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Holding has been extensively investigated as a strategy to mitigate the inherently stochastic nature of public transport operations. Holding focuses on either regulating vehicle headways using a rule-based approach or minimizing passenger travel cost by employing optimization models. This paper introduces a holding decision rule that explicitly addresses passenger travel cost. The decision to hold...
In this paper, we develop a centralized and automated conflict resolution methodology for vehicles that guarantees collision-free motion by coordinating the vehicles' speeds on predetermined paths. A new computationally efficient formulation for collision-free motion constraints of vehicles is proposed. We develop a methodology to maximize the speed and safety distance of vehicles subjected to the...
This paper concerns optimally controlling an autonomous vehicle to perform safe and comfortable overtaking of a slower moving leading vehicle using model predictive control. The contribution of this paper is to further analyze the convex relaxation that was introduced in [1] in order to see how it compares with the standard formulation. The main difference between the formulations is that the sampling...
This paper presents a novel isolated traffic signal control algorithm based on a game-theoretic optimization framework. The algorithm models a signalized intersection considering four phases, where each phase is modeled as a player in a game in which the players cooperate to reach a mutual agreement. The Nash bargaining solution is applied to obtain the optimal control strategy, considering a variable...
Carpooling has been long deemed a promising approach to better utilizing existing transportation infrastructure. However, there are several reasons carpooling is still not the preferred mode of commute in the United States: first, complex human factors, including time constraints and not having right incentive structures, discourage the sharing of rides; second, algorithmic and technical barriers...
By exploring alternative approaches to combinatorial optimization, we propose the first known formal connection between clustering and set partitioning, with the goal of identifying a subclass of set partitioning problems that can be solved efficiently and with optimality guarantees through a clustering approach. We prove the equivalence between classical centroid clustering problems and a special...
This paper describes a real-time capable online path planning on roads and its experimental investigation for the highly maneuverable robotic electric vehicle research platform ROboMObil. The path planning algorithm is based on an efficiently solvable and compact optimization problem and contributes to the autonomous driving of centralized controlled vehicles. The necessary development from a global...
Driver feedback systems have the potential to improve driving safety and efficiency by providing instructions to drivers aimed at improving their driving style. There is already a rich body of available literature devoted to the derivation of energy efficient speed profiles to develop driver feedback or eco-driving systems. While most of them can be applied to any type of vehicle, their effectiveness...
Unmanned and autonomous vehicles (UxV) are one of most attractive and important technologies for many kinds of applications. A lot of researches related to multi UxVs have been made enthusiastically for the last several decades because there is a trend to use those UxVs as a swarm. When the algorisms are implemented in UxVs for real operations, the algorism must adapt to a lot of unexpected environmental...
Various multi-agent decentralized approaches based on reinforcement learning (RL) have been proposed to increase scalability and real-time adaptiveness of urban traffic control (UTC) systems. In such approaches, traffic light control parameters are not pre-defined, but intelligent agents controlling the junctions learn the suitable traffic signal settings. In order to consider applications of RL in...
We revisit the problem of traffic signal control in urban traffic networks. Recent work in the literature has studied the use of scheduling algorithms from communication networks to traffic signal control with the aim of maximising the network throughput. However, these algorithms are unable to capture some of the network characteristics such as protocol constraints or penalties on the control actions,...
Urban transport systems are often not capable to satisfy the numerous needs of urban mobility. Therefore, in recent years great interest has been given in Cooperative Intelligent Transportation Systems (C-ITS), which via two-way communication between road participants and infrastructure allow new solutions addressing transport problems. However, if efficiency improvements only target general traffic,...
We propose a method for ego-lane estimation that can robustly determine the currently used lane as required by future lane-precise navigation systems. It employs a lane-level map-matching on a digital road map through least-squares optimization and only requires sensors available in current production vehicles, such as GPS, odometry, visual lane-marking detection and radars. Radar data is used in...
Arterial coordinated control has practical significance for transit priority control when intersection spacing is relatively short and similar. In this paper we purpose a two-way green-wave optimal signal priority control model for rail transit, the objective is to maximize passenger vehicles' bandwidth of green wave under the constraint of transits' bandwidth with the consideration of transits' and...
Dynamic on-road driving scenarios require robust methods for planning a safe and feasible vehicle motion coping with both static and dynamic obstacles. Many of the different approaches which have been proposed to tackle this challenge are based on optimal control and employ local continuous or discrete optimization schemes. While discrete methods possess the ability to find reasonable solutions in...
Diverging diamond interchanges (DDI) have been proved to outperform other types of diamond interchanges in terms of safety, cost-effectiveness and efficiency, but most of those research efforts were based on case studies using simulation or empirical analysis. Few research efforts have been done to conduct the analytic calculation of delay, with which optimization of timing plans can be acquired more...
Traffic patterns of the lanes accommodating the same movement at signalized intersection are different with each other in most cases, which could decrease the efficiency of signal control. This problem derives from drivers' preferences to specific lane, which is contrary to common control strategy that usually takes the lane traffics as a whole. Lane-based timing technique can solve this problem,...
Traffic congestion has become a common issue in most large cities. Traditional solutions to traffic congestion have not had the expected effect. Investments of public and private agencies only move congestion from one place to another. Thereby, this work proposes solutions to minimize the traffic congestion by balancing the flow of vehicles that traverse the streets, through the allocation of tollbooths...
The aim of this work is the implementation of an intelligent system based ant colony algorithm to control a traffic signal intersection where the main goal is to reduce the average waiting time of the vehicles at the intersection. First a dynamic mathematical model of the flow at an intersection is given. Second, the intelligent system is implemented electronically around an Arduino microcontroller...
Capacitated Arc Routing Problem (CARP) is known as an NP-hard combinatorial optimization problem. Chemical Reaction Optimization (CRO) is a recent metaheuristic inspired by the nature of chemical reactions of molecules and the mechanism of energy redistribution. CRO has been successfully exploited for solving a broad family of continuous and discrete optimization problems. In this paper, we propose...
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