Mobile parcel lockers have been recently proposed by logistics operators as a technology that could help reduce traffic congestion and operational costs in urban freight distribution. Given their ability to relocate throughout area of deployment, they hold the potential improve customer accessibility convenience. In this study, we formulate Parcel Locker Problem (MPLP) , special case Location-Routing (LRP) which determines optimal stopover location for MPLs day plans corresponding delivery...

Unmanned aerial vehicles (UAVs) are being increasingly implemented in a range of applications. Their low payload capacity and ability to overcome congested road networks enables them provide fast delivery services for urgent high-value low-volume cargo. This work investigates the economic viability integrating UAVs into urban hospital supply chains. In doing so, strategic model that determines optimal configuration supporting infrastructure UAV between hospitals is proposed. The incorporates...

Abstract Unmanned aerial vehicles (UAVs) have been increasingly viewed as useful tools to assist humanitarian response in recent years. While organisations already employ UAVs for damage assessment during relief delivery, there is a lack of research into formalising problem that considers both aspects simultaneously. This paper presents novel endogenous stochastic vehicle routing coordinates UAV and deployments minimise overall mission cost. The algorithm levels transport network, with...

The increasing level of congestion and infrastructure costs in cities have created a need for more intelligent flexible transport systems. Urban Air Mobility (UAM) introduces the third dimension to intra-urban at minimal cost, bypassing providing reliable travel times users through provision air passenger transportation. performance UAM systems is highly dependent on vertiport locations, vehicle sizing specifications, which themselves are intrinsically linked. This study takes holistic...

Abstract The right Asphaltene Inhibitor (AI) selection is crucial for the control of asphaltene issues in oil production. Although many factors contribute precipitation/deposition fields, chemical process laboratory were often conducted only under ambient temperature and pressure. In this paper, we introduced a multifaceted approach inhibitor to overcome test condition discrepancy between fields. importance on performance chemicals was evidenced by our high optical scanning device results....

Large-scale evacuations constitute common life-saving exercises that are activated in many disaster response campaigns. Their effectiveness is often inhibited by traffic congestion, disrupted and imperfect coordination mechanisms, the poor state of underlying transportation networks. To address this problem, paper presents a hybrid simulation-optimisation methodology to optimise evacuation strategies through demand staging signal phasing. We introduce pre-planning model evaluates policies,...

The uptake of Electric Vehicles (EVs) is rapidly changing the landscape urban mobility services. Transportation Network Companies (TNCs) have been following this trend by increasing number EVs in their fleets. Recently, major TNCs explored prospect establishing privately owned charging facilities that will enable faster and more economic charging. Given scale complexity TNC operations, such decisions need to consider both requirements local planning regulations. Therefore, an optimisation...

Wind speed affects aviation performance, clean energy production, and other applications. By accurately predicting wind speed, operational delays accidents can be avoided, while the efficiency of production also increased. This paper initially overviews definition, characteristics, sensors capable measuring feature, relationship between this feature for all Quality Indicators (QIs). Subsequently, importance each QI relevant to wind-speed prediction is assessed, QIs are employed predict...

With growing air travel demand, weather disruptions cost millions in flight delays and cancellations. Current resilience analysis research has been focused on airports airlines, rather than the en-route waypoints, failed to consider impact of disruption scenarios. This paper analyses United Kingdom (UK) traffic network events that disrupt network’s high-traffic areas. A Demand Capacity Balancing (DCB) model is used simulate adverse re-optimise cancellation, delay, rerouting flights. The...

Complete streets scheme makes seminal contributions to securing the basic public right-of-way (ROW), improving road safety, and maintaining high traffic efficiency for all modes of commute. However, such a popular street design paradigm also faces endogenous pressures like appeal more balanced ROW non-vehicular users. In addition, deployment Autonomous Vehicle (AV) mobility is likely challenge conventional use space as well this scheme. Previous studies have invented automated control...

Same-day delivery (SDD) services have become increasingly popular in recent years. These been usually modeled by previous studies as a certain class of dynamic vehicle routing problem (DVRP) where goods must be delivered from depot to set customers the same day that orders were placed. Adaptive exact solution methods for DVRPs can intractable even small instances. In this paper, same-day (SDDP) is formulated Markov decision process (MDP) and it solved using parameter-sharing Deep Q-Network,...

The growing demand for air travel has led to the saturation of traffic networks. Conventional methods adding routes alleviate congestion and reduce delays may not achieve desired effect even degrade system performance. In this paper, we explore application Braess's Paradox in reduction This counterintuitive phenomenon shows that new connections a network can actually increase overall pressure. study uses Hidden Markov Viterbi algorithm match flow with routes, machine learning approach...

To understand the dynamics of an autonomous ridesharing transport mode from perspectives different stakeholders, a single model such system is essential, because this will enable policymakers and companies involved in manufacture operation shared vehicles (SAVs) to develop user-centered strategies. The needs be based on real data, network, traffic information applied cities situations, particularly those with complex public transportation systems. In paper, we propose new agent-based for SAV...

Last-mile logistics operators have recently introduced mobile parcel lockers (MPLs) and autonomous delivery robots (ADRs) to alleviate traffic congestion operational costs. Their ability relocate their position during the day has potential improve customer accessibility convenience, allowing customers collect parcels at preferred time among one of multiple locations. Previous research on MPLs ADRs primarily focuses operations analysis microscopic optimisation models (e.g., location-routing...

This paper presents a novel real-time dispatching algorithm using Deep Reinforcement Learning (DRL) designed to optimise autonomous haulage trucks' operations in open-pit mining. Our DRL model, simulated within an environment that accurately replicates truck behaviours, accounts for vehicle interactions - aspect typically challenging conventional mathematical optimisation approaches. Further distinguishing this work is the model's ability adapt varying fleet sizes without requiring...

Collaborative navigation becomes essential in situations of occluded scenarios autonomous driving where independent policies are likely to lead collisions. One promising approach address this issue is through the use Vehicle-to-Vehicle (V2V) networks that allow for sharing perception information with nearby agents, preventing catastrophic accidents. In article, we propose a collaborative control method based on V2V network compressed LiDAR features and employing Proximal Policy Optimisation...

The deployment of Autonomous Vehicles (AVs) poses considerable challenges and unique opportunities for the design management future urban road infrastructure. In light this disruptive transformation, Right-Of-Way (ROW) composition space has potential to be renewed. Design approaches intelligent control models have been proposed address problem, but we lack an operational framework that can dynamically generate ROW plans AVs pedestrians in response real-time demand. Based on microscopic...