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International Conference on transportation Information and Safety (ICTIS)

作者： Lanzhen Jiang Hongtai Yang Rong Zheng Jinghai Huo School of Transportation and Logistics National United Engineering Laboratory of Integrated and Intelligent Transportation National Engineering Laboratory of Integrated Transportation Big Data Application Technology Southwest Jiaotong University Chengdu China

ISBN: (纸本)9781665497145

The COVID-19 pandemic has changed the frequency of tourists using shared bicycles to a certain extent. This paper uses the cycling data of Boston, USA from June 2020 to December 2020, taking users in areas without bicycle sites as tourists. Using customers and subscribers among tourists to share bicycle trip data on a daily basis, taking into account the weather, the built environment of bicycle sites, and the number of COVID-19 cases per week, a negative binomial regression model is used to explore these factors during the epidemic. The relationship between regional customers and subscribers using shared bicycle trips and influencing factors. The results show that, first of all, during the pandemic, there is a double-peak tide phenomenon in the usage of shared bicycles by subscribers among tourists, and customers use more in the evening peak. Secondly, the population density and employment density around bicycle sites have a significant positive impact on the shared bicycle use of customers and subscribers. For every 1% increase in the population, subscriber usage increases by 4.55%, and every 1 % increase in employment Density, customer usage increased by 4.22 %. In addition, the number of bus stations and subway stations has a restraining effect on the use of shared bicycles. Finally, the number of epidemics will increase the usage of customers and subscribers to a certain extent, with subscribers increasing by 0.25% and customer usage increasing by 2.92 %. The research results can timely analyze the usage of bicycles shared by different users among tourists during the pandemic, and can help transportation agencies adjust services in different regions to better control the spread of the virus.

关键词： COVID-19 Pandemics Sociology Employment Bicycles Safety Statistics

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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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Lane-changing decision model for autonomous vehicle under mixed traffic environment 6

Lane-changing decision model for autonomous vehicle under mi...

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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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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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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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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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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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data-driven evacuation and rescue traffic optimization with rescue contraflow control

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Journal of Safety Science and Resilience 2024年第1期5卷 1-12页

作者： Zheng Liu Jialin Liu Xuecheng Shang Xingang Li School of Management Engineering Zhengzhou University of AeronauticsZhengzhou 450046China Collaborative Innovation Center for Aviation Economy Development of Henan Province Zhengzhou University of AeronauticsZhengzhou 450046China School of Systems science Beijing Jiaotong UniversityBeijing 100044China Key Laboratory of Transport Industry of Big Data Application Technologies for Comprehensive Transport Beijing Jiaotong UniversityBeijing 100044China School of Transportation Engineering Shandong Jianzhu UniversityJinan 250101China

In response to local sudden disasters,e.g.,high-rise office or residential building fire disasters,road occupation can cause conflicts,and traffic directions may be opposite between evacuation vehicles and rescue vehicles;moreover,lane contraflow can be adopted to meet these surge traffic ***,lane contraflow that provides more roads for rescue vehicles reduces the traffic supply in the evacuation *** is unclear how to control the number of contraflow roads used by rescue vehicles to coordinate evacuation and rescue traffic ***,we adjust the critical rescue traffic volume of reversing the normal road traffic direction to control rescue ***,we propose a multiobjective mixed integer linear programming formulation for evacuation and rescue traffic ***,considering that the upper limit of the critical rescue traffic volume is unknown and that the proposed formulation includes multiple objectives and multi-priority vehicle classes,a three-stage solving algorithm is ***,a large-scale evacuation and rescue traffic optimization result dataset is obtained for the Nguyen–Dupuis road network,and the impact of different rescue contraflow control plans on evacuation and rescue traffic is studied based on data-driven sta-tistical *** results show that by adjusting the optimal rescue traffic route,the critical rescue traffic volume for reversing the normal road traffic direction can reduce the interference of rescue traffic to evacuation traffic operation performance without reducing rescue traffic operation performance,and can be used to coor-dinate evacuation and rescue traffic operation under rescue contraflow.

关键词： Evacuation and rescue traffic optimization Rescue contraflow control Multiobjective mixed integer linear programming Three-stage solving algorithm data-driven statistical analysis

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An improved cellular automata model of traffic flow with look-ahead potential1

An improved cellular automata model of traffic flow with loo...

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Chinese Automation Congress (CAC)

作者： Xiao Ma Yu-Hu Liu National Engineering Laboratory of Integrated Transportation Big Data Application Technology School of Mathematics Southwest Jiaotong University Chengdu China

ISBN: (纸本)9781665426480

This paper presents an improved automata model for traffic flow based upon models for cellular automata and traffic flow. The proposed model is concerned with the headway and multiple velocities. The proposed model enforces the stochastic rules for moving a car on the basis of traffic in front of it. Rules for updating the velocity of car relies upon the location of the car as well as front traffic and their velocities. In particular, by using numerical simulations, the model proposed in this study can reach the steady-state more quickly for random perturbations.

关键词： Analytical models Perturbation methods Electric shock Automata Stochastic processes Numerical simulation Numerical models

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