Search

In this paper, we consider an extension of the Dynamic Vehicle Routing Problem with Backhauls integrated with two-dimensional loading problem called DVRPB with 2D loading constraints (2L-DVRPB). In the VRPB, a vehicle can deliver (Linehaul) then collect goods from customers (backhaul) and bring back to the depot. Once customer demand is formed by a set of two-dimensional items the problem will be treat as a 2L-VRPB. The 2L-VRPB has been studied on the static case. However, in most real-life application, new customer requests can be happen over time of backhaul and thus perturb the optimal routing schedule that was originally invented. This problem has not been analysed sofar in the literature. The 2L-DVRPB is an NP-Hard problem, so, we propose to use a Genetic algorithm for routing and a packing problems. We applied our approach in a real case study of the Regional Post Office of the city of Jendouba in the North of Tunisia. Results indicate that the AGA approach is considered as the best approach in terms of solutions quality for a real world routing system.

This paper addresses the experimental verification of vertical displacement predictions for a highway bridge under dynamic vehicle loads. In the structural health monitoring of bridge structures, the measurements of vertical displacements are relatively difficult than the measurements of axial strains, and the vertical displacements can give an intuitive information for monitoring the structural conditions. Therefore, an artificial neural network (ANN) was introduced for the accurate predictions of the vertical displacements from the axial strains. In the experiments, both the strains and displacements at the different locations were measured during 48 h for obtaining the training (Set 1) and testing (Set 2) data, which were utilized to develop and validate the ANN-based prediction model. The environmental effects such as temperature loads were eliminated from the experimental data using a calibration approach, and the pure contributions of the external vehicle loadings to the 3D highway bridge were considered. The validation results showed that the ANN-based model can accurately predict the vertical displacements. It is expected that the proposed ANN-based model, as a fast and accurate framework, can be utilized for various civil infrastructures during the structural health monitoring.

This paper compares different track model formulations for the simulation of dynamic vehicle–track interaction in switches and crossings (S&C, turnouts) in a multi-body simulation (MBS) environment. The investigations are an extension of the S&C simulation Benchmark with the addition of a finite element model of a 60E1-760-1:15 turnout. This model constitutes a common reference from which four different track formulations are derived: co-running, modal superposition, finite element incorporated into the MBS model and finite element coupled to MBS using a co-simulation approach. For the different track models, the difference in modelling technique, results, simulation time, and suitability for different simulation tasks is compared. A good agreement is found between the different track model formulations for wheel–rail contact forces and rail displacements. This study found a better agreement between co-running and structural track models compared to previous studies in the prediction of wheel–rail contact forces. This appears to be due to the increased complexity of co-running track model used in this study together with a tuning of the co-running track model to the reference model in a wider frequency range. For the reader interested to reproduce the results in this paper, the reference track model is available for download.

The advancement and development of technologies promote more interest in exploring Dynamic Vehicle Routing Problems (DVRP), especially in Home Healthcare. Home healthcare (HHC) has gained more attention from researchers in recent years due to its increasing demand. There are certain cases where some patients may require one or more care services concurrently. In such a situation, synchronization of vehicles within specific time slots is necessary. The inclusion of dynamic patients and synchronization of vehicles without disregarding the time window will transform into a formidable task for HHC organizations. Hence, the investigation of the Dynamic Vehicle Routing problem where Synchronization occurs within the Time Slots (DVRPSTS) becomes a remarkable model in the context of HHC. This paper proposed one such complex endeavour considering multi-objectives such as (i) minimize the total travel time and the number of vehicles utilized (ii) maximize the number of new patients visits in HHC. The accuracy and efficiency of the proposed algorithm Mutated Cuckoo Search Algorithm (MCSA) are validated by comparing its results with existing methods in the literature. Thus, this algorithm outperforms most of the randomly generated test instances. To the best of our knowledge, the proposed MCSA has not yet been modelled for the DVRPSTS in HHC.

A Benchmark of railway multibody dynamics software application to switches and crossings (S&C) is presented, comparing all major commercially available software and a few independent codes. Two different representative S&C have been implemented, using the Manchester Benchmark passenger vehicle. The final results show that all software offer a reliable and efficient way to understand the kinematic and dynamics forces between the wheels and the track elements. The highest challenges are found when modelling a combination of multiple rails in simultaneous contact with a wheel (check-stock or switch-stock), large longitudinal variations in rail shape (crossings) and high lateral steering forces (diverging cases in tight radius). In those cases, the codes able to account for the exact relative motion of each wheels with respect to each rails independently are the most apt. The most significant variations between software are found in the contact prediction with an influence on the detailed contact tangential and normal forces. The user variability is found to be very small, with the most time-consuming and error prone being the task of handling the input data for the variable rails definition. All software could benefit from improvements to assist the user and ensure higher reliability and efficiency generally.

In downtown areas of large cities, it is very challenging for drivers to find available parking spots, even when they are provided with information on parking availability and location information. To overcome this challenge, this paper develops a dynamic vehicle routing system to search for the optimal routes for connected vehicles to find parking spots successfully and to minimize total trip time, including driving time and walking time. The system predicts the probability of each parking lot having available parking spots based on the existing available number of spots and the vehicle arrival and departure rates collected by connected vehicles. This probability is integrated in the search for vehicle routes to minimize total travel and walking times. Numerical experiments indicate that the proposed system can reduce the cruising time spent searching for available parking spots, and the total trip time can be reduced by up to 24%. In addition, the system can decrease the number of re-routing decisions, which reduces the stress of drivers on the road. A sensitivity analysis of the parking probability is also conducted. Some future work based on the proposed system is proposed in the conclusion to this paper.

This paper presents the final description for the S&C Benchmark that was launched at the IAVSD 2019 conference held in Gothenburg, Sweden and completed by eighteen participants by the end of 2020. The purpose of this paper is to allow for the replication of the Benchmark exercise after publication for those who wish to do so in the future, and it includes a link to the repository containing all necessary input data. The original task description, including a description of the Benchmark submission, is presented in full. The results from the Benchmark are available in [Bezin Y, Palsson BA, Kik W, et al. Multibody simulation Benchmark for dynamic vehicle-track interaction in switches and crossings: results and method statements. Submitted to VSD, 2021].

The increase in the size of the city and the increase in population mobility have greatly increased the number of vehicles on the road, and at the same time brought considerable challenges to the traffic management department. In recent years, more and more experts and scholars have devoted themselves to applying sensors, network communication and dynamic adaptive technologies to road traffic management systems. At present, people have not completely overcome all kinds of complex problems in traffic supervision. The complexity of traffic information and the defects of identification algorithms have brought great challenges to intelligent traffic management. This article has launched a research on the intelligent Internet of Things traffic management system, with the detection and recognition of stationary vehicles and seat belts as the key analysis targets. When monitoring stationary vehicles, this paper replaces the background difference algorithm commonly used in dynamic vehicle detection with a new recognition algorithm. From the experimental results, the average detection accuracy of the new algorithm is 96.77% higher than the previous 87.56%. When studying the driver's seat belt detection, this paper combines the YOLOv3 target detection algorithm and the lightweight network structure, and proposes a driver-oriented positioning algorithm. With the increase in the number of lightweight templates, the accuracy of the positioning algorithm has increased from 80.57 to 99.98%. But on the other hand, the detection speed has also changed from 78 to 69 frames/s.

Cooperative Adaptive Cruise Control (CACC) is an advanced technique for organizing and managing a vehicle platoon, which employs the Vehicle-to-Vehicle/Vehicle-to-Infrastructure (V2V/V2I, or V2X) wireless communication to minimize the inter-vehicle distance while guaranteeing string-stability. Consequently, the conventional CACC system relies heavily on the quality of communications, which means that the regular CACC platoon is sensitive to the communication failure. Therefore, in this paper, a Safety Reinforced Cooperative Adaptive Cruise Control (SR-CACC) strategy is proposed to resist unexpected communication failure. Different from the regular CACC system, the safety enhanced platoon control system is embedded with a dual-branch control strategy. When a fatal wireless communication failure is detected and confirmed, the SR-CACC system will automatically activate the alternative sensor-based adaptive cruise control strategy. Moreover, to make the transforming process smooth, a linear smooth transition algorithm is added to the SR-CACC system. Then, to verify the performance of the proposed SR-CACC system, we conducted a simulation experiment with a heterogonous platoon constructed with eight vehicles. The experiments results reveal that, under the extremely poor communication environment, the proposed SR-CACC strategy can significantly improve the safety performance of the organized vehicle platoon.

Recently, the explosion of large amounts of traffic data has guided data scientists to create models with big data for a better decision-making. Big Data applications process and analyze this huge amounts of data (collected from a variety of heterogeneous data sources) that cannot be processed with traditional technologies. In this paper, Big Data frameworks are used for solving an optimization problem known as Dynamic Vehicle Routing Problem (DVRP). Hence, due to the NP-Hardness of the problem and to deal with a large size of data, we develop a parallel Spark Genetic Algorithm named (S-GA). This parallelism aims to take the advantage of Spark’s in-memory computing ability (as a master-slave distribution computing) and GA’s iterations operations. Parallel operations were used for fitness evaluation and genetic operations. Based on the parallel S-GA a decision support system is developed for the DVRP in order to generate the best routes. The experiments show that our proposed architecture is improved due to its capacity when coping with Big Data optimization problems by interconnecting components and deploying on different nodes of a cluster.

Autonomous vehicles are drawing significant attention from governments, manufacturers and consumers. Experts predict them to be the primary means of transportation by the middle of this century. Recent literature shows that vehicle automation has the potential to alter traffic patterns, vehicle ownership, and land use, which may affect fuel consumption from the transportation sector. In this paper, we developed a data-rich analytical framework to quantify system-wide fuel impacts of automation in the United States by integrating (1) a dynamic vehicle sales, stock, and usage model, (2) an historical transportation network-level vehicle miles traveled (VMT)/vehicle activity database, and (3) estimates of automation’s impacts on fuel efficiency and travel demand. The vehicle model considers dynamics in vehicle fleet turnover and fuel efficiency improvements of conventional and advanced vehicle fleet. The network activity database contains VMT, free-flow speeds, and historical speeds of road links that can help us accurately identify fuel-savings opportunities of automation. Based on the model setup and assumptions, we found that the impacts of automation on fuel consumption are quite wide-ranging—with the potential to reduce fuel consumption by 45% in our “Optimistic” case or increase it by 30% in our “Pessimistic” case. Second, implementing automation on urban roads could potentially result in larger fuel savings compared with highway automation because of the driving features of urban roads. Through scenario analysis, we showed that the proposed framework can be used for refined assessments as better data on vehicle-level fuel efficiency and travel demand impacts of automation become available.

The Dynamic Vehicle Routing Problem (DVRP) is a variant of the VRP that considers dynamic customer requests. The aim of the problem is to determine a set of routes to minimize the total travel distance. To solve this problem, we propose a Variable Neighbourhood Search (VNS) algorithm, in which eight neighborhood structures are designed to find the optimal routes for a fleet of vehicles serving a given customers without violating any constraints. The proposed algorithm was tested on benchmark instances. Numerical results indicate that the performance of the proposed method is comparable to that reported in the literature.

For the problem of heterogenous fleet dynamic vehicle rounting, a memetic algorithm was proposed to optimize the minimum vehicle number and transportation cost. In order to improve the global exploration ability of the algorithm, an improved distribution estimation algorithm is used in the pre-optimization phase of global search, Quantum genetic algorithm is used in real - time optimization. The client node reset and 2-opt algorithm are adopted to enhance the local search ability of the algorithm. Finally, the validity of the algorithm is verified by simulation experiments.

For fatigue damage prognosis of a long-span steel bridge, the dynamic stress analysis of critical structural components of the bridge under the future dynamic vehicle loading is essential. ...

Although increasing amounts of transaction data make it possible to characterize uncertainties surrounding customer service requests, few methods integrate predictive tools with prescriptive optimization procedures to meet growing demand for small-volume urban transport services. We incorporate temporal and spatial anticipation of service requests into approximate dynamic programming (ADP) procedures to yield dynamic routing policies for the single-vehicle routing problem with stochastic service requests, an important problem in city-based logistics. We contribute to the routing literature as well as to the field of ADP. We combine offline value function approximation (VFA) with online rollout algorithms resulting in a high-quality, computationally tractable policy. Our offline–online policy enhances the anticipation of the VFA policy, yielding spatial and temporal anticipation of requests and routing developments. Our combination of VFA with rollout algorithms demonstrates the potential benefit of using offline and online methods in tandem as a hybrid ADP procedure, making possible higher-quality policies with reduced computational requirements for real-time decision making. Finally, we identify a policy improvement guarantee applicable to VFA-based rollout algorithms, showing that base policies composed of deterministic decision rules lead to rollout policies with performance at least as strong as that of their base policy.

This study makes use of monocular digital photography, based on the IM-STBP (image matching-space time baseline parallax) method, to monitor bridge dynamic deformation to study bridge dynamic properties. A bridge was first photographed when traffic light was red (i.e., when the bridge was not influenced by dynamic vehicle load) to generate the zero image (a.k.a. the reference image), and then photographed every 3 s when the traffic light was green (i.e., when the bridge was influenced by dynamic vehicle load) to produce image sequences as successive images. Relative deformation values of deformation points were obtained based on the IM-STBP method. The results show that the measurement accuracy of the IM-STBP method reaches a sub-pixel level (0.445, 0.470 and 0.705 pixels in the X, Z and comprehensive directions, respectively) and that maximal deflections of the bridge monitored by cameras 1 and 3 (37.22 and 47.40 mm, respectively) are within bridge deflection tolerance (75 mm). The monocular digital photography presented in this study has proved effective in monitoring bridge dynamic deformation even when the photographing direction is not perpendicular to the bridge plane and useful in assessing the situation of a bridge by monitoring the instantaneous dynamic global deformation of a bridge when the traffic light is green. Deformation curves in real time can also provide warning of any possible danger on the bridge. These global deformation curves of a bridge play a key role in studying the dynamic properties of a bridge influenced by dynamic vehicle load.

The problem of the lateral instability of the vehicle is a top concern. When the vehicle steers at high speed, it may rollover. In order to limit this situation, the solution of using the stabilizer bar is proposed. This research focuses on establishing the spatial dynamic vehicle model (10 DOF) to simulate the oscillation of the vehicle. Besides, this research has established a new method for calculating the impact force of the stabilizer bar on a vehicle. This method is very intuitive, simple, and highly accurate. The results of the research have indicated that when the vehicle has been equipped with the stabilizer bar, the roll angle of the vehicle has been reduced. At high speeds and a large steering angle, the value of the impact force of the stabilizer bar increases significantly. The value of the impact force of the stabilizer bar at the rear axle is usually larger than the front axle. The new method established in this research may be applied to other researches in the future.

Real-time planning and control play essential roles in autonomous driving under the structured environments. In this paper, a hierarchical planning and control framework is proposed to enable safe and robust self-driving of the ego vehicle. Instead of rule-based decision making, a Markov Decision Process (MDP) is employed for automated decision making by assessing dominant factors of driving stability, efficiency and safety. A real-time trajectory smoother is combined with versatile low level controllers. In addition, the sensor detection limitation is considered in the longitudinal control, which regulates vehicle cruising, following and collision avoidance with smooth speed profile. The proposed framework alleviates the high level planning responsibility and increase the system reliability. Simulations are performed on a dynamic vehicle model in a two-lane environment based on OpenDRIVE standards. The efficiency and effectiveness of the proposed technique are verified.

This paper analyzes the vertical dynamic response of a railway track subjected to traffic loads in a turnout, especially around the switch blades and the crossing nose. In order to study the influence of vehicle and track parameters on the vehicle-track dynamics, a numerical feedback interaction between a multi-body model of the vehicle and a 3D finite elements model of the track is carried out. For this purpose, two different models are developed. In the first one, the track is modeled by means of a FE model in the time domain through ANSYS software; while in the second one, the vehicle is simulated as a multi-body model by means of VAMPIRE PRO software. The influence of different parameters (e.g., speed, sprung masses, track stiffness and vehicle eigenfrequencies) on the generation of dynamic loads in a turnout, especially in the switch blades and the crossing nose, is studied. Finally, the vibrations induced by the passing of the vehicle are calculated for different scenarios.

This paper presents a practical solution to the determination of the spatial pose of the driving recorder from road image of two parallel lanes. Our new solver considers the misalignment between optical axis and road direction, which is more suitable for the road traffic accident scenes. On this basis, the vehicle grounding location and video properties are combined to achieve target vehicle speed reconstruction. Finally, the static pose calculation and dynamic vehicle speed measurement experiments are carried out respectively. The results analysis shows that the recorder's spatial pose reduction is accurate, and the relative error of target vehicle speed under the same lane does not exceed ±5%, which satisfies the demand for road traffic accident speed measurement, and can be used as a useful supplement to the existing accident vehicle speed measurement methods.

The vertical dynamic vehicle–track interaction in a railway crossing is simulated in the time domain based on a moving Green’s function approach in combination with an implementation of Kalker’s variational method to solve the non-Hertzian, and potentially multiple, wheel–rail contact. The method is demonstrated by calculating the wheel–rail impact load and the sleeper–ballast contact pressure for a hollow-worn wheel profile passing over a nominal crossing geometry.

Nowadays, many scientists and companies in the automotive sector in the world are undertaking many important studies on electric vehicle technologies. For the electric vehicle to function as desired, the subsystems of the vehicle must be monitored and the parameters related to the vehicle must be kept in the most efficient range. Efficient use of these systems in electric vehicle will increase the vehicle range, as well as ensure the long life of the components used in the vehicle subsystems. Today, problem areas such as calculating the range of electric vehicles and battery state of charge have not yet been sufficiently standardized. The aim of this study is to make a range estimation in electric vehicle with fuzzy logic classifier which has been successfully applied in various problem areas. The fuzzy logic classifier is designed for range estimation, which is one of the most important research areas of electric vehicles today. In the Mamdani type fuzzy logic approach, dynamic vehicle parameters are taken into consideration. The fuzzy logic classifier considers the battery parameters of the vehicle and the power consumed instantly. In the prediction system, the power spent on the vehicle and the battery charge status are selected as inputs. The developed system was evaluated with three different test scenarios on the same track. These tests were conducted with no load (driver only), half load (driver + one person) and fully load (driver + three persons). The fuzzy logic classifier system determines in real-time how far electric vehicle can travel. (C) 2020 Elsevier Ltd. All rights reserved. Karabuk University Electric Vehicles Team (KBUELAR)Karabuk University; Scientific and Technological Research Council of Turkey (TUBITAK)Turkiye Bilimsel ve Teknolojik Arastirma Kurumu (TUBITAK); Karabuk University Scientific Research Projects (BAP)Karabuk University [KBU-BAP-16/1-YL-098] This study was financially funded by Karabuk University Electric Vehicles Team (KBUELAR), of which The Scientific and Technological Research Council of Turkey (TUBITAK) is the major funder, and Karabuk University Scientific Research Projects (BAP; Project Number: KBU-BAP-16/1-YL-098). WOS:000530032500008 2-s2.0-85079861742

This paper presents a parameterized structural track model for the simulation of dynamic vehicle-turnout interaction in a multi body simulation environment. The model is demonstrated by performing simulations for different vehicle speeds, crossing geometries and fixations between crossing rail and sleepers with different stiffness. Results are presented for dynamic wheel-rail contact forces, bending moments in crossing rail and sleepers and sleeper-ballast contact pressure. The main conclusions are that (a) the peak dynamic bending moment in the sleeper under the crossing transition is significantly higher with a stiff direct fixing compared to a softer indirect fixing and (b) the structural loading in terms of bending moment in the crossing rail, bending moment in the underlaying sleeper and sleeper-ballast contact pressure increases proportionally and significantly with increased impact angle and vehicle speed for wheels passing over the crossing transition.

Many applications in intelligent transportation systems are demanding an accurate vehicle GPS location prediction. In this study, we satisfy this demand by designing an automated GPS location prediction system based on the well known traditional Auto-Regressive Integrated Moving Average (ARIMA). To increase the proposed model accuracy, make it dynamic, and reduce its execution time, the traditional ARIMA model has been modified extensively. To perform GPS location prediction, the proposed model depends on a given vehicle previous locations to predict the vehicle future location. To make it dynamic, the proposed model is designed to regenerate all its parameters every period and only consider a specified window in the history. The proposed model is evaluated based on real vehicle dataset traces that we recorded using an app on a smart phone. The results show that the proposed framework can generate ARIMA models that can predict the GPS location of a vehicle in the future accurately and with a reasonable execution time. If the application needs harder deadline (shorter deadline), we propose to use the last ready model to predict the next vehicle’s GPS location.

This paper presents the development of a decision-support system for programming and routing vehicles dynamically for demands arising over the transportation execution of wheelchair users. For solving the problem is proposed an algorithm for inserting the new requests in existing routes which were developed in a Visual Basic For Applications language. The system is tested with 20 real instances of a real transportation system dedicated to wheelchair transportation and the results shows that the system is capable of handling the dynamic characteristic of the problem, accepting or refusing the new requests and generating solutions with a mean time of five seconds/request.

This paper proposes a dynamic vehicle routing problem (DVRP) model with nonstationary stochastic travel times under traffic congestion. Depending on the traffic conditions, the travel time between two nodes, particularly in a city, may not be proportional to distance and changes both dynamically and stochastically over time. Considering this environment, we propose a Markov decision process model to solve this problem and adopt a rollout-based approach to the solution, using approximate dynamic programming to avoid the curse of dimensionality. We also investigate how to estimate the probability distribution of travel times of arcs which, reflecting reality, are considered to consist of multiple road segments. Experiments are conducted using a real-world problem faced by Singapore logistics/delivery company and authentic road traffic information.

This paper addresses the methodology of the bridge-vehicle dynamic model definition based on the free response measurements of an existing train and existing bridge spans. In the case of the railway vehicle, the methodology uses the impulse excitations of a single car by means of the wedge method. In the case of the bridge spans, free responses are collected after the passages of trains. The global modal parameters (frequencies and modal damping) of both structures are identified using two modal identification techniques, i.e., the eigensystem realization algorithm (ERA) and the peak picking method (PP). A simplified single-suspension model of the vehicle with 11 global dof’s is proposed that can be useful in the bridge-vehicle interaction analysis. Two steel spans having non-ballasted tracks are the bridge structures. Field tests are conducted to identify the modal parameters and validate the numerical models. Finally, numerical simulations of the train passing over the bridges are compared with the in situ measurements performed under operating conditions.

Police patrol is a complex process. While on patrol, police officers must balance many intersecting responsibilities. Most notably, police must proactively patrol and prevent offenders from committing crimes but must also reactively respond to real-time incidents. Efficient patrol strategies are crucial to manage scarce police resources and minimize emergency response times. The objective of this review paper is to discuss solution methods that can be used to solve the so-called police patrol routing problem (PPRP). The starting point of the review is the existing literature on the dynamic vehicle routing problem (DVRP). A keyword search resulted in 30 articles that focus on the DVRP with a link to police. Although the articles refer to policing, there is no specific focus on the PPRP; hence, there is a knowledge gap. A diversity of approaches is put forward ranging from more convenient solution methods such as a (hybrid) Genetic Algorithm (GA), linear programming and routing policies, to more complex Markov Decision Processes and Online Stochastic Combinatorial Optimization. Given the objectives, characteristics, advantages and limitations, the (hybrid) GA, routing policies and local search seem the most valuable solution methods for solving the PPRP.

This paper investigates the dynamic version of the vehicle routing problem (DVRP), where new demands that arrive during the traveling horizon are considered and treated. When the environment changes (new demands are revealed), the solutions are to be adapted to take into consideration the new demands, while respecting the system constraints. To deal with this problem, an new Evolutionary approach combining Genetic Algorithm (GA) and a Local Search (LS) (EGALS) is proposed. The key idea of the proposed approach is to concurrently apply GA and LS to better manage the exploration-exploitation trade-off and enhance the obtained solutions. In order to assess its performance, we run the proposed approach on Solomon’s benchmark and compare the obtained results against well-performing approaches from the literature, and based on several performance measures. Our experimental results showed that EGALS outperforms the existing approaches in most cases and performs closely to the rest of algorithms with the remaining instances. This confirms that the proposed approach is promising and is competitive compared with other state-of-the-art algorithms.

This paper reports a preliminary feasibility study for combined control and navigation in a loop utilizing a nonlinear second-order dynamic vehicle process model in the cooperative-navigation framework of underwater vehicles equipped with an acoustic modem, attitude, and depth sensors, but lacking a Doppler velocity log (DVL), and a surface vehicle equipped with an acoustic modem and GPS. The case of underwater vehicle navigation without a DVL is of interest in several use-cases, including (a) small and low cost underwater vehicles for which DVLs may be impractical or infeasible due to their size and cost and (b) for missions in which the vehicle’s altitude above the sea floor (or depth beneath overhead ice) exceeds the DVL acoustic bottom-lock range. To the best of our knowledge, no previous study has examined the combined control and cooperative navigation of low-cost underwater vehicles without a DVL utilizing a dynamic model of the submerged vehicles motion in the cooperative navigation algorithm. The anecdotal simulation results presented herein suggest that it may be feasible to do combined control and navigation utilizing a dynamic process model without a DVL in cooperative navigation.

How to detect the prestress loss of the bridge in a fast and economical way is still a challenging problem for bridge engineers. Although some sensors have been developed to monitor the pre...

The paper analyses the interaction between the type and technical condition of road surfaces, dynamic vehicle loads, and the level of vibration propagated to the environment. Measurements of vibrations have been carried out at eight different locations. The dynamic load from vehicles was analysed for cars and delivery trucks passing in local traffic. As a result of conducted measurements and comparative analyses it has been determined to what extent the type of road surface and the technical condition and varied dynamic vehicle loads are affecting the level of vibration propagated to the environment.

Rail seat deterioration (RSD) of concrete ties is manifested by the loss of concrete material in the rail seat area supporting the rail. This failure mode can lead to track that performs poorly and, in extreme cases, can result in the loss of rail clip hold down, reverse rail cant, and rail rollover derailments. This paper describes the use of a multibody vehicle–track dynamics model developed to study the load environment of concrete tie rail seats, specifically addressing the failure mode of RSD. Vehicle–track interaction simulations were conducted to determine the effect of track geometry perturbations on the overall load environment. Various types and magnitudes of track geometry perturbations, including combinations of surface (vertical) and alignment (lateral) perturbations were considered. Fastening system parameters such as clip hold-down force, tie pad stiffness, and broken insulator conditions were also considered. Results of these simulations suggest that concrete crushing, a hypothesized mechanism of RSD, is unlikely in realistic revenue service conditions. Under the load environments considered, the results augment support for an abrasion-related mechanism of RSD that may be more dependent on tonnage and infiltration of fine particles in the rail seat, two factors not addressed in this model. Results from in-track testing are also presented to compare model outputs with measured in-track forces under artificial track geometry perturbations installed at the Transportation Technology Center’s Facility for Accelerated Service Testing. More broadly, the use of this model to explore the effects of vehicle track interaction on tie and fastener load environment is also discussed.

Vehicle vibration calculations play significant and extremely important role, and is based mainly help to assess the stability, vertical dynamic safe, smooth during vehicle’s operation. Full car vibration simulation model (3D) is used to conduct research. The required parameters are determined on the available SYM T880 car. Calculation results are analyzed in both time and frequency domain, helping more comprehensive assessment of vertical dynamic characteristics of T880 truck in particular as well as the basis of reference to conduct model, vibration evaluation of other kind of vehicles, contribute to improving the quality of vehicle design is more comfortable and safer.

Previous research has shown that vehicle en-route diversion can improve the efficiency of dynamic vehicle routing processes. However, an uncontrolled utilization of en-route diversions may increase demands on drivers and cause distraction. This is likely to result in more accidents or reduced productivity which generates additional costs. Since the benefits to the solution quality make a prohibition of en-route diversions unattractive, we propose a general penalty cost based approach for controlling diversions. In contrast to known approaches that allow all diversions, the proposed approach also considers negative application-dependent consequences of diversions on drivers. The approach limits diversions to those which improve the solution quality above a customizable and application-dependent threshold that estimates their negative consequences. We evaluate the proposed general approach by applying it on an exemplary basis to recent deterministic and pro-active real-time routing approaches. Computational experiments show the impact of different penalty cost values on the resulting number of diversions as well as on the attained solution quality. Based on these results, we derive reasonable application-dependent penalty cost values for considering both the contradicting aims of quick request delivery and reducing diversions to a desired extent.

Well-designed wheel-rail profiles are not only helpful in achieving expected dynamic vehicle performance but also in extending the service lives of wheels and rails. In this paper, a method for designing wheel-rail profiles is presented based on the rolling radius difference. This method consists of three parts, i.e., the reverse designs of wheel profiles, symmetric rail profiles and non-symmetric rail profiles. A reverse design method for wheel-rail profiles that can obtain smooth profile formed by quadratic curves is established according to the mapping relation between the rolling radius difference and the wheel-rail profile gradient. This reverse design method is verified and an example for optimizing the design of wheel profiles is introduced. Results show that the design method is effective and efficient. The static/dynamic indexes of the optimized wheel profiles matched with CHN60 can be greatly improved. According to the comparative analysis of wheel-rail contact and dynamic performance, when the lateral displacement reaches 6 mm, the maximum contact stress will be distributed evenly and can be decreased by 184.4 MPa compared to that of existing profiles, while the critical speed can be increased by 10.8% and the running stability can be improved by around 7%. It can be seen that this method is useful for the design of new wheel-rail profiles and optimization of existing wheel-rail profiles.

With the rapid development of the self-determination navigation system in many countries, multi-band multi-mode GNSS integrated positioning has become the current research hotspot, which can overcome the limitations that the navigation based on single satellite system would be not continuous and reliable while GNSS signal is sheltered seriously. According to the development status of GNSS navigation positioning system in China in recent years, the paper intended to study on the performance of combined BDS/GPS-RTK with the application of products of iGMAS. The result of static experiment showed that the positioning accuracy of single GPS was better than single BDS and combined BDS/GPS in open area, combined BDS/GPS was better than single BDS and single GPS in enclosed area. The result of dynamic vehicle experiment showed that combined BDS/GPS could still provide continuous and stable positioning service although the positioning reliability was greatly affected when the observation environment was bad. The result of antenna movement experiment showed that the positioning accuracy of single GPS and combined BDS/GPS was almost the same in either vertical or horizontal direction in open area and single GPS was better than combined BDS/GPS in enclosed area.

Drivers use torque feedback at the handwheel of a vehicle, or steering feel, to obtain information about the road and tire dynamics. This aids them in driving tasks like curve negotiation. Steer-by-wire vehicles, due to the mechanical decoupling of the front tires and handwheel, do not have any inherent steering feedback and require an artificial steering feel. One way to implement an artificial steering feel is to synthesize steering feedback with a model running on board the vehicle. Identifying the appropriate level of model fidelity required involves understanding what elements of steering feel are important. This paper proposes using objective steering feel measures used in industry as a means of understanding which elements of steering feel are most important. It also introduces a steering feel model of appropriate fidelity to capture these important elements of steering feel while remaining intuitive to tune objectively with a small set of parameters. Experimental data show that the desired performance measures obtained via dynamic vehicle simulation can be replicated on an actual steer-by-wire vehicle, validating the design technique.

The measurement of the difference between the left wheelbase and the right wheelbase is the most important part of vehicle detection. A large difference between the left wheelbase and the right wheelbase may lead to a serious traffic accident. This paper develops a new method for dynamic detection, which is based on binocular stereo vision and is a non-contact method that can reduce the equipment failure rate. A real vehicle experiment is performed to verify the proposed method. The manual measurement method and the photosensitive detection method are applied for comparison. The experimental results demonstrate that the proposed method is more stable than the manual measurement method and the photosensitive detection method, and the proposed method can also be extended to other vehicles. Thus, the proposed method is useful for vehicle detection.

A vehicle longitudinal dynamics model, its inverse model and a following model are established; and then two control applications namely gain scheduling Linear Quadratic (LQ) control and Model Predictive (MP) control are designed for adaptive cruise control (ACC) system; finally an integrated Simulink model including the nonlinear dynamic vehicle model and the ACC controller (either LQ or MP) was used to test the controllers in various traffic scenarios. Comparison results between the two controllers applications is provided to show the validity of the design.

The perishability of fresh agricultural products and real-time traffic information greatly reduce the customers’ satisfaction with fresh products distribution. In this paper, the vehicle distribution model for fresh agricultural products was established to maximize customers’ satisfaction with delivery time and freshness based on real-time traffic information. Genetic algorithm was adapted to get initial routes and dynamic adjusted routes. The results show that customers’ satisfaction can be improved and effect of dynamic traffic can be weakened by rational initial routing optimization and dynamic adjustment.

We studied dynamic vehicle routing problem with some requests to be acknowledged during the execution of transportation plan. We divided the time span into several slices and perform re-optimization with updated data at the beginning of each slice. To predict the arrivals of dynamic customers, we sampled number of scenarios. Each scenario is solved by the novel algorithm named selective service with limited resource (SSLR). Service level is ensured by maximizing the number of served customers and giving in-time response. Simulation results show the effectiveness of our proposed method.

The era of autonomous car is yet to evolve, as the job of planning navigation path in dynamically changing environment has become a challenging task for researchers. One of the fundamental dynamically changing parameter is traffic. In this paper, we have proposed dynamic vehicle traffic routing algorithm to facilitate the robotic car to find the appropriate route from a particular source location to reach the destination. Moreover, we have demonstrated this algorithm by applying different constraints like lookahead condition and previously acquired values as heuristic. Illustrations of these variants of algorithm are analyzed, based on the real data of a city. In addition to it, we have described how providing a cloud service can enhance the computation speed of enormous and continuously changing traffic data, thereby meeting storage requirements. OpenStack is used as a software platform to provide this service to the large-scale local network.

Path planning for autonomous vehicles is a challenging computer vision problem. In this work, we propose an algorithm to generate dynamically a smooth path for trajectory guidance of an autonomous vehicle. For this, we use B-spline curves and the perspective-distorted images obtained from an onboard camera. The theoretical principles of the algorithm are presented in detail. Preliminary results obtained with an experimental prototype are shown.

Vehicle vibration is an important measurement item in catenary inspection on high-speed railways. However, it is a difficult task for the accurate measurement of vehicle vibration, due to the complicated dynamic vibration of trains relative to tracks on different inspection conditions. In this paper, the dynamic vehicle vibration and measurement model are analyzed in detail, and a measurement system is proposed based on the analysis results. The expected measurement accuracy is finally verified in experimental test.

This study evaluated the influence of roughness-induced dynamic truck axle loading on the variation in pavement responses. Measured dynamic tire load data at 40, 60, and 80 km/h (24.9, 37.3, and 49.7 mph) for air and rubber truck suspensions from five sites (smooth to severely rough) were investigated. A total of 840 individual 3D-Move analyses were conducted to estimate responses of two different pavement structures under a moving dual tire tandem axle at multiple locations within pavement structures. A new parameter called Dynamic Response Coefficient (DRC) was introduced to represent the variation in pavement responses due to the variation in dynamic truck axle loading. DRC is the coefficient of variation for a specific response at a specific point within the pavement structure. The results showed that DRC differs from the Dynamic Load Coefficient (DLC) and is a function of location within pavement, pavement structure and temperature, suspension type, vehicle speed, and road roughness.

The Vehicle Routing Problem (VRP) is a classical combinatorial optimization problem. It is usually modelled in a static fashion; however, in practice, new requests by customers arrive after the initial workday plan is in progress. In this case, routes must be replanned dynamically. This paper investigates the Dynamic Vehicle Routing Problem with Time Windows (DVRPTW) in which customers’ requests either can be known at the beginning of working day or occur dynamically over time. We propose a hybrid heuristic algorithm that combines the harmony search (HS) algorithm and the Variable Neighbourhood Descent (VND) algorithm. It uses the HS to provide global exploration capabilities and uses the VND for its local search capability. In order to prevent premature convergence of the solution, we evaluate the population diversity by using entropy. Computational results on the Lackner benchmark problems show that the proposed algorithm is competitive with the best existing algorithms from the literature.