The Multi-objective Dynamic Traveling Salesman Problem: Last Mile Delivery with Unmanned Aerial Vehicles Assistance

Remer, Ben; Malikopoulos, Andreas A.

doi:10.23919/acc.2019.8815099

Cited by 14 publications

(7 citation statements)

References 20 publications

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“…A combination of SAVs with other transportation modes such as public transportation, however, might impose different conclusions [9], [10], [12], [18]. Although SAVs could be utilized in the way to facilitate the first and last mile transport [157] and promote the use of public transportation system (e.g., [154], [158]), SAVs may also divert passengers away from transit systems due to their capability of providing door-to-door services (e.g., [154], [159]).…”

Section: B Operating In a Multi-modal Environmentmentioning

confidence: 99%

Enhanced Mobility With Connectivity and Automation: A Review of Shared Autonomous Vehicle Systems

Zhao

Malikopoulos

2022

IEEE Intell. Transport. Syst. Mag.

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Shared mobility can provide access to transportation on a custom basis without vehicle ownership. The advent of connected and automated vehicle technologies can further enhance the potential benefits of shared mobility systems. Although the implications of a system with shared autonomous vehicles have been investigated, the research reported in the literature has exhibited contradictory outcomes. In this paper, we present a summary of the research efforts in shared autonomous vehicle systems that have been reported in the literature to date and discuss potential future research directions.

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Section: B Operating In a Multi-modal Environmentmentioning

confidence: 99%

Enhanced Mobility With Connectivity and Automation: A Review of Shared Autonomous Vehicle Systems

Zhao

Malikopoulos

2022

IEEE Intell. Transport. Syst. Mag.

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“…(5) Note that in (5) the weights for the objective functions l 1 , l 2 , and l 12 are determined by a weighting strategy using trigonometric functions of the SVO angles φ 1 and φ 2 . In the following theorem, we prove that a Nash equilibrium can be obtained by minimizing (5).…”

Section: A Problem Formulation and Control Frameworkmentioning

confidence: 99%

A Cooperative Optimal Control Framework for Connected and Automated Vehicles in Mixed Traffic Using Social Value Orientation

Le¹,

Malikopoulos²

2022

Preprint

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In this paper, we develop a socially cooperative optimal control framework for connected and automated vehicles (CAVs) in mixed traffic using social value orientation (SVO). In our approach, we formulate the interaction between a CAV and a human-driven vehicle (HDV) as a simultaneous game to facilitate the derivation of a Nash equilibrium. In the imposed game, each vehicle minimizes a weighted sum of its egoistic objective and a cooperative objective. The SVO angles are used to quantify preferences of the vehicles toward the egoistic and cooperative objectives which lead to an appropriate design of weighting factors in a multi-objective optimal control problem. We prove that by solving the proposed optimal control problem, a Nash equilibrium can be obtained. To estimate the SVO angle of the HDV, we develop a receding horizon estimation based on maximum entropy inverse reinforcement learning. The effectiveness of the proposed approach is demonstrated by numerical simulations at a highway on-ramp merging scenario.

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“…We designed IDS 3 C with the capacity to experimentally validate a wide variety of urban traffic scenarios. This includes eco-routing, mixed traffic [7], ride sharing [123], and air-ground coordination [124]. In several recent efforts, we have used IDS 3 C to implement and validate control algorithms for coordinating CAVs at traffic scenarios, such as merging roadways [68], roundabouts [77], intersections [43], adjacent intersections [56]- [58], and corridors [125].…”

Section: Information and Decision Science Lab's Scaled Smart Citymentioning

confidence: 99%

A Research and Educational Robotic Testbed for Real-time Control of Emerging Mobility Systems: From Theory to Scaled Experiments

Chalaki¹,

Beaver²,

Mahbub³

et al. 2021

Preprint

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Emerging mobility systems, e.g., connected and automated vehicles (CAVs), shared mobility, mark a paradigm shift in which a myriad of opportunities exist for users to better monitor the transportation network conditions and make optimal operating decisions to improve safety and reduce pollution, energy consumption, and travel delays [1]. Emerging mobility systems are typical cyber-physical systems where the cyber component (e.g., data and shared information through vehicle-to-vehicle and vehicle-to-infrastructure communication) can aim at optimally controlling the physical entities (e.g., CAVs, non-CAVs). The cyber-physical nature of such systems is associated with significant control challenges and gives rise to a new level of complexity in modeling and control [2]. As we move to increasingly complex emerging mobility systems, new control approaches are needed to optimize the impact on system behavior [3] of the interplay between vehicles at different traffic scenarios [4]. It is expected that CAVs will gradually penetrate the market and interact with human-driven vehicles in ways that will improve safety and transportation efficiency over the next several years. However, different levels of vehicle automation in the transportation network can significantly alter transportation efficiency metrics [5] ranging from 45% improvement to 60% deterioration. Moreover, we anticipate that efficient transportation and travel cost reduction might alter human travel behavior causing rebound effects, e.g., by improving efficiency, travel cost is decreased, hence willingness-to-travel is increased. The latter would increase overall vehicle miles traveled, which in turn might negate the benefits in terms of energy and travel time.Several studies have shown the benefits of CAVs to reduce energy and alleviate traffic congestion in specific transportation scenarios [6]-[8]. There have been two major approaches to utilizing connectivity and automation of vehicles, namely, platooning and traffic smoothing. A platoon is defined as a group of closely-coupled vehicles traveling to reduce their aerodynamic drag, especially at high cruising speeds. The concept of platoon formation is a popular systemlevel approach to address traffic congestion, which gained momentum in the 1980s and 1990s

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The Multi-objective Dynamic Traveling Salesman Problem: Last Mile Delivery with Unmanned Aerial Vehicles Assistance

Cited by 14 publications

References 20 publications

Enhanced Mobility With Connectivity and Automation: A Review of Shared Autonomous Vehicle Systems

Enhanced Mobility With Connectivity and Automation: A Review of Shared Autonomous Vehicle Systems

A Cooperative Optimal Control Framework for Connected and Automated Vehicles in Mixed Traffic Using Social Value Orientation

A Research and Educational Robotic Testbed for Real-time Control of Emerging Mobility Systems: From Theory to Scaled Experiments

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