A Hierarchical Approach to Optimal Flow-Based Routing and Coordination of Connected and Automated Vehicles

This paper addresses the challenge of generating optimal vehicle flow at the macroscopic level. Although several studies have focused on optimizing vehicle flow, little attention has been given to ensuring it can be practically achieved. To overcome this issue, we propose a route-recovery and eco-driving strategy for connected and automated vehicles (CAVs) that guarantees optimal flow generation. Our approach involves identifying the optimal vehicle flow that minimizes total travel time, given the constant travel demands in urban areas. We then develop a heuristic route-recovery algorithm to assign routes to CAVs that satisfy all travel demands while maintaining the optimal flow. Our method lets CAVs arrive at each road segment at their desired arrival time based on their assigned route and desired flow. In addition, we present an efficient coordination framework to minimize the energy consumption of CAVs and prevent collisions while crossing intersections. The proposed method can effectively generate optimal vehicle flow and potentially reduce travel time and energy consumption in urban areas.Comment: 7 pages, 7 figure

Routing in Mixed Transportation Systems for Mobility Equity

This letter proposes a routing framework in mixed transportation systems for improving mobility equity. We present a strategic routing game that governs interactions between compliant and noncompliant vehicles, where noncompliant vehicles are modeled with cognitive hierarchy theory. Then, we introduce a mobility equity metric (MEM) to quantify the accessibility and fairness in the transportation network. We integrate the MEM into the routing framework to optimize it with adjustable weights for different transportation modes. The proposed approach bridges the gap between technological advancements and societal goals in mixed transportation systems to enhance efficiency and equity. We provide numerical examples and analysis of the results.Comment: 6 pages, 5 figure

Modeling Travel Behavior in Mobility Systems with an Atomic Routing Game and Prospect Theory

In this paper, we present a game-theoretic modeling framework for studying the travel behavior in mobility systems, by incorporating prospect theory. As part of our motivation, we conducted an experiment in a scaled smart city to investigate the frequency of errors in actual and perceived probabilities of a highway route under free flow conditions. Based on these findings, we provide a game that captures how travelers distribute their traffic flows in a transportation network with splittable traffic, utilizing the Bureau of Public Roads function to establish the relationship between traffic flow and travel time cost. Given the inherent non-linearities, we propose a smooth approximation function that helps us estimate the prospect-theoretic cost functions. As part of our analysis, we characterize the best-fit parameters and derive an upper bound for the error. We then show a Nash Equilibrium existence. Finally, we present a numerical example and simulations to verify the theoretical results and demonstrate the effectiveness of our approximation.Comment: arXiv admin note: text overlap with arXiv:2202.0769

Congestion-Aware Routing, Rebalancing, and Charging Scheduling for Electric Autonomous Mobility-on-Demand System

In this paper, we investigate the problem of routing, rebalancing, and charging for electric autonomous mobility-on-demand systems concerning traffic congestion. We analyze the problem at the macroscopical level and use a volume-delay function to capture traffic congestion. To address this problem, we first formulate an optimization problem for routing and rebalancing. Then, we present heuristic algorithms to find the loop of the traffic flow and examine the energy constraints within the resulting loop. We impose charging constraints on the re-routing problem so that the new solution satisfies the energy constraint. Finally, we verify the effectiveness of our method through simulation.Comment: 6 pages, 2 figure

Combined Optimal Routing and Coordination of Connected and Automated Vehicles

In this letter, we consider a transportation network with a 100\% penetration rate of connected and automated vehicles (CAVs) and present an optimal routing approach that takes into account the efficiency achieved in the network by coordinating the CAVs at specific traffic scenarios, e.g., intersections, merging roadways, and roundabouts. To derive the optimal route of a travel request, we use the information of the CAVs that have already received a routing solution. This enables each CAV to consider the traffic conditions on the roads. The solution of any new travel request determines the optimal travel time at each traffic scenario while satisfying all state, control, and safety constraints. We validate the performance of our framework through numerical simulations. To the best of our knowledge, this is the first attempt to consider the coordination of CAVs in a routing problem.Comment: 6 pages, 5 figure

Energy-Optimal Goal Assignment of Multi-Agent System with Goal Trajectories in Polynomials

In this paper, we propose an approach for solving an energy-optimal goal assignment problem to generate the desired formation in multi-agent systems. Each agent solves a decentralized optimization problem with only local information about its neighboring agents and the goals. The optimization problem consists of two sub-problems. The first problem seeks to minimize the energy for each agent to reach certain goals, while the second problem entreats an optimal combination of goal and agent pairs that minimizes the energy cost. By assuming the goal trajectories are given in a polynomial form, we prove the solution to the formulated problem exists globally. Finally, the effectiveness of the proposed approach is validated through the simulation.Comment: 7 pages, 4 figure

Effects of Forest Therapy on Depressive Symptoms among Adults: A Systematic Review

This study systematically reviewed forest therapy programs designed to decrease the level of depression among adults and assessed the methodological rigor and scientific evidence quality of existing research studies to guide future studies. This systematic review was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. The authors independently screened full-text articles from various databases using the following criteria: (1) intervention studies assessing the effects of forest therapy on depressive symptoms in adults aged 18 years and older; (2) studies including at least one control group or condition; (3) peer-reviewed studies; and (4) been published either in English or Korean before July 2016. The Scottish Intercollegiate Guideline Network measurement tool was used to assess the risk of bias in each trial. In the final sample, 28 articles (English: 13, Korean: 15) were included in the systematic review. We concluded that forest therapy is an emerging and effective intervention for decreasing adults’ depression levels. However, the included studies lacked methodological rigor. Future studies assessing the long-term effect of forest therapy on depression using rigorous study designs are needed