+publisher:"University of Michigan" +contributor:("Yin, Yafeng")

University of Michigan

1. Xu, Zhengtian. On the Empty Miles of Ride-Sourcing Services: Theory, Observation and Countermeasures.

Degree: PhD, Civil Engineering, 2020, University of Michigan

URL: http://hdl.handle.net/2027.42/163209

► The proliferation of smartphones in recent years has catalyzed the rapid growth of ride-sourcing services such as Uber, Lyft, and Didi Chuxing. Such on-demand e-hailing… (more)

▼ The proliferation of smartphones in recent years has catalyzed the rapid growth of ride-sourcing services such as Uber, Lyft, and Didi Chuxing. Such on-demand e-hailing services significantly reduce the meeting frictions between drivers and riders and provide the platform with unprecedented flexibility and challenges in system management. A big issue that arises with service expansion is the empty miles produced by ride-sourcing vehicles. To overcome the physical and temporal frictions that separate drivers from customers and effectively reposition themselves towards desired destinations, ride-sourcing vehicles generate a significant number of vacant trips. These empty miles traveled result in inefficient use of the available fleet and increase traffic demand, posing substantial impacts on system operations. To tackle the issues, my dissertation is dedicated to deepening our understanding of the formation and the externalities of empty miles, and then proposing countermeasures to bolster system performance. There are two essential and interdependent contributors to empty miles generated by ride-sourcing vehicles: cruising in search of customers and deadheading to pick them up, which are markedly dictated by forces from riders, drivers, the platform, and policies imposed by regulators. In this dissertation, we structure our study of this complex process along three primary axes, respectively centered on the strategies of a platform, the behaviors of drivers, and the concerns of government agencies. In each axis, theoretical models are established to help understand the underlying physics and identify the trade-offs and potential issues that drive behind the empty miles. Massive data from Didi Chuxing, a dominant ride-sourcing company in China, are leveraged to evidence the presence of matters discussed in reality. Countermeasures are then investigated to strengthen management upon the empty miles, balance the interests of different stakeholders, and improve the system performance. Although this dissertation scopes out ride-sourcing services, the models, analyses, and solutions can be readily adapted to address related issues in other types of shared-use mobility services. Advisors/Committee Members: Yin, Yafeng (committee member), Saigal, Romesh (committee member), Chao, Xiuli (committee member), Masoud, Neda (committee member).

Subjects/Keywords: ride-sourcing systems and services; system modeling and analysis; driver behavior and management; market equilibrium and regulation; Transportation; Engineering

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APA (6^th Edition):

Xu, Z. (2020). On the Empty Miles of Ride-Sourcing Services: Theory, Observation and Countermeasures. (Doctoral Dissertation). University of Michigan. Retrieved from http://hdl.handle.net/2027.42/163209

Chicago Manual of Style (16^th Edition):

Xu, Zhengtian. “On the Empty Miles of Ride-Sourcing Services: Theory, Observation and Countermeasures.” 2020. Doctoral Dissertation, University of Michigan. Accessed April 19, 2021. http://hdl.handle.net/2027.42/163209.

MLA Handbook (7^th Edition):

Xu, Zhengtian. “On the Empty Miles of Ride-Sourcing Services: Theory, Observation and Countermeasures.” 2020. Web. 19 Apr 2021.

Vancouver:

Xu Z. On the Empty Miles of Ride-Sourcing Services: Theory, Observation and Countermeasures. [Internet] [Doctoral dissertation]. University of Michigan; 2020. [cited 2021 Apr 19]. Available from: http://hdl.handle.net/2027.42/163209.

Council of Science Editors:

Xu Z. On the Empty Miles of Ride-Sourcing Services: Theory, Observation and Countermeasures. [Doctoral Dissertation]. University of Michigan; 2020. Available from: http://hdl.handle.net/2027.42/163209

University of Michigan

2. Chen, Thomas. Advancing Quantitative Risk Analysis for Critical Water Infrastructure.

Degree: PhD, Industrial & Operations Engineering, 2019, University of Michigan

URL: http://hdl.handle.net/2027.42/153423

► Critical infrastructure systems play a vital role in the supply of lifeline services to businesses and the wider public. It is of paramount importance for… (more)

Subjects/Keywords: Risk Analysis; Critical Infrastructure; Mathematical Optimization; Statistical Learning; Industrial and Operations Engineering; Engineering

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APA (6^th Edition):

Chen, T. (2019). Advancing Quantitative Risk Analysis for Critical Water Infrastructure. (Doctoral Dissertation). University of Michigan. Retrieved from http://hdl.handle.net/2027.42/153423

Chicago Manual of Style (16^th Edition):

Chen, Thomas. “Advancing Quantitative Risk Analysis for Critical Water Infrastructure.” 2019. Doctoral Dissertation, University of Michigan. Accessed April 19, 2021. http://hdl.handle.net/2027.42/153423.

MLA Handbook (7^th Edition):

Chen, Thomas. “Advancing Quantitative Risk Analysis for Critical Water Infrastructure.” 2019. Web. 19 Apr 2021.

Vancouver:

Chen T. Advancing Quantitative Risk Analysis for Critical Water Infrastructure. [Internet] [Doctoral dissertation]. University of Michigan; 2019. [cited 2021 Apr 19]. Available from: http://hdl.handle.net/2027.42/153423.

Council of Science Editors:

Chen T. Advancing Quantitative Risk Analysis for Critical Water Infrastructure. [Doctoral Dissertation]. University of Michigan; 2019. Available from: http://hdl.handle.net/2027.42/153423

University of Michigan

3. Yu, Miao. Optimization Approaches for Mobility and Service Sharing.

Degree: PhD, Industrial & Operations Engineering, 2020, University of Michigan

URL: http://hdl.handle.net/2027.42/155115

► Mobility and service sharing is undergoing a fast rise in popularity and industrial growth in recent years. For example, in patient-centered medical home care, services… (more)

▼ Mobility and service sharing is undergoing a fast rise in popularity and industrial growth in recent years. For example, in patient-centered medical home care, services are delivered to patients at home, who share a group of medical staff riding together in a vehicle that also carries shared medical devices; companies such as Amazon and Meijer have been investing tremendous human effort and money in grocery delivery to customers who share the use of delivery vehicles and staff. In such mobility and service sharing systems, decision-makers need to make a wide range of system design and operational decisions, including locating service facilities, matching supplies with demand for shared mobility services, dispatching vehicles and staff, and scheduling appointments. The complexity of the linking decisions and constraints, as well as the dimensionality of the problems in the real world, pose challenges in finding optimal strategies efficiently. In this work, we apply techniques from Operations Research to investigate the optimal and practical solution approaches to improve the quality of service, cost-effectiveness, and operational efficiency of mobility and service sharing in a variety of applications. We deploy stochastic programming, integer programming, and approximation algorithms to address the issues in decision-making for seeking fast and reliable solutions for planning and operations problems. This dissertation contains four main chapters. In Chapter 2, we consider a class of vehicle routing problems (VRPs) where the objective is to minimize the longest route taken by any vehicle as opposed to the total distance of all routes. In such a setting, the traditional decomposition approach fails to solve the problem effectively. We investigate the hardness result of the problem and develop an approximation algorithm that achieves the best approximation ratio. In Chapter 3, we focus on developing an efficient computational algorithm for the elementary shortest path problem with resource constraints, which is solved as the pricing subproblem of the column generation-based approach for many VRP variants. Inspired by the color-coding approach, we develop a randomized algorithm that can be easily implemented in parallel. We also extend the state-of-the-art pulse algorithm for elementary shortest path problem with a new bounding scheme on the load of the route. In Chapter 4, we consider a carsharing fleet location design problem with mixed vehicle types and a restriction on CO2 emission. We use a minimum-cost flow model on a spatial-temporal network and provide insights on fleet location, car-type design, and their environmental impacts. In Chapter 5, we focus on the design and operations of an integrated car-and-ride sharing system for heterogeneous users/travelers with an application of satisfying transportation needs in underserved communities. The system aims to provide self-sustained community-based shared transportation. We address the uncertain travel and service time in operations via a stochastic integer… Advisors/Committee Members: Nagarajan, Viswanath (committee member), Shen, Siqian May (committee member), Yin, Yafeng (committee member), Epelman, Marina A (committee member), Lee, Jon (committee member).

Subjects/Keywords: Mobility and Service Sharing; Vehicle Routing; Approximation Algorithm; Stochastic Programming; Optimization; Operations Research; Industrial and Operations Engineering; Engineering

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Yu, M. (2020). Optimization Approaches for Mobility and Service Sharing. (Doctoral Dissertation). University of Michigan. Retrieved from http://hdl.handle.net/2027.42/155115

Chicago Manual of Style (16^th Edition):

Yu, Miao. “Optimization Approaches for Mobility and Service Sharing.” 2020. Doctoral Dissertation, University of Michigan. Accessed April 19, 2021. http://hdl.handle.net/2027.42/155115.

MLA Handbook (7^th Edition):

Yu, Miao. “Optimization Approaches for Mobility and Service Sharing.” 2020. Web. 19 Apr 2021.

Vancouver:

Yu M. Optimization Approaches for Mobility and Service Sharing. [Internet] [Doctoral dissertation]. University of Michigan; 2020. [cited 2021 Apr 19]. Available from: http://hdl.handle.net/2027.42/155115.

Council of Science Editors:

Yu M. Optimization Approaches for Mobility and Service Sharing. [Doctoral Dissertation]. University of Michigan; 2020. Available from: http://hdl.handle.net/2027.42/155115

University of Michigan

4. Zhao, Yan. Traffic State Estimation Using Probe Vehicle Data.

Degree: PhD, Mechanical Engineering, 2020, University of Michigan

URL: http://hdl.handle.net/2027.42/155289

► Traffic problems are becoming a burden on cities across the world. To prevent traffic accidents, mitigate congestion, and reduce fuel consumption, a critical step is… (more)

▼ Traffic problems are becoming a burden on cities across the world. To prevent traffic accidents, mitigate congestion, and reduce fuel consumption, a critical step is to have a good understanding of traffic. Traditionally, traffic conditions are monitored primarily by fixed-location sensors. However, fixed-location sensors only provide information about specific locations, and the installation and maintenance cost is very high. The advances in gls{gps}-based technologies, such as connected vehicles and ride-hailing services, provide us an alternative approach to traffic monitoring. While these types of gls{gps}-equipped probe vehicles travel on the road, a vast amount of trajectory data are being collected. As probe vehicle data contain rich information about traffic conditions, they have drawn much attention from both researchers and practitioners in the field of traffic management and control. Extensive literature has studied the estimation of traffic speeds and travel times using probe vehicle data. However, as for queue lengths and traffic volumes, which are critical for traffic signal control and performance measures, most of the existing estimation methods based on probe vehicles can hardly be implemented in practice. The main obstacle is the low market penetration of probe vehicles. Therefore, in this dissertation, we aim to develop probe vehicle based traffic state estimation methods that are suitable for the low penetration rate environment and can potentially be implemented in the real world. First, we treat the traffic state in each location and each time point independently. We focus on estimating the queues forming at isolated intersections under light or moderate traffic. The existing methods often require prior knowledge of the queue length distribution or the probe vehicle penetration rate. However, these parameters are not available beforehand in real life. Therefore, we propose a series of methods to estimate these parameters from historical probe vehicle data. Some of the methods have been validated using real-world probe vehicle data. Second, we study traffic state estimation considering temporal correlations. The correlation of queue lengths in different traffic signal cycles is often ignored by the existing studies, although the phenomenon is commonly-observed in real life, such as the overflow queues induced by oversaturated traffic. To fill the gap, we model such queueing processes and observation processes using a hidden Markov model (gls{hmm}). Based on the gls{hmm}, we develop two cycle-by-cycle queue length estimation methods and an algorithm that can estimate the parameters of the gls{hmm} from historical probe vehicle data. Lastly, we consider the spatiotemporal correlations of traffic states, with a focus on the estimation of traffic volumes. With limited probe vehicle data, it is difficult to estimate traffic volumes accurately if we treat each location and each time slot independently. Noticing that traffic volumes in different locations and different time slots are correlated, we… Advisors/Committee Members: Liu, Henry (committee member), Peng, Huei (committee member), Yin, Yafeng (committee member), Masoud, Neda (committee member), Orosz, Gabor (committee member).

Subjects/Keywords: Traffic state estimation; Probe vehicle; Data mining; Transportation; Engineering

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Zhao, Y. (2020). Traffic State Estimation Using Probe Vehicle Data. (Doctoral Dissertation). University of Michigan. Retrieved from http://hdl.handle.net/2027.42/155289

Chicago Manual of Style (16^th Edition):

Zhao, Yan. “Traffic State Estimation Using Probe Vehicle Data.” 2020. Doctoral Dissertation, University of Michigan. Accessed April 19, 2021. http://hdl.handle.net/2027.42/155289.

MLA Handbook (7^th Edition):

Zhao, Yan. “Traffic State Estimation Using Probe Vehicle Data.” 2020. Web. 19 Apr 2021.

Vancouver:

Zhao Y. Traffic State Estimation Using Probe Vehicle Data. [Internet] [Doctoral dissertation]. University of Michigan; 2020. [cited 2021 Apr 19]. Available from: http://hdl.handle.net/2027.42/155289.

Council of Science Editors:

Zhao Y. Traffic State Estimation Using Probe Vehicle Data. [Doctoral Dissertation]. University of Michigan; 2020. Available from: http://hdl.handle.net/2027.42/155289

University of Michigan

5. Luo, Qi. Incentive Contracts in Multi-agent Systems: Theory and Applications.

Degree: PhD, Industrial & Operations Engineering, 2020, University of Michigan

URL: http://hdl.handle.net/2027.42/155199

► This thesis studies incentive contracts in multi-agent systems with applications to transportation policy. The early adoption of emerging transportation systems such as electric vehicles (EVs),… (more)

▼ This thesis studies incentive contracts in multi-agent systems with applications to transportation policy. The early adoption of emerging transportation systems such as electric vehicles (EVs), peer-to-peer ridesharing, and automated vehicles (AVs) relies on governmental incentives. Those incentives help achieve a specific market share target, prevent irregular behaviors, and enhance social benefit. Yet, two challenges may impede the implementation of such incentive policies. First, the government and subsidized organizations must confront the uncertainty in a market; Second, the government has no access to the organizations' private information, and thus their strategies are unknown to it. In the face of these challenges, a command-and-control incentive policy fails. In Chapter 2, we revisit the primary setting in which a government agency incentivizes the OEM for accelerating the widespread adoption of AVs. This work aspires to offset the negative externalities of AVs in the ``dark-age'' of AV deployment. More specifically, this chapter designs AV subsidies to shorten the early AV market penetration period and maximize the total expected efficiency benefits of AVs. It seeks a generic optimal AV subsidy structure, so-called ``two-threshold'' subsidy policy, which is proven to be more efficient than the social-welfare maximization approach. In Chapter 3, we develop a multi-agent incentive contracts model to address the issue of stimulating a group of non-cooperating agents to act in the principal's interest over a planning horizon. We extend the single-agent incentive contract to a multi-agent setting with history-dependent terminal conditions. Our contributions include: (a) Finding sufficient conditions for the existence of optimal multi-agent incentive contracts and conditions under which they form a unique Nash Equilibrium; (b) Showing that the optimal multi-agent incentive contracts can be solved by a Hamilton-Jacobi-Bellman equation with equilibrium constraints; (c) Proposing a backward iterative algorithm to solve the problem. In Chapter 4, we obtain the optimal EV and charging infrastructure subsidies through the multi-agent incentive contracts model. Widespread adoption of Electric Vehicles (EV) mostly depends on governmental subsidies during the early stage of deployment. The governmental incentives must strike a balance between an EV manufacturer and a charging infrastructure installer. Yet, the current supply of charging infrastructure is not nearly enough to support EV growth over the next decades. We model the joint subsidy problem as a two-agent incentive contract. The government observes two correlated processes – the EV market penetration and the charging infrastructure expansion. It looks for an optimal policy that maximizes the cumulative social benefit in the face of uncertainty. In our case study, we find that the optimal dynamic subsidies can achieve 70% of the target EV market share in China by 2025, and also maintains the ratio of charging stations per EV. Chapter 5 ends the… Advisors/Committee Members: Hampshire, Robert Cornelius (committee member), Saigal, Romesh (committee member), Uichanco, Joline (committee member), Shi, Cong (committee member), Yin, Yafeng (committee member).

Subjects/Keywords: incentive contract; multiagent system; automated vehicles; electric vehicles; governmental subsidy; game theory; Industrial and Operations Engineering; Engineering

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Luo, Q. (2020). Incentive Contracts in Multi-agent Systems: Theory and Applications. (Doctoral Dissertation). University of Michigan. Retrieved from http://hdl.handle.net/2027.42/155199

Chicago Manual of Style (16^th Edition):

Luo, Qi. “Incentive Contracts in Multi-agent Systems: Theory and Applications.” 2020. Doctoral Dissertation, University of Michigan. Accessed April 19, 2021. http://hdl.handle.net/2027.42/155199.

MLA Handbook (7^th Edition):

Luo, Qi. “Incentive Contracts in Multi-agent Systems: Theory and Applications.” 2020. Web. 19 Apr 2021.

Vancouver:

Luo Q. Incentive Contracts in Multi-agent Systems: Theory and Applications. [Internet] [Doctoral dissertation]. University of Michigan; 2020. [cited 2021 Apr 19]. Available from: http://hdl.handle.net/2027.42/155199.

Council of Science Editors:

Luo Q. Incentive Contracts in Multi-agent Systems: Theory and Applications. [Doctoral Dissertation]. University of Michigan; 2020. Available from: http://hdl.handle.net/2027.42/155199

University of Michigan

6. Huang, Shihong. Cyber Security of Traffic Signal Control Systems with Connected Vehicles.

Degree: PhD, Civil Engineering, 2020, University of Michigan

URL: http://hdl.handle.net/2027.42/162931

► Our world is becoming increasingly connected through smart technologies. The same trend is emerging in transportation systems, wherein connected vehicles (CVs) and transportation infrastructure are… (more)

▼ Our world is becoming increasingly connected through smart technologies. The same trend is emerging in transportation systems, wherein connected vehicles (CVs) and transportation infrastructure are being connected through advanced wireless communication technologies. CVs have great potential to improve a variety of mobility applications, including traffic signal control (TSC), a critical component in urban traffic operations. CV-based TSC (CV-TSC) systems use trajectory data to make more informed control decisions, therefore can accommodate real-time traffic fluctuations more efficiently. However, vehicle-infrastructure connectivity opens new doors to potential cyber attacks. Malicious attackers can potentially send falsified trajectory data to CV-TSC systems and influence signal control decisions. The benefit of CV-TSC systems can be realized only if the systems are secure in cyberspace. Although many CV-TSC systems have been developed within the past decade, few consider cyber security in their system design. It remains unclear exactly how vulnerable CV-TSC systems are, how cyber attacks may be perpetrated, and how engineers can mitigate cyber attacks and protect CV-TSC systems. Therefore, this dissertation aims to systematically understand the cyber security problems facing CV-TSC systems under falsified data attacks and provide a countermeasure to safeguard CV-TSC systems. These objectives are accomplished through four studies. The first study evaluates the effects of falsified data attacks on TSC systems. Two TSC systems are considered: a conventional actuated TSC system and an adaptive CV-TSC system. Falsified data attacks are assumed to change the input data to these systems and therefore influence control decisions. Numerical examples show that both systems are vulnerable to falsified data attacks. The second study investigates how falsified data attacks may be perpetrated in a realistic setting. Different from prior research, this study considers a more realistic but challenging black-box attack scenario, in which the signal control model is unavailable to the attacker. Under this constraint, the attacker has to learn the signal control model using a surrogate model. The surrogate model predicts signal timing plans based on critical traffic features extracted from CV data. The attacker can generate falsified CV data (i.e., falsified vehicle trajectories) to alter the values of critical traffic features and thus influence signal control decisions. In the third study, a data-driven method is proposed to protect CV-TSC systems from falsified data attacks. Falsified trajectories are behaviorally distinct from normal trajectories because they must accomplish a certain attack goal; thus, the problem of identifying falsified trajectories is considered an abnormal trajectory identification problem. A trajectory-embedding model is developed to generate vector representations of trajectory data. The similarity (distance) between each pair of trajectories can be computed based on these vector representations.… Advisors/Committee Members: Liu, Henry (committee member), Mao, Z Morley (committee member), Masoud, Neda (committee member), Yin, Yafeng (committee member).

Subjects/Keywords: Cyber security; Traffic signal control; Connected vehicle; Falsified data attack; Engineering (General); Transportation; Engineering

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Huang, S. (2020). Cyber Security of Traffic Signal Control Systems with Connected Vehicles. (Doctoral Dissertation). University of Michigan. Retrieved from http://hdl.handle.net/2027.42/162931

Chicago Manual of Style (16^th Edition):

Huang, Shihong. “Cyber Security of Traffic Signal Control Systems with Connected Vehicles.” 2020. Doctoral Dissertation, University of Michigan. Accessed April 19, 2021. http://hdl.handle.net/2027.42/162931.

MLA Handbook (7^th Edition):

Huang, Shihong. “Cyber Security of Traffic Signal Control Systems with Connected Vehicles.” 2020. Web. 19 Apr 2021.

Vancouver:

Huang S. Cyber Security of Traffic Signal Control Systems with Connected Vehicles. [Internet] [Doctoral dissertation]. University of Michigan; 2020. [cited 2021 Apr 19]. Available from: http://hdl.handle.net/2027.42/162931.

Council of Science Editors:

Huang S. Cyber Security of Traffic Signal Control Systems with Connected Vehicles. [Doctoral Dissertation]. University of Michigan; 2020. Available from: http://hdl.handle.net/2027.42/162931

University of Michigan

7. Sun, Xiaotong. Facilitating Cooperative Truck Platooning for Energy Savings: Path Planning, Platoon Formation and Benefit Redistribution.

Degree: PhD, Civil Engineering, 2020, University of Michigan

URL: http://hdl.handle.net/2027.42/163047

► Enabled by the connected and automated vehicle (CAV) technology, cooperative truck platooning that offers promising energy savings is likely to be implemented soon. However, as… (more)

▼ Enabled by the connected and automated vehicle (CAV) technology, cooperative truck platooning that offers promising energy savings is likely to be implemented soon. However, as the trucking industry operates in a highly granular manner so that the trucks usually vary in their operation schedules, vehicle types and configurations, it is inevitable that 1) the spontaneous platooning over a spatial network is rare, 2) the total fuel savings vary from platoon to platoon, and 3) the benefit achieved within a platoon differs from position to position, e.g., the lead vehicle always achieves the least fuel-saving. Consequently, trucks from different owners may not have the opportunities to platoon with others if no path coordination is performed. Even if they happen to do so, they may tend to change positions in the formed platoons to achieve greater benefits, yielding behaviorally unstable platoons with less energy savings and more disruptions to traffic flows. This thesis proposes a hierarchical modeling framework to explicate the necessitated strategies that facilitate cooperative truck platooning. An empirical study is first conducted to scrutinize the energy-saving potentials of the U.S. national freight network. By comparing the performance under scheduled platooning and ad-hoc platooning, the author shows that the platooning opportunities can be greatly improved by careful path planning, thereby yielding substantial energy savings. For trucks assembled on the same path and can to platoon together, the second part of the thesis investigates the optimal platoon formation that maximizes total platooning utility and benefits redistribution mechanisms that address the behavioral instability issue. Both centralized and decentralized approaches are proposed. In particular, the decentralized approach employs a dynamic process where individual trucks or formed platoons are assumed to act as rational agents. The agents decide whether to form a larger, better platoon considering their own utilities under the pre-defined benefit reallocation mechanisms. Depending on whether the trucks are single-brand or multi-brand, whether there is a complete information setting or incomplete information setting, three mechanisms, auction, bilateral trade model, and one-sided matching are proposed. The centralized approach yields a near-optimal solution for the whole system and is more computationally efficient than conventional algorithms. The decentralized approach is stable, more flexible, and computational efficient while maintaining acceptable degrees of optimality. The mechanisms proposed can apply to not only under the truck platooning scenario but also other forms of shared mobility. Advisors/Committee Members: Yin, Yafeng (committee member), Shen, Siqian May (committee member), Liu, Henry (committee member), Masoud, Neda (committee member).

Subjects/Keywords: cooperative truck platooning; energy-saving potentials; benefit reallocation mechanisms; optimal platoon formation; shared mobility; Civil and Environmental Engineering; Engineering

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Sun, X. (2020). Facilitating Cooperative Truck Platooning for Energy Savings: Path Planning, Platoon Formation and Benefit Redistribution. (Doctoral Dissertation). University of Michigan. Retrieved from http://hdl.handle.net/2027.42/163047

Chicago Manual of Style (16^th Edition):

Sun, Xiaotong. “Facilitating Cooperative Truck Platooning for Energy Savings: Path Planning, Platoon Formation and Benefit Redistribution.” 2020. Doctoral Dissertation, University of Michigan. Accessed April 19, 2021. http://hdl.handle.net/2027.42/163047.

MLA Handbook (7^th Edition):

Sun, Xiaotong. “Facilitating Cooperative Truck Platooning for Energy Savings: Path Planning, Platoon Formation and Benefit Redistribution.” 2020. Web. 19 Apr 2021.

Vancouver:

Sun X. Facilitating Cooperative Truck Platooning for Energy Savings: Path Planning, Platoon Formation and Benefit Redistribution. [Internet] [Doctoral dissertation]. University of Michigan; 2020. [cited 2021 Apr 19]. Available from: http://hdl.handle.net/2027.42/163047.

Council of Science Editors:

Sun X. Facilitating Cooperative Truck Platooning for Energy Savings: Path Planning, Platoon Formation and Benefit Redistribution. [Doctoral Dissertation]. University of Michigan; 2020. Available from: http://hdl.handle.net/2027.42/163047

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Open Access Theses and Dissertations