turn intersections considering emission and delay 6

Signal timing optimization of exit lanes for left-turn inter...

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6th International Conference on Traffic engineering and transportation System, ICTETS 2022

作者： Zhang, Shaohua Liu, Yugang Wan, Qing Tang, Liying Hu, FengLin Shu, Zhan School of Transportation and Logistics Southwest Jiaotong University Sichuan Province Chengdu610031 China National Engineering Laboratory of Integrated Transportation Big Data Application Technology Southwest Jiaotong University Sichuan Province Chengdu610031 China National United Engineering Laboratory of Integrated and Intelligent Transportation Southwest Jiaotong University Sichuan Province Chengdu610031 China Institute of Transportation Development Strategy and Planning of Sichuan Province Sichuan Province Chengdu610000 China

ISBN: (纸本)9781510663053

To evaluate the environmental benefits and operating efficiency of exit lanes for left-turn intersections, a signal optimization model considering emissions and delays is proposed. Considering the three pollutants of CO, HC, and NOx in cars and buses exhaust, VISSIM simulation software is used to obtain second-by-second data of vehicles. The data is used to calculate the second-by-second Vehicle Specific Power and to calibrate the two types of emission factors for each lane group. Cycle length, main-signal and pre-signal control are regarded as constraints, and minimum emissions and delays are regarded as optimization goals. The bi-objective optimization for exit lanes for left-turn intersections is transformed into a single-objective optimization problem through the linear weighted sum method, and the genetic algorithm is used to solve the optimal signal timing scheme. The results show that, compared with conventional intersections, the design of EFL intersections can not only improve operation efficiency, but also reduce emissions. The optimal signal timing scheme for exit lanes for left-turn intersection can reduce the delay by 6.27% and the total emissions by 7.47%;At the same time, when the proportion of left-turn traffic is 35%~40%, the signal optimization model proposed in this paper has the best optimization performance. Effective in relieving traffic pressure and has good environmental benefits. © 2023 SPIE.

关键词： Genetic algorithms

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Vulnerability analysis of weighted metro networks considering station traffic: the case of Shenzhen 6

Vulnerability analysis of weighted metro networks considerin...

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6th International Conference on Traffic engineering and transportation System, ICTETS 2022

作者： Long, Shiyu Liu, Yugang Zheng, Shuai Xu, Yihe School of Transportation and Logistics Southwest Jiaotong University Sichuan Province Chengdu610031 China National Engineering Laboratory of Integrated Transportation Big Data Application Technology Southwest Jiaotong University Sichuan Province Chengdu610031 China National United Engineering Laboratory of Integrated and Intelligent Transportation Southwest Jiaotong University Sichuan Province Chengdu610031 China Institute of Transportation Development Strategy and Planning of Sichuan Province Sichuan Province Chengdu610000 China

ISBN: (纸本)9781510663053

Due to the large number of passengers served by the metro, with its extensive served area, as well as the interconnection of different stations within the metro system, there is a high possibility that a large number of city residents' trips will be delayed or forced to be canceled and cause economic losses, once a safety accident occurs in the subway system. An easy-to-practice and highly flexible evaluation framework are proposed to explore the identification of vulnerable nodes in a weighted metro network, considering network connectivity and node traffic. The degree distribution of the passenger flow weighted network obeys the power law distribution. The relationship between node connectivity, node passenger flow, and key players in the network are also discussed. We simulated network node failures under four scenarios to assess the impact of node failures on network accessibility and the number of passengers served. The network is robust when the nodes fail randomly;the network is vulnerable to deliberate attacks based on topological node characteristics. The strategies that have the most significant impact on site traffic are node weight-based attack and node weighted-degree-based attack, with the weighted-degree-based attack being more disruptive to network connectivity and the best performing strategy in aggregate. Furthermore, we have identified the top 10 nodes in the Shenzhen Metro network that are more influential to passengers and disruptive to the network structure, which could provide a reference for metro emergency management. © 2023 SPIE.

关键词： Complex networks

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Characterizing Flight Delay Profiles with a Tensor Factorization Framework

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engineering 2021年第4期7卷 465-472页

作者： Mingyuan Zhang Shenwen Chen Lijun Sun Wenbo Du Xianbin Cao School of Electronic and Information Engineering Beihang UniversityBeijing 100191China National Engineering Laboratory for Comprehensive Transportation Big Data Application Technology Beijing 100191China Department of Civil Engineering and Applied Mechanics McGill UniversityMontrealQC H3A 0C3Canada

In air traffic and airport management,experience gained from past operations is crucial in designing appropriate strategies when facing a new ***,this paper uses massive spatiotemporal flight data to identify similar traffic and delay patterns,which become critical for gaining a better understanding of the aviation system and relevant ***,as the datasets imply complex dependence and higher-order interactions between space and time,retrieving significant features and patterns can be very *** this paper,we propose a probabilistic framework for highdimensional historical flight *** apply a latent class model and demonstrate the effectiveness of this framework using air traffic data from 224 airports in China during 2014–*** find that profiles of each dimension can be clearly divided into various patterns representing different regular *** prove the effectiveness of these patterns,we then create an estimation model that provides preliminary judgment on the airport delay *** outcomes of this study can help airport operators and air traffic managers better understand air traffic and delay patterns according to the experience gained from historical scenarios.

关键词： Air traffic management Flight delay Latent class model Tensor decomposition

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Research on 2+1 alternate highway setting in mountain area based on VISSIM simulation 6

Research on 2+1 alternate highway setting in mountain area b...

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6th International Conference on Traffic engineering and transportation System, ICTETS 2022

作者： Hu, Fenglin Liu, Yugang Zhang, Shaohua Yi, Hongbo Liu, Gang School of Transportation and Logistics Southwest Jiaotong University Sichuan Province Chengdu610031 China National Engineering Laboratory of Integrated Transportation Big Data Application Technology Southwest Jiaotong University Sichuan Province Chengdu610031 China National United Engineering Laboratory of Integrated and Intelligent Transportation Southwest Jiaotong University Sichuan Province Chengdu610031 China Institute of Transportation Development Strategy and Planning of Sichuan Province Sichuan Province Chengdu610000 China

ISBN: (纸本)9781510663053

For a long time, the operation efficiency of highways in Sichuan plateau mountainous areas has been low, and overtaking accidents occur frequently. In addition, many places are limited by natural conditions and unable to build the two-way four-lane highway. Hence, this paper proposes a new scheme to transform and expand the two-lane road into a 2+1 alternate lane. We used VISSIM software, combined with the actual traffic characteristics of the Sichuan mountainous area, and integrated with the driving behavior features to conduct a simulation analysis on the geometric parameter design, setting influencing factors and applicability of 2+1 alternate highway. It not only fills the domestic research gap but also provides theoretical support for building a safe and efficient mountain traffic system. The study found: This scheme optimizes the service level while improving the operation efficiency. When the proportion of trucks exceeds 20%, prohibiting trucks from passing through overtaking lanes shows relatively higher service levels. 2+1 alternate highways in mountainous areas have significantly better service levels than other options when the overtaking lane length is set to 550-900m, and the speed limit in the single lane is 50-100km/h. © 2023 SPIE.

关键词： Trucks

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Urban transportation network allocation considering heterogeneous users in the context of carbon trading 6

Urban transportation network allocation considering heteroge...

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6th International Conference on Traffic engineering and transportation System, ICTETS 2022

作者： Sheng, Qian Liu, Yugang Zhan, Yu Wan, Qing Fan, LinQiang School of Transportation and Logistics Southwest Jiaotong University Sichuan Province Chengdu610031 China National Engineering Laboratory of Integrated Transportation Big Data Application Technology Southwest Jiaotong University Sichuan Province Chengdu610031 China National United Engineering Laboratory of Integrated and Intelligent Transportation Southwest Jiaotong University Sichuan Province Chengdu610031 China Institute of Transportation Development Strategy and Planning of Sichuan Province Sichuan Province Chengdu610000 China

ISBN: (纸本)9781510663053

Due to the large number of motor vehicles in urban road networks, serious traffic congestion and high proportion of road carbon emissions, failure to take effective measures to manage travel demand will result in waste of road resources and environmental pollution. Considering the complex variability of the actual road network and the heterogeneous characteristics of road travelers, this paper proposes a dynamic traffic network allocation model in the context of carbon trading. The model is a dual dynamic day-by-day model, which considers both the dynamic changes of road network traffic and the dynamic adjustment and changes of carbon quota consumption rate. After 600 days of dynamic evolution, the road network reaches the system optimal state while achieving user equilibrium. Meanwhile, the carbon emission reduction on the road transport network before and after the implementation of carbon trading scheme is compared and analyzed, and the overall carbon emission is reduced by 9.23%. This provides a scientific theoretical basis and a feasible solution for the carbon trading scheme in urban transportation demand management and guiding low-carbon travel. © 2023 SPIE.

关键词： Carbon

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An Interpretable Machine Learning-Based Analysis of Vehicle Yielding During Pedestrian-Vehicle Interactions at Unsignalized Intersections

An Interpretable Machine Learning-Based Analysis of Vehicle ...

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International Conference on Intelligent transportation

作者： Ruiqi Wang Ang Ji Tao Li Zhanbo Sun Zhijian Fu National Engineering Laboratory of Integrated Transportation Big Data Application Technology School of Transportation and Logistics Southwest Jiaotong University Chengdu Sichuan China

The paper introduces an interpretable machine learning technique SHAP (SHapley Additive exPlanation) to analyze the vehicle yielding behaviors during pedestrian-vehicle interactions at unsignalized intersections. The study first extracts trajectory data from drone videos and then exploits machine learning methods to construct the yielding classification model. The results indicate that Random Forest (RF) outperforms Support Vector Machine (SVM), Gradient Boosting Machine (GBM), and eXtreme Gradient Boosting (XGBoost), achieving the best classification performance with an area under the ROC curve (AUC) of 0.934. Finally, the SHAP algorithm is fused with RF to improve the model interpretability. The analysis reveals that the distances between vehicles and pedestrians make the most significant impact on vehicle yielding behavior. Furthermore, it is found that traffic-related variables exhibit non-linear and threshold effects on vehicle yielding.

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Identifying Flight Trajectory Patterns via a Density-Aided Hierarchical Clustering Algorithm 5th

Identifying Flight Trajectory Patterns via a Density-Aided H...

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5th China Aviation Science and technology Conference, 2021

作者： Zhang, Zhuxi Chen, Yichong Fang, Jing Zhou, Xueyang An, Yuhang Zhu, Xi National Engineering Laboratory for Comprehensive Transportation Big Data Application Technology Beihang University Beijing100191 China Unit 32751 Beijing China School of Electronics and Information Engineering Beihang University Beijing100191 China Aviation Data Communication Corporation Beijing100191 China School of Computer Science and Engineering Beihang University Beijing100191 China Research Institute for Frontier Science Beihang University Beijing100191 China

ISBN: (纸本)9789811674228

Identifying flight trajectory patterns is a vital task that helps controllers better understand the flight operation mechanism, so as to effectively recognize flight anomalies and manage traffic flow, etc. However, flight operation is sensitively affected by the weather and instant airspace regulation, making the flight trajectory pattern too intertwined to be easily distinguished. In this work, we propose a trajectory pattern identification method based on a density-aided hierarchical clustering algorithm. This method employs a weighted trajectory clustering mechanism to keep the minor trajectory patterns from being improperly "swallowed" by other large trajectory patterns. Experimental results show that the proposed method can explicitly distinguish different trajectory patterns and achieve more accurate results than existing approaches. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Clustering algorithms

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Finding robust and consistent space-time delivery paths for multi-day vehicle routing problem

Finding robust and consistent space-time delivery paths for ...

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2019 IEEE Intelligent transportation Systems Conference, ITSC 2019

作者： Zhuge, Lijuan Tong, Lu Carol Wu, Hailong Chen, Yiheng Zhou, Xuesong Beijing Jiaotong University School of Traffic and Transportation Haidian Beijing100044 China Beihang University School of Electronic and Information Engineering Beijing100091 China National Engineering Laboratory for Comprehensive Transportation Big Data Application Technology Beijing100091 China Beijing Jingdong Zhenshi Information Technology Co. Ltd. Logistics RandD Department China Arizona State University School of Sustainable Engineering and the Built Environment TempeAZ85281 United States

ISBN: (纸本)9781538670248

Facing uncertain and dynamic demands over different days, logistics companies need to adopt adaptive solutions for the last-mile delivery. Meanwhile, one of the major barriers for implementing vehicle routing problem (VRP) algorithms in real world dispatching systems is the stability of delivery driver's routes and schedules. To establish a theoretically sound and practically useful solution framework, this paper aims to optimize robust and consistent space-time paths for the multi-day VRP by providing daily schedules with limited variations from the master schedule. A multi-commodity network flow-based optimization model is proposed to minimize generalized transportation costs and the daily deviation of day-dependent space-time paths among demand analysis zones. Lagrange relaxation (LR) methods and alternating direction method of multipliers (ADMM) are used to handle complex side constraints. Experiments on illustrative networks and Beijing delivery network are developed to demonstrate the effectiveness of the proposed method. © 2019 IEEE.

关键词： Vehicle routing

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