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Daniel (Jian) Sun
Smart City and Intelligent Transportation Interdisciplinary Center, School of Design, Shanghai Jiao Tong University, No. 800 Dongchuan Road, Min-Hang District, Shanghai 200240, China

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Journal article
Published: 15 May 2021 in Atmospheric Pollution Research
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Evaluating the performance of air quality models for roadside traffic exhaust dispersion is critical to sustainable environmental development and urban pollution management. This study introduces three models, namely CAL3QHC, ENVI-met and ANSYS Fluent, to model the pollutant dispersion at an isolated busy urban signalized intersection, by taking fine particulate matter (PM2.5) as the subject matter. A dynamic emission factor model was established based on Cell Transmission Model (CTM) and Portable Emission Measurement System (PEMS) experiment, which was further implemented with the User Defined Function (UDF) of ANSYS Fluent. Results from an empirical study based on the Jianchuan and Humin Road intersection, in suburb Shanghai, demonstrate that ANSYS Fluent performs better for PM2.5 concentration prediction with carefully calibrated parameter settings. Simulation results from both CAL3QHC and ANSYS Fluent are within an acceptable scale, while ENVI-met performs better in assessing the correlation relationships between PM concentrations and the intersectional and meteorological factors. The concentration of PM2.5 was found to increase significantly during the idle phase, which tends to be accumulated in front of the intersection buildings simultaneously. With the increasing of the altitude, the overall average PM2.5 concentration of the intersection decreases gradually. Street canyons with high buildings were found with comparable lower wind speeds, hindering the pollutant diffusion. Finds of this study may assist urban intersection design from a variety of perspectives, e.g., lane channelization, signal timing, and even architecture styles of the surrounding buildings.

ACS Style

Daniel (Jian) Sun; Shaojie Wu; Suwan Shen; Tiandong Xu. Simulation and assessment of traffic pollutant dispersion at an urban signalized intersection using multiple platforms. Atmospheric Pollution Research 2021, 12, 101087 .

AMA Style

Daniel (Jian) Sun, Shaojie Wu, Suwan Shen, Tiandong Xu. Simulation and assessment of traffic pollutant dispersion at an urban signalized intersection using multiple platforms. Atmospheric Pollution Research. 2021; 12 (7):101087.

Chicago/Turabian Style

Daniel (Jian) Sun; Shaojie Wu; Suwan Shen; Tiandong Xu. 2021. "Simulation and assessment of traffic pollutant dispersion at an urban signalized intersection using multiple platforms." Atmospheric Pollution Research 12, no. 7: 101087.

Research article
Published: 10 April 2021 in Journal of Advanced Transportation
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During the last twenty years, the complex network modeling approach has been introduced to assess the reliability of rail transit networks, in which the dynamic performance involving passenger flows have attracted more attentions during operation stages recently. This paper proposes the passenger-flow-weighted network reliability evaluation indexes, to assess the impact of passenger flows on network reliability. The reliability performances of the rail transit network and passenger-flow-weighted one are analyzed from the perspective of a complex network. The actual passenger flow weight of urban transit network nodes was obtained from the Shanghai Metro public transportation card data, which were used to assess the reliability of the passenger-flow-weighted network. Furthermore, the dynamic model of the Shanghai urban rail transit network was constructed based on the coupled map lattice (CML) model. Then, the processes of cascading failure caused by network nodes under different destructive situations were simulated, to measure the changes of passenger-flow-weighted network reliability during the processes. The results indicate that when the scale of network damage attains 50%, the reliability of the passenger-flow-weighted network approaches zero. Consequently, taking countermeasures during the initial stage of network cascading may effectively prevent the disturbances from spreading in the network. The results of the paper could provide guidelines for operation management, as well as identify the unreliable stations within passenger-flow-weighted networks.

ACS Style

Shaojie Wu; Yan Zhu; Ning Li; Yizeng Wang; Xingju Wang; Daniel Jian Sun. Urban Rail Transit System Network Reliability Analysis Based on a Coupled Map Lattice Model. Journal of Advanced Transportation 2021, 2021, 1 -9.

AMA Style

Shaojie Wu, Yan Zhu, Ning Li, Yizeng Wang, Xingju Wang, Daniel Jian Sun. Urban Rail Transit System Network Reliability Analysis Based on a Coupled Map Lattice Model. Journal of Advanced Transportation. 2021; 2021 ():1-9.

Chicago/Turabian Style

Shaojie Wu; Yan Zhu; Ning Li; Yizeng Wang; Xingju Wang; Daniel Jian Sun. 2021. "Urban Rail Transit System Network Reliability Analysis Based on a Coupled Map Lattice Model." Journal of Advanced Transportation 2021, no. : 1-9.

Journal article
Published: 24 October 2020 in Transportmetrica A: Transport Science
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ACS Style

Yizhe Huang; Daniel(Jian) Sun; Aoyong Li; Kay W. Axhausen. Impact of bicycle traffic on the macroscopic fundamental diagram: some empirical findings in Shanghai. Transportmetrica A: Transport Science 2020, 17, 1122 -1149.

AMA Style

Yizhe Huang, Daniel(Jian) Sun, Aoyong Li, Kay W. Axhausen. Impact of bicycle traffic on the macroscopic fundamental diagram: some empirical findings in Shanghai. Transportmetrica A: Transport Science. 2020; 17 (4):1122-1149.

Chicago/Turabian Style

Yizhe Huang; Daniel(Jian) Sun; Aoyong Li; Kay W. Axhausen. 2020. "Impact of bicycle traffic on the macroscopic fundamental diagram: some empirical findings in Shanghai." Transportmetrica A: Transport Science 17, no. 4: 1122-1149.

Journal article
Published: 02 October 2020 in Journal of Cleaner Production
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With the increasing urbanization and motorization, transportation has become one of the primary sources of carbon emission and air pollution, causing serious diseases to city residents. This study focuses on assessing pollutant dispersion patterns under multi-scenario situations and verifying the effectiveness of computational fluid dynamics (CFD) numerical simulation model using wind tunnel experiments and field measurements. A single-vehicle model was built to obtain the spatiotemporal distribution of Carbon Monoxide (CO) concentrations around the vehicle. Pressure coefficients of monitoring points were measured to compare with the values from the wind tunnel test. Then, numerical simulations were extended to car-following platoon and empirical street canyon scenarios. On-site measurements were carried out to ensure that the CFD model reflects the actual flow field around a vehicle in a certain precision range for given experimental design. The results indicated that the traffic-related pollutants were concentrated in the semicircle with the exhaust pipe as the center, with a radius of 1.5m behind the vehicle. The podium building structure in the street perpendicular to the prevailing wind direction tends to induce the deposition of pollutants at the corner and bottom of the podium. Exhaust concentration at the right-angle area of a podium building on the leeward side of the wind direction is 221.1% higher than that in the windward side. Findings of this study may shed light on the street architecture design and the future applications of CFD model to estimate pollutant concentration along urban street canyons, thus to eventually improve urban environmental sustainability.

ACS Style

Daniel(Jian) Sun; Xueqing Shi; Ying Zhang; Lihui Zhang. Spatiotemporal distribution of traffic emission based on wind tunnel experiment and computational fluid dynamics (CFD) simulation. Journal of Cleaner Production 2020, 282, 124495 .

AMA Style

Daniel(Jian) Sun, Xueqing Shi, Ying Zhang, Lihui Zhang. Spatiotemporal distribution of traffic emission based on wind tunnel experiment and computational fluid dynamics (CFD) simulation. Journal of Cleaner Production. 2020; 282 ():124495.

Chicago/Turabian Style

Daniel(Jian) Sun; Xueqing Shi; Ying Zhang; Lihui Zhang. 2020. "Spatiotemporal distribution of traffic emission based on wind tunnel experiment and computational fluid dynamics (CFD) simulation." Journal of Cleaner Production 282, no. : 124495.

Journal article
Published: 25 September 2020 in Sustainability
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The prevention and control of COVID-19 in megacities is under large pressure because of tens of millions and high-density populations. The majority of epidemic prevention and control policies implemented focused on travel restrictions, which severely affected urban mobility during the epidemic. Considering the impacts of epidemic and associated control policies, this study analyzes the relationship between COVID-19, travel of residents, Point of Interest (POI), and social activities from the perspective of taxi travel. First, changes in the characteristics of taxi trips at different periods were analyzed. Next, the relationship between POIs and taxi travels was established by the Geographic Information System (GIS) method, and the spatial lag model (SLM) was introduced to explore the changes in taxi travel driving force. Then, a social activities recovery level evaluation model was proposed based on the taxi travel datasets to evaluate the recovery of social activities. The results demonstrated that the number of taxi trips dropped sharply, and the travel speed, travel time, and spatial distribution of taxi trips had been significantly influenced during the epidemic period. The spatial correlation between taxi trips was gradually weakened after the outbreak of the epidemic, and the consumption travel demand of people significantly decreased while the travel demand for community life increased dramatically. The evaluation score of social activity is increased from 8.12 to 74.43 during the post-epidemic period, which may take 3–6 months to be fully recovered as a normal period. Results and models proposed in this study may provide references for the optimization of epidemic control policies and recovery of public transport in megacities during the post-epidemic period.

ACS Style

Guangyue Nian; Bozhezi Peng; Daniel Sun; Wenjun Ma; Bo Peng; Tian-Yuan Huang. Impact of COVID-19 on Urban Mobility during Post-Epidemic Period in Megacities: From the Perspectives of Taxi Travel and Social Vitality. Sustainability 2020, 12, 7954 .

AMA Style

Guangyue Nian, Bozhezi Peng, Daniel Sun, Wenjun Ma, Bo Peng, Tian-Yuan Huang. Impact of COVID-19 on Urban Mobility during Post-Epidemic Period in Megacities: From the Perspectives of Taxi Travel and Social Vitality. Sustainability. 2020; 12 (19):7954.

Chicago/Turabian Style

Guangyue Nian; Bozhezi Peng; Daniel Sun; Wenjun Ma; Bo Peng; Tian-Yuan Huang. 2020. "Impact of COVID-19 on Urban Mobility during Post-Epidemic Period in Megacities: From the Perspectives of Taxi Travel and Social Vitality." Sustainability 12, no. 19: 7954.

Journal article
Published: 19 August 2020 in Building and Environment
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As an important component of urban roads, signalized intersections have contributed significantly to motor vehicle emissions, which however has not been modelled in high accuracy. This paper uses the International Vehicle Emission (IVE) model to obtain the localized emission factors, so that a dispersion model, CAL3QHC was introduced and modified to incorporate the vehicle acceleration and deceleration states. Two emission reduction schemes for urban signalized intersections, the Green Light Optimal Speed Advisory (GLOSA) system and the no-obstacle driveway design, were proposed, by taking the intersection of Wen'er West Road and Liangmu Road in Hangzhou, China as an empirical example. The overall performance and roadside emission dispersion were simulated using VISSIM software package, with the improved CAL3QHC model. The GLOSA system and the no-obstacle driveway design were found to mitigate the roadside CO concentration by 21.2% and 22.1%, respectively. Findings of the study may assist to monitor roadside pollutant concentrations, formulate and evaluate emission mitigation strategies in urban intersections.

ACS Style

Daniel (Jian) Sun; Zhiwei Yin; Peng Cao. An improved CAL3QHC model and the application in vehicle emission mitigation schemes for urban signalized intersections. Building and Environment 2020, 183, 107213 .

AMA Style

Daniel (Jian) Sun, Zhiwei Yin, Peng Cao. An improved CAL3QHC model and the application in vehicle emission mitigation schemes for urban signalized intersections. Building and Environment. 2020; 183 ():107213.

Chicago/Turabian Style

Daniel (Jian) Sun; Zhiwei Yin; Peng Cao. 2020. "An improved CAL3QHC model and the application in vehicle emission mitigation schemes for urban signalized intersections." Building and Environment 183, no. : 107213.

Journal article
Published: 28 July 2020 in Transport Policy
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During the passing decade, taxi floating car data (FCD) has become an important tool to investigate urban trip choice behaviors and activities. The corresponding taxi exhaust reduction issue is also with rather significance for traffic emission mitigation in urban areas. By taking Shanghai as an empirical case, this paper analyzed the spatiotemporal characteristics of multimode travelers by combining the taxi FCD (from Qiangsheng Inc.), the metro smartcard data and the GPS trajectories of Mobike, one of the most popular shared bicycles in China, 2018). Binomial logit models (BNL) were proposed to estimate mode choices for both peak and off-peak periods by incorporating socio-economic, demographic, urban morphology, land use properties, and various trip-related variables. The choices between metro and taxi, Mobike and taxi were analyzed, respectively, with the corresponding influential factors identified. The results indicated that the percentage of residential and commercial land uses, the number of educational facilities have significant impacts on travel mode choice during peak hours, while the percentage of commercial land, the number of hospitals and bus lines are more prominent during off-peak periods. To quantify the emission reduction benefits, localized calculation of automobile exhaust was established according to the Vehicle Specific Power (VSP) based measurements obtained from the Portable Emission Measurement System (PEMS) experiments. Then, five corresponding emission mitigation schemes were proposed based on the model findings, and the cost-benefit of each countermeasure was further analyzed. Comparing with releasing the peak-hour crowdedness of metro stations, increasing Mobike supply, updating taxis into electric vehicles, and equipping taxis with catalytic converters, the scheme of removing non-motor vehicle restrictions was found with the shortest payback period and was consequently recommended as accordance with the proposal of urban eco and non-motorized transportation. Findings of this study is useful for transportation management in improving the mode share of metro and bicycles, thus to alleviate the congestion and auto emissions in urban areas.

ACS Style

Fangxi Chen; Zhiwei Yin; Yingwei Ye; Daniel(Jian) Sun. Taxi hailing choice behavior and economic benefit analysis of emission reduction based on multi-mode travel big data. Transport Policy 2020, 97, 73 -84.

AMA Style

Fangxi Chen, Zhiwei Yin, Yingwei Ye, Daniel(Jian) Sun. Taxi hailing choice behavior and economic benefit analysis of emission reduction based on multi-mode travel big data. Transport Policy. 2020; 97 ():73-84.

Chicago/Turabian Style

Fangxi Chen; Zhiwei Yin; Yingwei Ye; Daniel(Jian) Sun. 2020. "Taxi hailing choice behavior and economic benefit analysis of emission reduction based on multi-mode travel big data." Transport Policy 97, no. : 73-84.

Journal article
Published: 24 June 2020 in International Journal of Environmental Research and Public Health
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Transportation has become one of the primary sources of urban atmospheric pollutants and it causes severe diseases among city residents. This study focuses on assessing the pollutant dispersion pattern using computational fluid dynamics (CFD) numerical simulation, with the effect and results validated by the results from wind tunnel experiments. First, the wind tunnel experiment was carefully designed to preliminarily assess the flow pattern of vehicle emissions. Next, the spatiotemporal distribution of pollutant concentrations around the motor vehicle was modeled using a CFD numerical simulation. The pollutant concentration contours indicated that the diffusion process of carbon monoxide mainly occurred in the range of 0−2 m above the ground. Meanwhile, to verify the correctness of the CFD simulation, pressure distributions of seven selected points that were perpendicular along the midline of the vehicle surface were obtained from both the wind tunnel experiment and the CFD numerical simulation. The Pearson correlation coefficient between the numerical simulation and the wind tunnel measurement was 0.98, indicating a strong positive correlation. Therefore, the distribution trend of all pressure coefficients in the numerical simulation was considered to be consistent with those from the measurements. The findings of this study could shed light on the concentration distribution of platoon-based vehicles and the future application of CFD simulations to estimate the concentration of pollutants along urban street canyons.

ACS Style

Xueqing Shi; Daniel (Jian) Sun; Ying Zhang; Jing Xiong; Zhonghua Zhao. Modeling Emission Flow Pattern of a Single Cruising Vehicle on Urban Streets with CFD Simulation and Wind Tunnel Validation. International Journal of Environmental Research and Public Health 2020, 17, 4557 .

AMA Style

Xueqing Shi, Daniel (Jian) Sun, Ying Zhang, Jing Xiong, Zhonghua Zhao. Modeling Emission Flow Pattern of a Single Cruising Vehicle on Urban Streets with CFD Simulation and Wind Tunnel Validation. International Journal of Environmental Research and Public Health. 2020; 17 (12):4557.

Chicago/Turabian Style

Xueqing Shi; Daniel (Jian) Sun; Ying Zhang; Jing Xiong; Zhonghua Zhao. 2020. "Modeling Emission Flow Pattern of a Single Cruising Vehicle on Urban Streets with CFD Simulation and Wind Tunnel Validation." International Journal of Environmental Research and Public Health 17, no. 12: 4557.

Research article
Published: 01 June 2020 in Computational Intelligence and Neuroscience
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One important objective of urban traffic signal control is to reduce individual delay and improve safety for travelers in both private car and public bus transit. To achieve signal control optimization from the perspective of all users, this paper proposes a platoon-based adaptive signal control (PASC) strategy to provide multimodal signal control based on the online connected vehicle (CV) information. By introducing unified phase precedence constraints, PASC strategy is not restricted by fixed cycle length and offsets. A mixed-integer linear programming (MILP) model is proposed to optimize signal timings in a real-time manner, with platoon arrival and discharge dynamics at stop line modeled as constraints. Based on the individual passenger occupancy, the objective function aims at minimizing total personal delay for both buses and automobiles. With the communication between signals, PASC achieves to provide implicit coordination for the signalized arterials. Simulation results by VISSIM microsimulation indicate that PASC model successfully reduces around 40% bus passenger delay and 10% automobile delay, respectively, compared with signal timings optimized by SYNCHRO. Results from sensitivity analysis demonstrate that the model performance is not sensitive to the number fluctuation of bus passengers, and the requested CV penetration rate range is around 20% for the implementation.

ACS Style

Ning Li; Shukai Chen; Jianjun Zhu; Daniel Jian Sun. A Platoon-Based Adaptive Signal Control Method with Connected Vehicle Technology. Computational Intelligence and Neuroscience 2020, 2020, 1 -10.

AMA Style

Ning Li, Shukai Chen, Jianjun Zhu, Daniel Jian Sun. A Platoon-Based Adaptive Signal Control Method with Connected Vehicle Technology. Computational Intelligence and Neuroscience. 2020; 2020 ():1-10.

Chicago/Turabian Style

Ning Li; Shukai Chen; Jianjun Zhu; Daniel Jian Sun. 2020. "A Platoon-Based Adaptive Signal Control Method with Connected Vehicle Technology." Computational Intelligence and Neuroscience 2020, no. : 1-10.

Journal article
Published: 27 November 2019 in Sustainability
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Research assessing on-road emission flow patterns from motor vehicles is essential in monitoring urban air quality, since it helps to mitigate atmospheric pollution levels. To reveal the influence of vehicle induced turbulence (VIT) caused by both front- and rear-vehicles on traffic exhaust and verify the applicability of the simplified line source emission model, a Computational Fluid Dynamics (CFD) numerical simulation was used to investigate the micro-scale vehicle pollutant flow patterns. The simulation results were examined through sensitivity analysis and compared with the field measured carbon monoxide (CO) concentration. Conclusions indicate that the vehicle induced turbulence caused by the airflow blocking effect of both front- and rear-vehicles impedes the diffusion of front-vehicle traffic exhaust, compared with that of the rear vehicle. The front-vehicle isosurface with the CO mass fraction of 0.0012 extended to 6.0 m behind the vehicle, while that of the rear-vehicle extends as far as 12.7 m. But for the entire motorcade, VIT is beneficial to the diffusion of pollutants in car-following situations. Meanwhile, within the range of 9 m behind the rear of the lagging vehicle lies a vehicle induced turbulence zone. Furthermore, the influence of vehicle induced turbulence on traffic exhaust flow pattern is obvious within a range of 1 m on both sides of the vehicle body, where the concentration gradient of on-road emission is larger and contains severe mechanical turbulence. As a result, in the large concentration gradient area of the pollutant flow field, which accounts for 99.85% of the total concentration gradient, using the line source models to represent the on-road emission might introduce considerable errors due to neglecting the influence of vehicle induced turbulence. Findings of this study may shed lights on predicting emission concentrations in multiple locations by selecting appropriate on-road emission source models.

ACS Style

Xueqing Shi; Daniel (Jian) Sun; Song Fu; Zhonghua Zhao; Jinfang Liu. Assessing On-Road Emission Flow Pattern under Car-Following Induced Turbulence Using Computational Fluid Dynamics (CFD) Numerical Simulation. Sustainability 2019, 11, 6705 .

AMA Style

Xueqing Shi, Daniel (Jian) Sun, Song Fu, Zhonghua Zhao, Jinfang Liu. Assessing On-Road Emission Flow Pattern under Car-Following Induced Turbulence Using Computational Fluid Dynamics (CFD) Numerical Simulation. Sustainability. 2019; 11 (23):6705.

Chicago/Turabian Style

Xueqing Shi; Daniel (Jian) Sun; Song Fu; Zhonghua Zhao; Jinfang Liu. 2019. "Assessing On-Road Emission Flow Pattern under Car-Following Induced Turbulence Using Computational Fluid Dynamics (CFD) Numerical Simulation." Sustainability 11, no. 23: 6705.

Journal article
Published: 17 October 2019 in Sustainability
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Electric vehicles (EVs) are promising alternatives to replace traditional gasoline vehicles. The relationship between available charging stations and electric vehicles has to be precisely coordinated to facilitate the increasing promotion and usage of EVs. This paper aims to investigate the choice of the charging location with global positioning system (GPS) trajectories of 700 Plug-in Hybrid Electric Vehicle (PHEV) users as well as the charging facility data in Shanghai. First, the recharge accessibility of each PHEV user was investigated, and 9% rely solely on public charging networks. Then, we explored the relationship between fuel consumption and the average distance between charging to analyze the environmental benefits of PHEVs. It was found that 16% PHEVs are similar to EVs, and 9% whose drivers rely solely on public charging stations are similar to internal combustion engine (ICE) vehicles. PHEV users were divided into four types based on the actual recharge access: home and workplace-based user (private + workplace + public), the home-based user (private + public), the workplace-based user (workplace + public), and the public-based user (public). Models were developed to identify and compare the factors that influence PHEV user’s charging location choices (home, workplace, and public stations). The modeling and results interpretation were carried out for all PHEV users, home and workplace-based users, home-based users, and workplace-based users, respectively. The estimation results demonstrated that PHEV users tended to charge at home or workplace rather than public charging stations. Charging price, charging price tariff, the initial state of charge (SOC), dwell time, charging power, the density and size of public charging stations, the total number of public charging, vehicle kilometer travel (VKT) of the current trip and current day are the main predictors when choosing the charging location. Findings of this study may provide new insights into the operational strategies of the public charging station as well as the deployment of public charging facilities in urban cities.

ACS Style

Bolong Yun; Daniel (Jian) Sun; Yingjie Zhang; Siwen Deng; Jing Xiong. A Charging Location Choice Model for Plug-In Hybrid Electric Vehicle Users. Sustainability 2019, 11, 5761 .

AMA Style

Bolong Yun, Daniel (Jian) Sun, Yingjie Zhang, Siwen Deng, Jing Xiong. A Charging Location Choice Model for Plug-In Hybrid Electric Vehicle Users. Sustainability. 2019; 11 (20):5761.

Chicago/Turabian Style

Bolong Yun; Daniel (Jian) Sun; Yingjie Zhang; Siwen Deng; Jing Xiong. 2019. "A Charging Location Choice Model for Plug-In Hybrid Electric Vehicle Users." Sustainability 11, no. 20: 5761.

Journal article
Published: 28 September 2019 in Transportation Research Part A: Policy and Practice
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Identifying and understanding factors that influence the demand of ridesourcing market is essential for online hailing systems to improve the quality of service. This paper proposes a two-level growth model (GM) to identify the potential multi-level factors that may affect online ride-hailing service demand. By using the massive datasets from Didi Chuxing, Inc., including both Didi Express and Didi Taxi services, the order number fluctuations at different urban circle zones after the implementation of restrictions on ridesourcing in Shanghai, 2016 were analyzed, to assess the competition and mutual complementarities between Express and Taxi, the two major services provided by Didi Chuxing. The relative market share of Express was estimated to reveal the possible related spatial and temporal factors, which further demonstrates significant positive associations between ridesourcing demand and built environment factors, such as commercial/residential land use, public transport accessibility, as well as weather conditions. Metro service availability and rainy weather were found correlated with a relatively higher market share of Express service. Additionally, compared to the regular road transit service, the metro system was found to have a stronger correlation with the ridesourcing demand. Findings of this study may provide guidelines for urban planning and traffic operations, which in turn assists to achieve high-quality ridesourcing service for travellers.

ACS Style

Daniel(Jian) Sun; Xueqing Ding. Spatiotemporal evolution of ridesourcing markets under the new restriction policy: A case study in Shanghai. Transportation Research Part A: Policy and Practice 2019, 130, 227 -239.

AMA Style

Daniel(Jian) Sun, Xueqing Ding. Spatiotemporal evolution of ridesourcing markets under the new restriction policy: A case study in Shanghai. Transportation Research Part A: Policy and Practice. 2019; 130 ():227-239.

Chicago/Turabian Style

Daniel(Jian) Sun; Xueqing Ding. 2019. "Spatiotemporal evolution of ridesourcing markets under the new restriction policy: A case study in Shanghai." Transportation Research Part A: Policy and Practice 130, no. : 227-239.

Articles
Published: 15 April 2019 in Transportmetrica A: Transport Science
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Network vulnerability of urban rail transit systems generally reflects the functionality loss caused by node or line operational disruptions, which, however, should be taken into consideration during the planning stage. This study aimed to identify the optimal alignment corridor of a new metro line by considering network vulnerability properties. A quantitative evaluation approach was developed to assess the performance of an urban metro network under various disruption scenarios. In addition to network vulnerability characteristics, the utility of new ridership and total construction costs were accounted for in determining the alignment of a new rail transit corridor. The Tabu Search algorithm has been proposed to find the optimum solution. The metro network in the Pudong District of Shanghai, China, has been adopted as the case study, and an optimal metro line corridor was identified for the new line linking the center of the district to a planned major facility. The result further indicates that the proposed approach can be integrated into the planning of rail transit systems or even of the entire transit network for improving the reliability and resilience of public transportation service.

ACS Style

Guangyue Nian; Fangxi Chen; Zhe Li; Yi Zhu; Daniel (Jian) Sun. Evaluating the alignment of new metro line considering network vulnerability with passenger ridership. Transportmetrica A: Transport Science 2019, 15, 1402 -1418.

AMA Style

Guangyue Nian, Fangxi Chen, Zhe Li, Yi Zhu, Daniel (Jian) Sun. Evaluating the alignment of new metro line considering network vulnerability with passenger ridership. Transportmetrica A: Transport Science. 2019; 15 (2):1402-1418.

Chicago/Turabian Style

Guangyue Nian; Fangxi Chen; Zhe Li; Yi Zhu; Daniel (Jian) Sun. 2019. "Evaluating the alignment of new metro line considering network vulnerability with passenger ridership." Transportmetrica A: Transport Science 15, no. 2: 1402-1418.

Journal article
Published: 05 December 2018 in Transport
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Due to low quality of bus service in a congested road network, some bus-waiting travelers would take taxis instead in order to save time or get to their destinations on time. However, the correlation between bus service quality and passengers’ taxi-hiring behavior is essentially unknown. This paper aims to assess the effects of bus service quality on taxi-hiring behavior based on historical data from the Global Position Systems (GPS) equipped buses and taxis in the city of Shenzhen, China. The taxi-hiring behavior is captured by analyzing the taxi-data, such as the origins of passenger pick-up, destinations of passengers drop-off, and taxi paths from the taxi movement data. The quality of bus service is assessed based on the bus location information. Parametric, semiparametric and nonparametric models are developed to explore the effects of bus service quality on taxi-hiring behavior. The results indicate that bus speed, headway and stoppage time are the core factors affecting passengers’ taxi-hiring behavior. Availability of metro, time of the day and bus route directions are the secondary important factors. This study shows that when buses run with relatively low and stable speed, taxi-hiring behavior is sensitive to the slight change of bus speed. More passengers would like to take taxis when bus speed starts to decline, or speed or stoppage time of buses tends to be irregular. However, the effects of bus headway on taxi-hiring behavior are more complicated. A specific turning point (coefficient of variability of mean headway ≈ 0.7) in the relationship between taxi-hiring behavior and bus headway is shown in this paper. Based on data mining and model development, this research presents details on attributes of bus service that drive passengers to switch to taxis and how changes in those attributes encourage modal shift from buses to taxis.

ACS Style

Hong-Wei Wang; Zhong-Ren Peng; Qing-Chang Lu; Daniel (Jian) Sun; Cong Bai. ASSESSING EFFECTS OF BUS SERVICE QUALITY ON PASSENGERS’ TAXI-HIRING BEHAVIOR. Transport 2018, 33, 1030 -1044.

AMA Style

Hong-Wei Wang, Zhong-Ren Peng, Qing-Chang Lu, Daniel (Jian) Sun, Cong Bai. ASSESSING EFFECTS OF BUS SERVICE QUALITY ON PASSENGERS’ TAXI-HIRING BEHAVIOR. Transport. 2018; 33 (4):1030-1044.

Chicago/Turabian Style

Hong-Wei Wang; Zhong-Ren Peng; Qing-Chang Lu; Daniel (Jian) Sun; Cong Bai. 2018. "ASSESSING EFFECTS OF BUS SERVICE QUALITY ON PASSENGERS’ TAXI-HIRING BEHAVIOR." Transport 33, no. 4: 1030-1044.

Research article
Published: 01 August 2018 in Journal of Advanced Transportation
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Dynamic congestion pricing has attracted increasing attentions during the recent years. Nevertheless, limited research has been conducted to address the dynamic tolling scheme at the network level, such as to cooperatively manage two alternative networks with heterogeneous properties, e.g., the two-layer network consisting of both expressway and arterial network in the urban areas. Recently, the macroscopic fundamental diagram (MFD) developed by both field experiments and simulation tests illustrates a unimodal low-scatter relationship between the mean flow and density network widely, providing the network traffic state is roughly homogeneous. It reveals traffic flow properties at an aggregated level and sheds light on dynamic traffic management of a large network. This paper proposes a bilevel programming toll model, incorporating MFD to solve the unbalanced flow distribution problem within the two-layer transportation networks. The upper level model aims at minimizing the total travel time, while the lower level focuses on the MFD-based traffic assignment, which extends the link-based traffic assignment to network wide level. Genetic algorithm (GA) and the method of successive average were adopted for solving the proposed model, on which an online experimental platform was established using VISSIM, MATLAB, and Visual Studio software packages. The results of numerical studies demonstrate that the total travel time is decreased by imposing the dynamic toll, while the total travel time savings significantly outweigh the toll paid. Consequently, the proposed dynamic toll scheme is believed to be effective from both traffic and economic points of view.

ACS Style

Bangyang Wei; Daniel(Jian) Sun. A Two-Layer Network Dynamic Congestion Pricing Based on Macroscopic Fundamental Diagram. Journal of Advanced Transportation 2018, 2018, 1 -11.

AMA Style

Bangyang Wei, Daniel(Jian) Sun. A Two-Layer Network Dynamic Congestion Pricing Based on Macroscopic Fundamental Diagram. Journal of Advanced Transportation. 2018; 2018 ():1-11.

Chicago/Turabian Style

Bangyang Wei; Daniel(Jian) Sun. 2018. "A Two-Layer Network Dynamic Congestion Pricing Based on Macroscopic Fundamental Diagram." Journal of Advanced Transportation 2018, no. : 1-11.

Journal article
Published: 15 June 2018 in European Transport Research Review
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Urban metro system generally has to deal with intractable heavily passenger loading during peak hours, in which demands are extreme huge in certain stations. However, overcrowding doesn’t ubiquitously exist for all stations and mitigation measures have to be carried out on purpose, respectively. Because of the restrictions on operational costs and avoiding transportation resources wasting, simply increasing dispatch frequency is not rational to solve the problem. Short turning pattern has been proved to be an efficient way to solve the issue, which had been mainly used in urban ground public transport systems. This paper applied short turning pattern to urban metro system and relaxed constraints of the turning-back facility. A mathematical model is proposed to determine the short turning parameters, during which a load factor was introduced as a measurement of overcrowding condition. An empirical case from Shanghai Metro Line 2 was incorporated to demonstrate the effectiveness of the proposed model. The results indicated that the short turning route from Beixinjing to Longyang Rd. in Shanghai Metro Line 2 could effectively relieve overcrowding within the heavy traffic demand zones. Findings of this study could provide valuable suggestions in metro system administration for potential improvement on the operational performance during peak hours.

ACS Style

Xueqing Ding; Shituo Guan; Daniel Jian Sun; Limin Jia. Short turning pattern for relieving metro congestion during peak hours: the substance coherence of Shanghai, China. European Transport Research Review 2018, 10, 28 .

AMA Style

Xueqing Ding, Shituo Guan, Daniel Jian Sun, Limin Jia. Short turning pattern for relieving metro congestion during peak hours: the substance coherence of Shanghai, China. European Transport Research Review. 2018; 10 (2):28.

Chicago/Turabian Style

Xueqing Ding; Shituo Guan; Daniel Jian Sun; Limin Jia. 2018. "Short turning pattern for relieving metro congestion during peak hours: the substance coherence of Shanghai, China." European Transport Research Review 10, no. 2: 28.

Validation study
Published: 10 May 2018 in Accident Analysis & Prevention
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Inappropriate cruising speed, such as speeding, is one of the major contributors to the road safety, which increases both the quantitative number and severity of traffic accidents. Previous studies have indicated that traffic congestion is one of the primary causes of drivers’ frustration and aggression, which may lead to inappropriate speed choice. In this study, the large taxi floating car data (FCD) was used to empirically evaluate how traffic congestion-related negative moods, defined as state aggressiveness, affected drivers’ speed choice. The indirect effect of traffic delay on the cruising speed adjustment through the state aggressiveness was assessed through the mediation analysis. Furthermore, the moderated mediation analysis was performed to explore the effect of driver type, value of time, and working duration on the mediation role of state aggressiveness. The results proved that the state aggressiveness was the mediator of the relationship between travel delays and driving speed adjustment, and the mediation role was different across various driver types. As compared to the aggressive drivers, the normal drivers and the steady drivers tended to behave more aggressively after experiencing non-recurrent congestion during the early stage of the trips. When the value of time was high, steady drivers were more likely to adjust their speed choice although the effect was not statistically significant for other driver types. The validation results indicated that the speed model incorporating state aggressiveness could better predict the travel time than the traditional speed model that only considering the specific expected speed distribution. The prediction results for the manifest indicators of state aggressiveness, such as the maximum speed and the speed deviation, also demonstrated a reasonable reflection of the field data.

ACS Style

Yizhe Huang; Daniel (Jian) Sun; Li-Hui Zhang. Effects of congestion on drivers’ speed choice: Assessing the mediating role of state aggressiveness based on taxi floating car data. Accident Analysis & Prevention 2018, 117, 318 -327.

AMA Style

Yizhe Huang, Daniel (Jian) Sun, Li-Hui Zhang. Effects of congestion on drivers’ speed choice: Assessing the mediating role of state aggressiveness based on taxi floating car data. Accident Analysis & Prevention. 2018; 117 ():318-327.

Chicago/Turabian Style

Yizhe Huang; Daniel (Jian) Sun; Li-Hui Zhang. 2018. "Effects of congestion on drivers’ speed choice: Assessing the mediating role of state aggressiveness based on taxi floating car data." Accident Analysis & Prevention 117, no. : 318-327.

Conference paper
Published: 01 April 2018 in Proceedings of the Institution of Civil Engineers - Transport
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ACS Style

Kaisheng Zhang; Ya Xu; Daniel (Jian) Sun. A mixed frontier model for urban bus performance evaluation. Proceedings of the Institution of Civil Engineers - Transport 2018, 171, 65 -74.

AMA Style

Kaisheng Zhang, Ya Xu, Daniel (Jian) Sun. A mixed frontier model for urban bus performance evaluation. Proceedings of the Institution of Civil Engineers - Transport. 2018; 171 (2):65-74.

Chicago/Turabian Style

Kaisheng Zhang; Ya Xu; Daniel (Jian) Sun. 2018. "A mixed frontier model for urban bus performance evaluation." Proceedings of the Institution of Civil Engineers - Transport 171, no. 2: 65-74.

Comparative study
Published: 09 February 2018 in Traffic Injury Prevention
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Objective: The 3 objectives of this study are to (1) identify the driving style characteristics of taxi drivers in Shanghai and New York City (NYC) using taxi Global Positioning System (GPS) data and make a comparative analysis; (2) explore the influence of different driving style characteristics on the frequency of speeding (who and how?) and (3) explore the influence of driving style characteristics, road attributes, and environmental factors on the speeding rate (when, where, and how?) Methods: This study proposes a driver–road–environment identification (DREI) method to investigate the determinant factors of taxi speeding violations. Driving style characteristics, together with road and environment variables, were obtained based on the GPS data and auxiliary spatiotemporal data in Shanghai and NYC. Results: The daily working hours of taxi drivers in Shanghai (18.6 h) was far more than in NYC (8.5 h). The average occupancy speed of taxi drivers in Shanghai (21.3 km/h) was similar to that of NYC (20.3 km/h). Speeders in both cities had shorter working hours and longer daily driving distance than other taxi drivers, though their daily income was similar. Speeding drivers routinely took long-distance trips (>10 km) and preferred relatively faster routes. Length of segments (1.0–1.5 km) and good traffic condition were associated with high speeding rates, whereas central business district area and secondary road were associated with low speeding rates. Moreover, many speeding violations were identified between 4:00 a.m. and 7:00 a.m. in both Shanghai and NYC and the worst period was between 5:00 a.m. and 6:00 a.m. in both cities. Conclusions: Characteristics of drivers, road attributes, and environment variables should be considered together when studying driver speeding behavior. Findings of this study may assist in stipulating relevant laws and regulations such as stricter offense monitoring in the early morning, long segment supervision, shift rule regulation, and working hour restriction to mitigate the risk of potential crashes.

ACS Style

Yizhe Huang; Daniel (Jian) Sun; Juanyu Tang. Taxi driver speeding: Who, when, where and how? A comparative study between Shanghai and New York City. Traffic Injury Prevention 2018, 19, 311 -316.

AMA Style

Yizhe Huang, Daniel (Jian) Sun, Juanyu Tang. Taxi driver speeding: Who, when, where and how? A comparative study between Shanghai and New York City. Traffic Injury Prevention. 2018; 19 (3):311-316.

Chicago/Turabian Style

Yizhe Huang; Daniel (Jian) Sun; Juanyu Tang. 2018. "Taxi driver speeding: Who, when, where and how? A comparative study between Shanghai and New York City." Traffic Injury Prevention 19, no. 3: 311-316.

Journal article
Published: 01 December 2017 in Science of The Total Environment
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Comprehensive analyses of urban traffic carbon emissions are critical in achieving low-carbon transportation. This paper started from the architecture design of a carbon emission mobile monitoring system using multiple sets of equipment and collected the corresponding data about traffic flow, meteorological conditions, vehicular carbon emissions and driving characteristics on typical roads in Shanghai and Wuxi, Jiangsu province. Based on these data, the emission model MOVES was calibrated and used with various sensitivity and correlation evaluation indices to analyze the traffic carbon emissions at microscopic, mesoscopic and macroscopic levels, respectively. The major factors that influence urban traffic carbon emissions were investigated, so that emission factors of CO, CO and HC were calculated by taking representative passenger cars as a case study. As a result, the urban traffic carbon emissions were assessed quantitatively, and the total amounts of CO, CO and HC emission from passenger cars in Shanghai were estimated as 76.95kt, 8271.91kt, and 2.13kt, respectively. Arterial roads were found as the primary line source, accounting for 50.49% carbon emissions. In additional to the overall major factors identified, the mobile monitoring system and carbon emission quantification method proposed in this study are of rather guiding significance for the further urban low-carbon transportation development.

ACS Style

Daniel (Jian) Sun; Ying Zhang; Rui Xue; Yi Zhang. Modeling carbon emissions from urban traffic system using mobile monitoring. Science of The Total Environment 2017, 599-600, 944 -951.

AMA Style

Daniel (Jian) Sun, Ying Zhang, Rui Xue, Yi Zhang. Modeling carbon emissions from urban traffic system using mobile monitoring. Science of The Total Environment. 2017; 599-600 ():944-951.

Chicago/Turabian Style

Daniel (Jian) Sun; Ying Zhang; Rui Xue; Yi Zhang. 2017. "Modeling carbon emissions from urban traffic system using mobile monitoring." Science of The Total Environment 599-600, no. : 944-951.