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Dr. Yi Zhang
Tsinghua-Berkeley Shenzhen Institute, Tsinghua University, Shenzhen, PR China.

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Research Keywords & Expertise

0 Energy Conservation
0 Transportation Operations
0 Renewable and Sustainable Energy
0 Building energy performance
0 Big data Application in Urban Management

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Short Biography

Dr. Yi Zhang is the research assistant professor in Tsinghua-Berkeley Shenzhen Institute of Tsinghua University. She obtained her PhD Degree from University of Cambridge UK. Before that, she studied in Tsinghua University, China and Imperial College, UK for her Bachelor and MSc Degrees. Her research focuses on big data analysis and intelligent transportation management, electrical vehicles operation theory and methodology, application planning of renewable energy at large scale, coordination energy system for transportation and buildings

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Research article
Published: 05 May 2021 in Transportation Letters
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The environmental traffic assignment problem in the bimodal network with electric vehicles (EVs) and gasoline vehicles (GVs) has become a hot topic recently. However, few previous works consider the psychological difference between EV users and GV users in terms of environmental awareness , in order to fill in this research gap, we formulate an environment-oriented mixed-behavior user equilibrium (EMUE) model to distinguish the route choice criterion between EV users and GV users by considering the Pro-environmental behavior (PEB) of EV users. . We formulate a bi-objective optimization model and propose a differentiable road pricing scheme for EV and GV users to manage the congestion and emissions simultaneously. We investigate whether the differentiable road pricing can decentralize the Pareto-efficient flow as a unique mixed-behavior equilibrium. Moreover, we conduct numerical experiments based on the Sioux Falls network and the existing urban network in Qianhai Zone to evaluate the effectiveness of the proposed pricing scheme, models and algorithms.

ACS Style

Haoning Xi; Liu He; Yi Zhang; Zhen Wang. Differentiable road pricing for environment-oriented electric vehicle and gasoline vehicle users in the bi-objective transportation network. Transportation Letters 2021, 1 -15.

AMA Style

Haoning Xi, Liu He, Yi Zhang, Zhen Wang. Differentiable road pricing for environment-oriented electric vehicle and gasoline vehicle users in the bi-objective transportation network. Transportation Letters. 2021; ():1-15.

Chicago/Turabian Style

Haoning Xi; Liu He; Yi Zhang; Zhen Wang. 2021. "Differentiable road pricing for environment-oriented electric vehicle and gasoline vehicle users in the bi-objective transportation network." Transportation Letters , no. : 1-15.

Journal article
Published: 20 April 2021 in IEEE Access
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Road transportation accounts for significant percentages of urban energy consumption and carbon emissions. Therefore, it is important to predict and analyze the fuel consumption and emissions for on-road vehicles, which are varied under different conditions. Previous studies have shown that some traffic elements such as road type and weather condition have considerable influence on transportation fuel consumption and emissions. However, limited to the data availability, most of the existing studies focus on specific routes or scenarios, and few of them consider the effects of road type and weather condition systematically at large scale. In this research, a data-driven mesoscopic model was developed to investigate the effects of road type and weather condition on the link-level fuel consumption and emission factors based on big traffic data. This built model utilized the neural network for the prediction algorithm with inputs including road type, weather condition, and link-level aggregated operation data obtained through link-based segregation over trajectory snippets. The investigation was carried out with real-world big traffic data collected from 10,944 taxis over a 2-month period of operation in Shenzhen, and produced reliable predictions for four road types with clear and rainy weather conditions. Both statistical analysis and model prediction results showed that fuel consumption and emission factors are lower in low-speed range for freeway and expressway, and are lower in middle-speed range for main road and secondary road. In addition, rainy weather condition tends to have lower fuel consumption and emission factors than clear weather condition.

ACS Style

Rui Shang; Yi Zhang; Zuo-Jun Max Shen. Analyzing the Effects of Road Type and Rainy Weather on Fuel Consumption and Emissions: A Mesoscopic Model Based on Big Traffic Data. IEEE Access 2021, 9, 62298 -62315.

AMA Style

Rui Shang, Yi Zhang, Zuo-Jun Max Shen. Analyzing the Effects of Road Type and Rainy Weather on Fuel Consumption and Emissions: A Mesoscopic Model Based on Big Traffic Data. IEEE Access. 2021; 9 ():62298-62315.

Chicago/Turabian Style

Rui Shang; Yi Zhang; Zuo-Jun Max Shen. 2021. "Analyzing the Effects of Road Type and Rainy Weather on Fuel Consumption and Emissions: A Mesoscopic Model Based on Big Traffic Data." IEEE Access 9, no. : 62298-62315.

Journal article
Published: 16 April 2021 in IEEE Transactions on Intelligent Transportation Systems
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The properties of cooperative driving strategies for planning and controlling Connected and Automated Vehicles (CAVs) at intersections range from some that achieve highly efficient coordination performance to others whose implementation is computationally fast. This paper comprehensively compares the performance of four representative strategies in terms of travel time, energy consumption, computation time, and fairness under different conditions, including the geometric configuration of intersections, asymmetry in traffic arrival rates, and the relative magnitude of these rates. Our simulation-based study has led to the following conclusions: 1) The Monte Carlo Tree Search (MCTS)-based strategy achieves the best traffic efficiency and has great performance in fuel consumption; 2) MCTS and Dynamic Resequencing (DR) strategies both perform well in all metrics of interest. If the computation budget is adequate, the MCTS strategy is recommended; otherwise, the DR strategy is preferable; 3) An asymmetric intersection has a noticeable impact on the strategies, whereas the influence of the arrival rates can be neglected. When the geometric shape is asymmetrical, the modified First-In-First-Out (FIFO) strategy significantly outperforms the FIFO strategy and works well when the traffic demand is moderate, but their performances are similar in other situations; and 4) Improving traffic efficiency sometimes comes at the cost of fairness, but the DR and MCTS strategies can be adjusted to realize a better trade-off between various performance metrics by appropriately designing their objective functions.

ACS Style

Huile Xu; Christos G. Cassandras; Li Li; Yi Zhang. Comparison of Cooperative Driving Strategies for CAVs at Signal-Free Intersections. IEEE Transactions on Intelligent Transportation Systems 2021, PP, 1 -14.

AMA Style

Huile Xu, Christos G. Cassandras, Li Li, Yi Zhang. Comparison of Cooperative Driving Strategies for CAVs at Signal-Free Intersections. IEEE Transactions on Intelligent Transportation Systems. 2021; PP (99):1-14.

Chicago/Turabian Style

Huile Xu; Christos G. Cassandras; Li Li; Yi Zhang. 2021. "Comparison of Cooperative Driving Strategies for CAVs at Signal-Free Intersections." IEEE Transactions on Intelligent Transportation Systems PP, no. 99: 1-14.

Journal article
Published: 30 March 2021 in Accident Analysis & Prevention
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This research is aimed at investigating drivers’ attitudes towards connected vehicle technology in general and two connected vehicle applications in particular—Lane Speed Monitoring and High Speed Differential Warning—which have been demonstrated via simulation to be effective in enhancing traffic mobility and safety, respectively. An online survey was sent to customers of an automobile manufacturer in the United States. Out of the 1453 survey responses that were received, 650 complete and valid responses were used to analyze the respondents’ stated acceptance of and expected behavioral responses to the two connected vehicle applications under a variety of scenarios. Statistical analyses were conducted to examine the influence of demographic and socioeconomic factors. The results reveal that the respondents express high willingness to use connected vehicle technology and the two applications under various circumstances, and the willingness is strongly associated with age, gender, education level, and income. Higher levels of acceptance are observed in older, male, higher-educated, or higher-income respondents, while the patterns of conditional acceptance and expected behavioral responses vary with specific scenarios. These results provide useful information for application developers, traffic operators, and policy makers to steer connected vehicle technology development and deployment in the direction that will benefit both the users and the society.

ACS Style

Weixia Li; Guoyuan Wu; Danya Yao; Yi Zhang; Matthew J. Barth; Kanok Boriboonsomsin. Stated acceptance and behavioral responses of drivers towards innovative connected vehicle applications. Accident Analysis & Prevention 2021, 155, 106095 .

AMA Style

Weixia Li, Guoyuan Wu, Danya Yao, Yi Zhang, Matthew J. Barth, Kanok Boriboonsomsin. Stated acceptance and behavioral responses of drivers towards innovative connected vehicle applications. Accident Analysis & Prevention. 2021; 155 ():106095.

Chicago/Turabian Style

Weixia Li; Guoyuan Wu; Danya Yao; Yi Zhang; Matthew J. Barth; Kanok Boriboonsomsin. 2021. "Stated acceptance and behavioral responses of drivers towards innovative connected vehicle applications." Accident Analysis & Prevention 155, no. : 106095.

Journal article
Published: 22 March 2021 in Sustainability
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The accessibility of transit stops (ATS) is a critical index for the evaluation of transit service, focusing on the first/last mile portions of transit trips. It is significantly affected by feeder modes, such as walking and cycling. Comparison of the application of different modes has been addressed in previous research, thus there is mostly only one feeder mode considered in this case study. This study has proposed a model for ATS with multiple feeder modes (ATSMFM), capable of integrating multiple feeder modes and considering the heterogeneity of travellers from the perspective of city managers. It is a bi-level model, combining cumulative and utility-based approaches. The final form of ATSMFM is developed referring to the cumulative approach, while the determination of the catchment area is utility-based. A numerical experiment has been conducted to demonstrate the necessity and applicability of ATSMFM. The results show that the ATS with a single feeder mode, such as cycling or walking, underestimates the catchment area of nearly one-third or two-thirds of travellers. As for ATSMFM, this proposed approach can automatically select the feeder mode from alternatives according to traveller attributes, thus removing the limitation of a single feeder mode, and is suitable for calculating ATS in the complex environment with multiple feeder modes. Besides, the ATSMFM model can support city managers with different emphases in transit planning via flexibly setting the threshold.

ACS Style

Mingzhu Song; Yi Zhang; Meng Li; Yi Zhang. Accessibility of Transit Stops with Multiple Feeder Modes: Walking and Private-Bike Cycling. Sustainability 2021, 13, 3522 .

AMA Style

Mingzhu Song, Yi Zhang, Meng Li, Yi Zhang. Accessibility of Transit Stops with Multiple Feeder Modes: Walking and Private-Bike Cycling. Sustainability. 2021; 13 (6):3522.

Chicago/Turabian Style

Mingzhu Song; Yi Zhang; Meng Li; Yi Zhang. 2021. "Accessibility of Transit Stops with Multiple Feeder Modes: Walking and Private-Bike Cycling." Sustainability 13, no. 6: 3522.

Journal article
Published: 19 February 2021 in IEEE Transactions on Intelligent Vehicles
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The design of cooperative adaptive cruise control is critical in mixed traffic flow, where connected and automated vehicles (CAVs) and human-driven vehicles (HDVs) coexist. Compared with pure CAVs, the major challenge is how to handle the prediction uncertainty of HDVs, which can cause significant state deviation of CAVs from planned trajectories. In most existing studies, model predictive control (MPC) is utilized to replan CAVs' trajectories to mitigate the deviation at each time step. However, as the replanning process is usually conducted by solving an optimization problem with information through inter-vehicular communication, MPC methods suffer from heavy computational and communicational burdens. To address this limitation, a robust platoon control framework is proposed based on tube MPC in this paper. The prediction uncertainty is dynamically mitigated by the feedback control and restricted inside a set with a high probability. When the uncertainty exceeds the set or additional external disturbance emerges, the feedforward control is triggered to plan a "tube'' (a sequence of sets), which can bound CAVs' actual trajectories. As the replanning process is usually not required, the proposed method is much more efficient regarding computation and communication, compared with the MPC method. Comprehensive simulations are provided to validate the effectiveness of the proposed framework.

ACS Style

Shuo Feng; Ziyou Song; Zhaojian Li; Yi Zhang; Li Li. Robust Platoon Control in Mixed Traffic Flow Based on Tube Model Predictive Control. IEEE Transactions on Intelligent Vehicles 2021, PP, 1 -1.

AMA Style

Shuo Feng, Ziyou Song, Zhaojian Li, Yi Zhang, Li Li. Robust Platoon Control in Mixed Traffic Flow Based on Tube Model Predictive Control. IEEE Transactions on Intelligent Vehicles. 2021; PP (99):1-1.

Chicago/Turabian Style

Shuo Feng; Ziyou Song; Zhaojian Li; Yi Zhang; Li Li. 2021. "Robust Platoon Control in Mixed Traffic Flow Based on Tube Model Predictive Control." IEEE Transactions on Intelligent Vehicles PP, no. 99: 1-1.

Journal article
Published: 05 December 2020 in Energy
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As prediction of trip-based electricity consumption has become an prerequisite for the deployment of large-scale EB fleets, this study has established random forest-based models to systematically investigate the impacts of environmental conditions, route characteristics, and dynamic traffic conditions. The models have been performed on real-world data collected from 1024 EBs over five consecutive months in Shenzhen, China. The results show that considering all the influencing variables can significantly enhance the prediction performance, but comparatively speaking, the route characteristics contribute the most among the three categories and involving more variables demonstrates greater advantages within the trip length under 20km. It is also found that the trip length, the number of bus stops and the number of the traffic lights passed rank the top three most influencing factors, while the wet-dry condition is the least one. In addition, the variations under five operation scenarios show similar trend. The trip length and average travel speed are inversely proportional to the specific electricity consumption, while the number of bus stops visited, traffic lights passed, and ambient temperature exhibit a gentle proportional relationship. Moreover, it is suggested to plan the new bus line over 10 km in terms of reducing electricity consumption per kilometre.

ACS Style

Pengshun Li; Yi Zhang; Kai Zhang; Mengyan Jiang. The effects of dynamic traffic conditions, route characteristics and environmental conditions on trip-based electricity consumption prediction of electric bus. Energy 2020, 218, 119437 .

AMA Style

Pengshun Li, Yi Zhang, Kai Zhang, Mengyan Jiang. The effects of dynamic traffic conditions, route characteristics and environmental conditions on trip-based electricity consumption prediction of electric bus. Energy. 2020; 218 ():119437.

Chicago/Turabian Style

Pengshun Li; Yi Zhang; Kai Zhang; Mengyan Jiang. 2020. "The effects of dynamic traffic conditions, route characteristics and environmental conditions on trip-based electricity consumption prediction of electric bus." Energy 218, no. : 119437.

Journal article
Published: 23 September 2020 in IEEE Transactions on Intelligent Transportation Systems
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How to generate testing scenario libraries for connected and automated vehicles (CAVs) is a major challenge faced by the industry. In previous studies, to evaluate maneuver challenge of a scenario, surrogate models (SMs) are often used without explicit knowledge of the CAV under test. However, performance dissimilarities between the SM and the CAV under test usually exist, and it can lead to the generation of suboptimal scenario libraries. In this article, an adaptive testing scenario library generation (ATSLG) method is proposed to solve this problem. A customized testing scenario library for a specific CAV model is generated through an adaptive process. To compensate for the performance dissimilarities and leverage each test of the CAV, Bayesian optimization techniques are applied with classification-based Gaussian Process Regression and a newly designed acquisition function. Comparing with a pre-determined library, a CAV can be tested and evaluated in a more efficient manner with the customized library. To validate the proposed method, a cut-in case study is investigated and the results demonstrate that the proposed method can further accelerate the evaluation process by a few orders of magnitude.

ACS Style

Shuo Feng; Yiheng Feng; Haowei Sun; Yi Zhang; Henry X. Liu. Testing Scenario Library Generation for Connected and Automated Vehicles: An Adaptive Framework. IEEE Transactions on Intelligent Transportation Systems 2020, PP, 1 -10.

AMA Style

Shuo Feng, Yiheng Feng, Haowei Sun, Yi Zhang, Henry X. Liu. Testing Scenario Library Generation for Connected and Automated Vehicles: An Adaptive Framework. IEEE Transactions on Intelligent Transportation Systems. 2020; PP (99):1-10.

Chicago/Turabian Style

Shuo Feng; Yiheng Feng; Haowei Sun; Yi Zhang; Henry X. Liu. 2020. "Testing Scenario Library Generation for Connected and Automated Vehicles: An Adaptive Framework." IEEE Transactions on Intelligent Transportation Systems PP, no. 99: 1-10.

Journal article
Published: 28 August 2020 in Applied Sciences
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A ground source heat pump system is a highly efficient renewable heating, cooling, and ventilation system that utilizes the ground as a heat source or sink via ground heat exchangers. Energy pile is an energy geotechnical structure that couples a ground heat exchanger with a geotechnical structure, leading to low capital cost. The design of energy piles can be challengeable due to their complicated geometries and the requirement of mechanical load. This study focuses on the heat transfer across the concrete–soil interface of energy piles in urban areas. Case studies from two projects, the Lambeth College and Shell Centre projects, are presented and discussed. The back analysis of two energy pile cases illustrated that the heat transfer coefficient at the pile–soil interface can differ between the cooling mode and the heating mode. It can be concluded that the difference in the heat transfer coefficient is influenced by a number of factors such as soil properties, concrete (grout) properties, and the installation method.

ACS Style

He Qi; Yu Zhou; Zhonghua Zhang; Bo Wang; Yi Zhang; Hongzhi Cui; Xi Wang. Heat Transfer Performance in Energy Piles in Urban Areas: Case Studies for Lambeth College and Shell Centre UK. Applied Sciences 2020, 10, 5974 .

AMA Style

He Qi, Yu Zhou, Zhonghua Zhang, Bo Wang, Yi Zhang, Hongzhi Cui, Xi Wang. Heat Transfer Performance in Energy Piles in Urban Areas: Case Studies for Lambeth College and Shell Centre UK. Applied Sciences. 2020; 10 (17):5974.

Chicago/Turabian Style

He Qi; Yu Zhou; Zhonghua Zhang; Bo Wang; Yi Zhang; Hongzhi Cui; Xi Wang. 2020. "Heat Transfer Performance in Energy Piles in Urban Areas: Case Studies for Lambeth College and Shell Centre UK." Applied Sciences 10, no. 17: 5974.

Journal article
Published: 11 August 2020 in Applied Sciences
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To meet long-term climate change targets, the way that heating and cooling are generated and distributed has to be changed to achieve a supply of affordable, secure and low-carbon energy for all buildings and infrastructures. Among the possible renewable sources of energy, ground source heat pump (GSHP) systems can be an effective low-carbon solution that is compatible with district heating and cooling in urban areas. There are no location restrictions for this technology, and underground energy sources are stable for long-term use. According to a previous study, buildings in urban areas have demonstrated significant spatial heterogeneity in terms of their capacity to demand (C/D) ratio under the application of GSHP due to variations in heating demand and available space. If a spatial sharing strategy can be developed to allow the surplus geothermal capacity to be shared with neighbors, the heating and cooling demands of a greater number of buildings in an area can be satisfied, thus achieving a city with lower carbon emissions. In this study, a GSHP district system model was developed with a specific embedding sharing strategy for the application of GSHP. Two sharing strategies were proposed in this study: (i) Strategy 1 involved individual systems with borehole sharing, and (ii) Strategy 2 was a central district system. Three districts in London were selected to compare the performance of the developed models on the C/D ratio, required borehole number and carbon emissions. According to the comparison analysis, both strategies were able to enhance the GSHP application capacity and increase the savings of carbon emissions. However, the improvement levels were shown to be different. A greater number of building types and a higher variety in building types with larger differentiation in heating and cooling demands can contribute to a better district sharing performance. In addition, it was found that these two sharing strategies were applicable to different kinds of districts.

ACS Style

Yi Zhang; He Qi; Yu Zhou; Zhonghua Zhang; Xi Wang. Exploring the Impact of a District Sharing Strategy on Application Capacity and Carbon Emissions for Heating and Cooling with GSHP Systems. Applied Sciences 2020, 10, 5543 .

AMA Style

Yi Zhang, He Qi, Yu Zhou, Zhonghua Zhang, Xi Wang. Exploring the Impact of a District Sharing Strategy on Application Capacity and Carbon Emissions for Heating and Cooling with GSHP Systems. Applied Sciences. 2020; 10 (16):5543.

Chicago/Turabian Style

Yi Zhang; He Qi; Yu Zhou; Zhonghua Zhang; Xi Wang. 2020. "Exploring the Impact of a District Sharing Strategy on Application Capacity and Carbon Emissions for Heating and Cooling with GSHP Systems." Applied Sciences 10, no. 16: 5543.

Journal article
Published: 30 July 2020 in Sustainability
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The presence of bike-sharing has a significant influence on the ease of trips by bike, which is one critical aspect of bicycling accessibility (BAcc). The existing measurements of BAcc rarely consider the factor of ownership of bikes, which means that no distinction is made between private-bikes and shared bikes. To measure BAcc more fully, this paper proposes a method to evaluate the influences of bike-sharing on BAcc and to perform the method on a real-world case study in Beijing. It is found that bike-sharing has a boosting effect on BAcc, and the increased rate of BAcc is significantly affected by bicycling frequency and shared-bike availability. A case study in Beijing utilizing geo-location data collected from two major bike-sharing companies (OFO and Mo-bike) illustrates the significance of the impact of bike-sharing on BAcc and the necessity to include bike-sharing in the measurement of BAcc. Besides, the case study shows BAcc around the transit station is better than that over the whole area. Given that bicycling feeds transit, this research lays the foundation for analyzing the combination of bike-sharing and transit from the perspective of accessibility and can further support transportation planning.

ACS Style

Mingzhu Song; Kaiping Wang; Yi Zhang; Meng Li; Qi He; Yi Zhang. Impact Evaluation of Bike-Sharing on Bicycling Accessibility. Sustainability 2020, 12, 6124 .

AMA Style

Mingzhu Song, Kaiping Wang, Yi Zhang, Meng Li, Qi He, Yi Zhang. Impact Evaluation of Bike-Sharing on Bicycling Accessibility. Sustainability. 2020; 12 (15):6124.

Chicago/Turabian Style

Mingzhu Song; Kaiping Wang; Yi Zhang; Meng Li; Qi He; Yi Zhang. 2020. "Impact Evaluation of Bike-Sharing on Bicycling Accessibility." Sustainability 12, no. 15: 6124.

Journal article
Published: 18 June 2020 in Transportation Research Part D: Transport and Environment
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A signal priority strategy (SPS) is implemented to encourage the development of public transportation, but this strategy may delay other vehicles to produce more emissions, especially at intersection. This study aims to develop an intersection energy consumption and emissions model framework with an embedded SPS to analyse the impacts of the SPS on the intersection. To validate this model framework, an intersection in Shenzhen, China was selected for simulation as a case study. In this study, we compared the effects of an active SPS, a real-time SPS and the real-time SPS improved under Intelligent Vehicle Infrastructure Cooperation System (i-VICS) on the energy consumption and emissions of the targeted intersection. The simulation results illustrate that, the active strategy could decrease fuel consumption and emissions with a maximum reduction of 13.33% in fuel consumption, and the real-time strategy maintains a smooth fluctuation in the total fuel consumption and emissions during the entire period. Compared with the two in-use strategies, the i-VICS-based transit priority strategy demonstrates the best environmental performance, by reducing the greatest negative environmental influences and cutting down the most emissions of nearly 28.86% in the case study. The developed intersection energy consumption and emissions model framework can be applied to evaluation of different SPSs on the environment respect, which can benefit to urban transportation management in a more sustainable way.

ACS Style

Haofei Liu; Yi Zhang; Kai Zhang. Evaluating impacts of intelligent transit priority on intersection energy and emissions. Transportation Research Part D: Transport and Environment 2020, 86, 102416 .

AMA Style

Haofei Liu, Yi Zhang, Kai Zhang. Evaluating impacts of intelligent transit priority on intersection energy and emissions. Transportation Research Part D: Transport and Environment. 2020; 86 ():102416.

Chicago/Turabian Style

Haofei Liu; Yi Zhang; Kai Zhang. 2020. "Evaluating impacts of intelligent transit priority on intersection energy and emissions." Transportation Research Part D: Transport and Environment 86, no. : 102416.

Journal article
Published: 15 June 2020 in Sustainability
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In recent years, with the rapid development of China’s automobile industry, the number of vehicles in China has been increasing steadily. Vehicles represent a convenient mode of travel, but the growth rate of the number of urban motor vehicles far exceeds the construction rate of parking facilities. The continuous improvement of parking allocation methods has always been key for ensuring sustainable city management. Thus, developing an efficient and dynamic parking distribution algorithm will be an important breakthrough to alleviate the urban parking shortage problem. However, the existing parking distribution models do not adequately consider the influence of real-time changes in parking demand and supply on parking space assignment. Therefore, this study proposed a method for dynamic parking allocation using parking demand predictions and a predictive control method. A neural-network-based dynamic parking distribution model was developed considering seven influencing factors: driving duration, walking distance, parking fee, traffic congestion, possibility of finding a parking space in the target parking lot and adjacent parking lot, and parking satisfaction degree. Considering whether the parking spaces in the targeted parking lots are shared or not, two allocation modes—sharing mode and non-sharing mode—were proposed and embedded into the model. At the experimental stage, a simulation case and a real-time case were performed to evaluate the developed models. The experimental results show that the dynamic parking distribution model based on neural networks can not only allocate parking spaces in real time but also improve the utilisation rate of different types of parking spaces. The performance score of the dynamic parking distribution model for a time interval of 2–20 min was maintained above 80%. In addition, the distribution performance of the sharing mode was better than that of the non-sharing mode and contributed to a better overall effectiveness. This model can effectively improve the utilisation rate of resources and the uniformity of distribution and can reduce the failure rate of parking; thus, it significantly contributes to more smart and sustainable urban parking management.

ACS Style

Ziyao Zhao; Yi Zhang; Yi Zhang; Kaifeng Ji; He Qi. Neural-Network-Based Dynamic Distribution Model of Parking Space Under Sharing and Non-Sharing Modes. Sustainability 2020, 12, 4864 .

AMA Style

Ziyao Zhao, Yi Zhang, Yi Zhang, Kaifeng Ji, He Qi. Neural-Network-Based Dynamic Distribution Model of Parking Space Under Sharing and Non-Sharing Modes. Sustainability. 2020; 12 (12):4864.

Chicago/Turabian Style

Ziyao Zhao; Yi Zhang; Yi Zhang; Kaifeng Ji; He Qi. 2020. "Neural-Network-Based Dynamic Distribution Model of Parking Space Under Sharing and Non-Sharing Modes." Sustainability 12, no. 12: 4864.

Journal article
Published: 04 May 2020 in IEEE Transactions on Intelligent Transportation Systems
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ACS Style

Shuo Feng; Yiheng Feng; Haowei Sun; Shan Bao; Yi Zhang; Henry X. Liu. Testing Scenario Library Generation for Connected and Automated Vehicles, Part II: Case Studies. IEEE Transactions on Intelligent Transportation Systems 2020, 1 -13.

AMA Style

Shuo Feng, Yiheng Feng, Haowei Sun, Shan Bao, Yi Zhang, Henry X. Liu. Testing Scenario Library Generation for Connected and Automated Vehicles, Part II: Case Studies. IEEE Transactions on Intelligent Transportation Systems. 2020; ():1-13.

Chicago/Turabian Style

Shuo Feng; Yiheng Feng; Haowei Sun; Shan Bao; Yi Zhang; Henry X. Liu. 2020. "Testing Scenario Library Generation for Connected and Automated Vehicles, Part II: Case Studies." IEEE Transactions on Intelligent Transportation Systems , no. : 1-13.

Research article
Published: 16 April 2020 in IET Intelligent Transport Systems
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Real-time, on-demand mobility systems have gradually revolutionised the transportation means. However, they continue to exhibit problems on inadequate vehicles at peak times. The popularity of ‘sharing’ may ultimately solve such problems as more passengers are served over time, particularly in high-demand (high-density) locations, thereby realising efficient, comfortable, and environmentally friendly transportation. While, existing sharing methods only arrange each order based on current information and do not apply subsequently received information to pursue more optimal route arrangements. Their research explicitly improves large-scale vehicle sharing methods using subsequent information and proposes the concept of a ‘wait time threshold ’ for a vehicle, to manage the constraint contradictions in this process. Based on a representative high-demand case of serving all inbound and outbound passengers at Shenzhen Bao’ an International Airport, a system with consideration of subsequent information provides significant improvements comparing to a system without it. The improvement performance varies with dates under different demand scenarios, high demand indicating a more optimistic influence. Therefore, having such a city-scale sharing model makes it possible to provide decision support to the transportation management department, which encourages to establish a low carbon city.

ACS Style

Yanglan Wang; Yi Zhang; Jiangshan Ma. Dynamic real‐time high‐capacity ride‐sharing model with subsequent information. IET Intelligent Transport Systems 2020, 14, 742 -752.

AMA Style

Yanglan Wang, Yi Zhang, Jiangshan Ma. Dynamic real‐time high‐capacity ride‐sharing model with subsequent information. IET Intelligent Transport Systems. 2020; 14 (7):742-752.

Chicago/Turabian Style

Yanglan Wang; Yi Zhang; Jiangshan Ma. 2020. "Dynamic real‐time high‐capacity ride‐sharing model with subsequent information." IET Intelligent Transport Systems 14, no. 7: 742-752.

Journal article
Published: 18 March 2020 in IEEE Access
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There are generally two kinds of traffic control strategies to relieve traffic congestion in lane-drop bottlenecks: variable speed limits (VSL) control and lane-changing (LC) control. However, VSL has limited or even no effect due to many mandatory LC maneuvers near bottlenecks, while LC fails to reduce traffic congestion when traffic demand is high. Although a few control methods combine VSL and LC, they do not consider the interaction between VSL and LC, which rules out many potentially good alternatives. We instead propose an integrated VSL and LC control method under a connected and automated vehicle (CAV) environment, which can consider the interaction and simultaneously find the values of LC numbers and speed limits to maximize traffic efficiency. Our control is in the framework of the model predictive control (MPC), which consists of prediction, optimization, and implementation. We adopt an improved multi-class cell transmission model (CTM) for traffic state prediction, then use the genetic algorithm (GA) for optimization which optimizes traffic network performance, and implement our control method in the SUMO platform. Simulation results demonstrate that our control method greatly improves the capacity of the road and is robust to different traffic demands and scenarios. Our control outperforms no control and VSL-only control in travel time and exhaust emissions, which reduces total travel time by 23.86% to 44.62% and exhaust emissions by 10.29% to 48.19%.

ACS Style

Yuqing Guo; Huile Xu; Yi Zhang; Danya Yao. Integrated Variable Speed Limits and Lane-Changing Control for Freeway Lane-Drop Bottlenecks. IEEE Access 2020, 8, 54710 -54721.

AMA Style

Yuqing Guo, Huile Xu, Yi Zhang, Danya Yao. Integrated Variable Speed Limits and Lane-Changing Control for Freeway Lane-Drop Bottlenecks. IEEE Access. 2020; 8 (99):54710-54721.

Chicago/Turabian Style

Yuqing Guo; Huile Xu; Yi Zhang; Danya Yao. 2020. "Integrated Variable Speed Limits and Lane-Changing Control for Freeway Lane-Drop Bottlenecks." IEEE Access 8, no. 99: 54710-54721.

Journal article
Published: 14 February 2020 in Journal of Advanced Transportation
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Parking issues have been receiving increasing attention. An accurate parking occupancy prediction is considered to be a key prerequisite to optimally manage limited parking resources. However, parking prediction research that focuses on estimating the occupancy for various parking lots, which is critical to the coordination management of multiple parks (e.g., district-scale or city-scale), is relatively limited. This study aims to analyse the performance of different prediction methods with regard to parking occupancy, considering parking type and parking scale. Two forecasting methods, FM1 and FM2, and four predicting models, linear regression (LR), support vector machine (SVR), backpropagation neural network (BPNN), and autoregressive integrated moving average (ARIMA), were proposed to build models that can predict the parking occupancy of different parking lots. To compare the predictive performances of these models, real-world data of four parks in Shenzhen, Shanghai, and Dongguan were collected over 8 weeks to estimate the correlation between the parking lot attributes and forecast results. As per the case studies, among the four models considered, SVM offers stable and accurate prediction performance for almost all types and scales of parking lots. For commercial, mixed functional, and large-scale parking lots, FM1 with SVM made the best prediction. For office and medium-scale parking lots, FM2 with SVM made the best prediction.

ACS Style

Ziyao Zhao; Yi Zhang. A Comparative Study of Parking Occupancy Prediction Methods considering Parking Type and Parking Scale. Journal of Advanced Transportation 2020, 2020, 1 -12.

AMA Style

Ziyao Zhao, Yi Zhang. A Comparative Study of Parking Occupancy Prediction Methods considering Parking Type and Parking Scale. Journal of Advanced Transportation. 2020; 2020 ():1-12.

Chicago/Turabian Style

Ziyao Zhao; Yi Zhang. 2020. "A Comparative Study of Parking Occupancy Prediction Methods considering Parking Type and Parking Scale." Journal of Advanced Transportation 2020, no. : 1-12.

Journal article
Published: 13 February 2020 in IEEE Transactions on Intelligent Transportation Systems
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Testing and evaluation is a critical step in the development and deployment of connected and automated vehicles (CAVs), and yet there is no systematic framework to generate testing scenario library. This study aims to provide a general framework for the testing scenario library generation (TSLG) problem with different operational design domains (ODDs), CAV models, and performance metrics. Given an ODD, the testing scenario library is defined as a critical set of scenarios that can be used for CAV test. Each testing scenario is evaluated by a newly proposed measure, scenario criticality, which can be computed as a combination of maneuver challenge and exposure frequency. To search for critical scenarios, an auxiliary objective function is designed, and a multi-start optimization method along with seed-filling is applied. Theoretical analysis suggests that the proposed framework can obtain accurate evaluation results with much fewer number of tests, if compared with the on-road test method. In part II of the study, three case studies are investigated to demonstrate the proposed method. Reinforcement learning based technique is applied to enhance the searching method under high-dimensional scenarios.

ACS Style

Shuo Feng; Yiheng Feng; Chunhui Yu; Yi Zhang; Henry X. Liu. Testing Scenario Library Generation for Connected and Automated Vehicles, Part I: Methodology. IEEE Transactions on Intelligent Transportation Systems 2020, 22, 1573 -1582.

AMA Style

Shuo Feng, Yiheng Feng, Chunhui Yu, Yi Zhang, Henry X. Liu. Testing Scenario Library Generation for Connected and Automated Vehicles, Part I: Methodology. IEEE Transactions on Intelligent Transportation Systems. 2020; 22 (3):1573-1582.

Chicago/Turabian Style

Shuo Feng; Yiheng Feng; Chunhui Yu; Yi Zhang; Henry X. Liu. 2020. "Testing Scenario Library Generation for Connected and Automated Vehicles, Part I: Methodology." IEEE Transactions on Intelligent Transportation Systems 22, no. 3: 1573-1582.

Journal article
Published: 25 September 2019 in IEEE Transactions on Intelligent Transportation Systems
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In this paper, we propose a new cooperative driving strategy for connected and automated vehicles (CAVs) at unsignalized intersections. Based on the tree representation of the solution space for the passing order, we combine Monte Carlo tree search (MCTS) and some heuristic rules to find a nearly global-optimal passing order (leaf node) within a very short planning time. Testing results show that this new strategy can keep a good tradeoff between performance and computation flexibility.

ACS Style

Huile Xu; Yi Zhang; Li Li; Weixia Li. Cooperative Driving at Unsignalized Intersections Using Tree Search. IEEE Transactions on Intelligent Transportation Systems 2019, 21, 4563 -4571.

AMA Style

Huile Xu, Yi Zhang, Li Li, Weixia Li. Cooperative Driving at Unsignalized Intersections Using Tree Search. IEEE Transactions on Intelligent Transportation Systems. 2019; 21 (11):4563-4571.

Chicago/Turabian Style

Huile Xu; Yi Zhang; Li Li; Weixia Li. 2019. "Cooperative Driving at Unsignalized Intersections Using Tree Search." IEEE Transactions on Intelligent Transportation Systems 21, no. 11: 4563-4571.

Journal article
Published: 22 July 2019 in IEEE Transactions on Intelligent Transportation Systems
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Connected and automated vehicles (CAVs) show great potential to improve both traffic efficiency and safety by sharing information. This paper addresses the problem of coordinating two strings of vehicles at highway on-ramps efficiently and safely in the longitudinal direction. A rule-based adjusting algorithm is proposed to achieve a near-optimal merging sequence for vehicles coming from the mainline and entering through the ramp. Optimality analysis indicates that the proposed method performs very well compared with the global optimal solutions. Furthermore, to investigate the effectiveness and robustness of the proposed method, simulation-based case studies are carried out under both balanced and unbalanced scenarios. The results are compared with two other control strategies (i.e., rule-based methods and optimization-based methods) in terms of throughput, delay, computational cost, and fuel consumption.

ACS Style

Jishiyu Ding; Li Li; Huei Peng; Yi Zhang. A Rule-Based Cooperative Merging Strategy for Connected and Automated Vehicles. IEEE Transactions on Intelligent Transportation Systems 2019, 21, 3436 -3446.

AMA Style

Jishiyu Ding, Li Li, Huei Peng, Yi Zhang. A Rule-Based Cooperative Merging Strategy for Connected and Automated Vehicles. IEEE Transactions on Intelligent Transportation Systems. 2019; 21 (8):3436-3446.

Chicago/Turabian Style

Jishiyu Ding; Li Li; Huei Peng; Yi Zhang. 2019. "A Rule-Based Cooperative Merging Strategy for Connected and Automated Vehicles." IEEE Transactions on Intelligent Transportation Systems 21, no. 8: 3436-3446.