Huanmei Qin’s research while affiliated with Beijing University of Technology and other places

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Publications (42)


A Study of Shared Travel Behavior in Household-Based Autonomous Vehicles
  • Conference Paper

December 2024

Huanmei Qin

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Tianyuan Hu

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Meina Cheng

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Zhaolin Lu

Analysis on passenger flow evolution and service facility configuration for large-scale events in outer suburbs
  • Article
  • Full-text available

October 2024

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30 Reads

European Journal of Transport and Infrastructure Research

As more and more large-scale winter events are held in different areas, a reasonable configuration of service facilities is crucial for ensuring the successful execution of these events. Based on an analysis of the passenger flow for large-scale events in outer suburbs, this study has developed a dynamic evolution model to well simulate passenger arrival distribution among nodes and queue performance over time. Subsequently, an optimization model for service facility configuration based on node linkage is proposed. Using a large-scale winter event as a case study, we conclude that assigning a higher objective weight to spectators’ queuing time cost in the optimization model leads to an increase in the number of configured service facilities among nodes, thereby enhancing service quality. Different facility layouts for security checks and ticket checks have no significant effects on the optimal number of configured service facilities and spectator queuing time costs. However, implementing a remote security check can alleviate passenger congestion at downstream nodes and reduce the overall queuing time cost. The dynamic evolution model and the service facilities configuration model are suitable for coordinating passenger flow under limited-service facility provision along with measures such as adjusting facility layouts and controlling passenger flow. Thus, a good match between passenger flow distribution and facility service capacity can be achieved. The research conclusions can provide a reference for the analysis of passenger flow, service facility configuration, and passenger flow organization for large-scale events held in the outer suburbs.

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The experience routes and autonomous vehicles
Traffic conditions in autonomous driving demonstration areas
Examples of personalized stated choice tables
Initial perception of autonomous vehicles for different groups
Perception compared with expectations for two groups

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Exploring commuters’ mode preference to autonomous vehicles based on a personalized travel experience survey

August 2024

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82 Reads

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1 Citation

Transportation

With the rapid development of autonomous driving technology and the sharing economy, autonomous driving has significant potential to offer a broader range of travel choices for travelers. To explore different commuters’ autonomous vehicles—related behavioral decisions and choice preference, this study designed a personalized travel experience survey and established travel choice models incorporating individual perceptions and attitudes for two groups. It was found that commuters’ perceptions of autonomous vehicles were significantly improved by travel experience. Travel time is the most concerned factor in travel mode choice for private car commuters, while travel cost is the most important factor for public transport commuters. Therefore, enhancing operational efficiency and reducing the energy consumption of autonomous vehicles could effectively encourage commuters to adopt new travel modes. Improving travelers’ travel experiences and positive attitudes towards using autonomous vehicles is conducive to the adoption of private autonomous vehicles by private car commuters and the choice of shared autonomous vehicles by public transport users. By promoting people’s acceptance of ride-sharing and awareness of its benefits through user experience, publicity, and guidance, a substantial increase in the adoption of shared autonomous vehicles can be achieved among both commuter groups. Suitable thresholds for crucial factors, including travel time and cost, perception, and attitudes towards ride-sharing, were determined for both groups to facilitate their mode transfer among traditional travel modes and autonomous vehicles. The research findings can provide a reference for anticipating travel demand and guiding the formulation of transport policies for future transportation systems.


Demand-Responsive Transit Service With Soft Time Windows Considering Real-Time Disruptions Based on Bounded Rationality

March 2024

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17 Reads

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1 Citation

Transportation Research Record Journal of the Transportation Research Board

Demand-responsive transit (DRT) with smartphone-based applications is emerging as a flexible and sustainable mobility service, transforming urban transportation. Nevertheless, to satisfy the real-time and inconsistent demand, it is becoming increasingly important to capture the decision-making psychology of order cancellations. In this study, a two-phase optimization framework is presented in response to real-time disruptions, including order cancellations and the insertion of new real-time passengers. In contrast to random real-time demand, this paper is more concerned about the impacts of the feedback information on order cancellations. Bounded rationality is incorporated into the model to discuss the decision-making process of cancellation behaviors. With regard to the soft window, a compensation strategy is proposed to promote the profit while encouraging passengers for a long-term use. Additionally, solution algorithm based on variable neighborhood search (VNS) and rolling horizon is constructed to approach the Pareto solutions set. To testify the validity of the proposed algorithm, small-scale experiments in simplified Sioux Falls network are investigated for multiple runs. Meanwhile, a real-world case study in Beijing is explored to evaluate the system performance considering real-time disruptions. The results indicate that the dynamic DRT service can substantially improve the system profit but increase the penalty cost. The profit presents a significant improvement to 940 (renminbi) RMB as a result of the insert of real-time passengers. This study, therefore, not only provides a deeper insight into the analysis of passenger cancellation behavior but also contributes to construct a more flexible DRT service.







Citations (22)


... Complex economic interactions and potential financial impacts under various market scenarios are modeled by DRL, allowing for the development of robust strategies that balance economic viability with environmental sustainability [28]. This modeling includes the strategic integration of DRPs, which are optimized to shift energy usage to off-peak times, thus balancing the grid and reducing costs [29]. ...

Reference:

Optimizing business strategies for carbon energy management in buildings: a machine learning approach in economics and management
Assessing the sustainability of time-dependent electric demand responsive transit service through deep reinforcement learning
  • Citing Article
  • March 2024

Energy

... SP surveys, on the other hand, involve presenting respondents with hypothetical travel scenarios and requesting that they express their preferences or expected behavior in various circumstances (Fujiwara et al., 2023;Rudloff and Straub, 2021). Researchers have used SP surveys to look into things like how people might use self-driving cars (Azizi Soldouz et al., 2023;Moreno et al., 2018;Qin et al., 2023), how much they value time saved while traveling (Cherry et al., 2023;Miguel Figueroa-Medina et al., 2022), and how congestion pricing affects the choice of transportation modes Li et al., 2023;. Stated preference (SP) surveys enable researchers to manipulate the characteristics of hypothetical situations and determine the relative significance of various elements in influencing travel behavior. ...

Effect of Cognitive Experiences and Attitudes on Commuters’ Travel Choice Behavior for Autonomous Vehicles
  • Citing Article
  • June 2023

Journal of Urban Planning and Development

... In a study analyzing parking policies in 12 cities on five continents, it becomes clear that parking problems are similar everywhere; however, urban planners frequency, while the most critical factors are determined as the parking cost, parking search time, parking duration, and walking time between the parking spot and the final destination [14]. A study conducted in China found that individuals pay more attention to the walking distance after parking, driving time, and parking price when making their parking choices [29]. Moreover, a study in Israel showed that drivers who park for long durations are less likely to change their behavior in response to parking restriction policies [27]. ...

Research on Parking Recommendation Methods Considering Travelers’ Decision Behaviors and Psychological Characteristics

... Current studies focus on the following two aspects: independent bridging bus scheduling and combined bridging bus scheduling [9]. The former studies have assumed that buses circulate back and forth along interrupted sections [10], and that the vehicle travel routes are fixed [11], a bus can only run on a specific route and is not allowed to run across routes [12]. ...

Towards a more flexible demand responsive transit service with compensation mechanism considering boundedly rational passengers

... Based on (Hao et al. 2019) research, a dynamic pricing system for shared parking can increase space utilization and occupancy rates 60 − 80% , promoting sustainable urban transportation. Qin et al. (2022) also recommends a target occupancy rate of 60 − 80% and price adjustments of 2 Yuan per hour to balance effectiveness and operating costs. Vuchic (2017) analyzed impact of parking pricing in regulating the dynamic traffic demands and shown that a typical car trip pays a parking fee of more than $5 on average and 70% of the direct total travel cost. ...

Analysis of the Effect of Demand-Driven Dynamic Parking Pricing on on-Street Parking Demand

IEEE Access

... Recent studies such as Alomrani et al. (2023) proposed graphbased bipartite optimization for real-time dispatching, improving matching efficiency, but without differentiating service levels between passengers [29]. Wang et al. (2022) simulated soft time windows and compensation policies to examine service differentiation, but implemented these within a fixed optimization context, limiting reusability across alternative strategies or geographic contexts [30]. Table 1 offers a comparative summary of these representative works. ...

A Slack Departure Strategy for Demand Responsive Transit Based on Bounded Rationality

... Scalability extends beyond physical or digital realms to intellectual domains, as seen in [22], where systems discern management policy weaknesses and suggest improvements. Similarly, [23] proposes solutions for potential parking issues in On-street systems, adaptable to standard smart parking systems. ...

Analysis on cruising process for on-street parking using an spectral clustering method

... The main contributions of this study are as follows: on the one hand, there are few studies on mechanical parking planning. Some studies have analyzed the internal organization, control strategy, site selection and cost, mechanical structure [7][8][9][10][11][12], and the design of the device and intelligent system optimization of the single facilities, while there is a lack of regional planning studies that provide theoretical and practical support for the spatial layout planning of mechanical parking. On the other hand, very few studies have addressed the relationship between car parks and the built environment, especially mechanical parking lots, and there is a lack of analysis of the impact of factors. ...

Analysis of parking cruising behaviour and parking location choice
  • Citing Article
  • August 2020

Transportation Planning and Technology

... Research on individual decision-making processes is fundamental to discovering macroscopic behavioral rules in travel mode selection. Qin et al. [30] designed a behavioral experiment with a process-tracing method to obtain data on repeated travel mode choices under different contexts. A stochastic and dynamic model based on Decision Space Theory has been proven to be reliable and is used to reproduce and analyze the repeated decision-making processes. ...

Analysis on context change and repetitive travel mode choices based on a dynamic, computational model
  • Citing Article
  • April 2019

Transport Policy

... The conclusions drawn by the authors was that time headway is a measure of potential risk, i.e., short time headway could be maintained without a crash; whereas, TTC measures impending risk, i.e., a short TTC will result in a crash (Bella et al., 2014). Ben-Yaacov, Maltz, & Shinar, 2002;Fu, Gasper, & Kim, 2013;Li, Xing, Wang, & Dong, 2017;Maltz et al., 1899;Mamdoohi et al., 2014;Navarro et al., 2018;Ni, Kang, & Andersen, 2010;Peng, Lu, He, & Gu, 2017;Risto & Martens, 2014;Rosey et al., 2017;Tscharn, Naujoks, & Neukum, 2018;Vogel, 2003 Economou et al., 2020;Fitch et al., 2014;Fleming et al., 2019;Gao et al., 2020;Ha, Kang, & Park, 2003;Hogema & Van Der Horst, 1997;Jamson et al., 2005;Kaber, Liang, Zhang, Rogers, & Gangakhedkar, 2012;Lansdown, 2019;McGehee et al., 1994;Morris & Pilcher, 2016;Pampel et al., 2015;Pantangi et al., 2020;Probst, Brandt, & Degner, 1986;Qin, Yang, & Zheng, 2018;Rakauskas et al., 2008;Risto & Martens, 2013;Rudin-Brown, 2006;Seacrist et al., 2018;Shangguan, Wang, Liu, & Wang, 2019;Shino, Kamata, Nagai, Michitsuji, & Mora, 2008;Wang et al., 2011;Yang, Wong, & McDonald, 2015;Ye & Zhang, 2009;Zheng, Zhu, He, He, & Liu, 2019;Zokaei et al., 2020 Total 110 ...

Operation and Management
  • Citing Conference Paper
  • January 2018