Vehicle Travel Time Research Articles

Assigning customer-dependent travel time limits to routes in a cold-chain inventory routing problem

This study is activated by a real-world case of cold chain distribution in the Yangtze River Delta of China. Due to the uneven spatial distribution of customers, the customers close to the depot are distributed by self-owned vehicles (SOVs) with a short route time limit while the far customers are distributed by outsourced vehicles (OSVs) with a long route time limit. Although the divide-and-conquer heuristic procedure is practically used in the examined case, it fails to continuously optimize the solutions in timely manners. The examined cold chain distribution problem is an extension of inventory routing problems (IRPs) while the combination of SOVs and OSVs with different route time limits makes the present solution methods inapplicable. Compared with IRPs, the transportation cost and fuel cost of vehicle cold storage are considered simultaneously; the vehicle travel time limits are assigned depending on the distances from the depot to the visited customers. A formal mixed-integer linear program (MILP) and a descriptive model are developed. Considering the case and its dataset cannot be solved by a MILP solver, a genetic algorithm is developed for exploring good solutions using the descriptive model. The algorithmic tuning and operational parameters are investigated by demonstrative and sensitivity analyzing experiments. The examined case is general in cold chain distribution. The solution method can be extended to scheduling heterogeneous fleets for uneven spatially distributed customers.

Population-based simulation optimization for urban mass rapid transit networks

In this paper, we present a simulation-based headway optimization for urban mass rapid transit networks. The underlying discrete event simulation model contains several stochastic elements, including time-dependent demand and turning maneuver times as well as direction-dependent vehicle travel and passenger transfer times. Passenger creation is a Poisson process that uses hourly origin–destination-matrices based on anonymous mobile phone and infrared count data. The numbers of passengers on platforms and within vehicles are subject to capacity restrictions. As a microscopic element, passenger distribution along platforms and within vehicles is considered. The bi-objective problem, involving cost reduction and service level improvement, is transformed into a single-objective optimization problem by normalization and scalarization. Population-based evolutionary algorithms and different solution encoding variants are applied. Computational experience is gained from test instances based on real-world data (i.e., the Viennese subway network). A covariance matrix adaptation evolution strategy performs best in most cases, and a newly developed encoding helps accelerate the optimization process by producing better short-term results.

Simulation study of vehicle travel time on route with signals considering comprehensive influencing factors

Vehicle travel time is widely regarded as an important performance of the road traffic as well as a significant decision factors for travelers. While the travel time is variable because of the stochastic factors such as traffic flow, signals, and some other emergency conditions. Considering the dynamic characteristics of road traffic flow and the importance of shortening travel time for emergency transport task, in this paper, a basic vehicle travel time model based on empirical velocity–density function is established, in which the travel time is divided into road running time and signal waiting time. Simulations based on the basic model are conducted to investigate the comprehensive effect of the multiple factors on the travel time, such as traffic density, number of signals, circle time, green ratio and offset time between adjacent signals. A green-wave traffic objective-oriented method is also explored to achieve the shortest travel time. The results demonstrate that plateaus and sloped plateaus would appear under the comprehensive influence of both traffic density and traffic light number or signal parameters. It is found there is a minimum traffic time with a certain offset time under different traffic density when the traffic lights on a route do not change synchronously. The fitting formula and theoretical formula for the optimal offset time are also proposed, which can be used to achieve green-wave traffic in a practical case.

PENGEMBANGAN MODEL SIMULASI SISTEM DINAMIK UNTUK MENINGKATKAN EFISIENSI SISTEM OPERASIONAL TRANSPORTASI

If transport continues to increase, plus manufacturers competing to produce interesting transportation on the market, thus allowing the improvement of the transport users. If the increase occurs, it will cause congestion. Congestion was a factor that greatly affect the efficiency of the transport system, where the transportation system is a form of attachment and the interconnected between the passenger, shuttles and infrastructure that interact in order to transfer people or goods, which is covered in an order, either by natural or artificial or engineered. It takes the right planning strategies in addressing conditions congestion such as implementation of reconfiguration of the route network, a program that using dynamical systems in proper design and planning, and the determination of the most appropriate scenario can improve the efficiency of the transportation system. This research uses scenario through reconfiguration of network routes to improve the efficiency of the transportation system. in this study, this scenario is considered to be the most appropriate to increase the efficiency of vehicle travel time by way of the transfer of light vehicle routes that will go towards the Urip Sumoharjo street because it results in a reduction in travel time by 1.2% of travel time before the scenario.

A Framework to Operationalize a Deep and Vast Literature for Practice: Translating Land Value Uplift Literature to Estimate Economic Impacts of Multimodal Transportation System Projects

Traditional methods for evaluating transportation system investments typically rely heavily on one or two metrics of evaluations, such as vehicle travel time delay and level-of-service measures. Transportation projects often have substantial and significant impacts on many other aspects of society, including the economic vitality of our communities. The focus of this study was a practical one: operationalize a vast literature exploring the theories and findings that describe positive and negative economic impacts of transportation investments, in this case focused on the impacts on real estate value. It was completed with sponsorship from Smart Growth America to develop a pilot application for Washington DOT. The framework described in this manuscript allows analysts to estimate and compare changes in real estate value, and therefore changes in economic vitality, resulting from different investment decisions. The economic impacts estimated in change in U.S. dollar value of single-family residential, multifamily residential, and commercial real estate can be used in combination with other performance measures (e.g., travel time savings, environmental impacts) to evaluate a more comprehensive picture of the impacts of transportation infrastructure. Because this framework was spatially developed, the analyst will be able to more readily identify which neighborhoods and corresponding populations may see the largest impacts on the cost of housing resulting from specific transportation projects. This, in combination with housing expertise and tools developed to understand the displacement of vulnerable populations, could also help agencies anticipate where there would be increased pressure in relation to cost of housing caused by specific transportation projects.

Adaptive Rolling Smoothing With Heterogeneous Data for Traffic State Estimation and Prediction

Spatial–temporal traffic state estimation and the prediction of urban expressways is a vital component of traffic management and information systems. The adaptive smoothing method is one of the most frequently used approaches to estimate traffic states. However, the fixed filter parameters used in existing approaches sometimes fail to characterize traffic dynamics well. To better capture generation, propagation, and mitigation dynamics of traffic congestion, we propose an adaptive rolling smoothing (ARS) approach by dynamically tuning the filter parameters in a rolling horizon scheme for online applications. The fusion of heterogeneous traffic data combines aggregate traffic measurements (e.g., traffic flow rate, time occupancy, and speed collected by remote microwave sensors) and disaggregate information (e.g., timestamps of individual vehicles detected by license plate recognition cameras). A nonlinear traffic flow filter based on the virtual trajectory algorithm is established to reconstruct the spatial–temporal traffic state and estimate experienced travel times of individual vehicles. The results demonstrate the capability and effectiveness of the proposed ARS approach in the historical traffic state estimation and short-term traffic flow prediction. Complicated traffic states of weaving, merging, and diverging segments can be well distinguished by reconstructing time-space speed diagrams. The proposed approach can be extended to develop efficient missing data imputation algorithms and hierarchical control strategies for heterogeneously congested urban expressways.

A simulation system and speed guidance algorithms for intersection traffic control using connected vehicle technology

In the connected vehicle environment, real-time vehicle-state data can be obtained through vehicle-to-infrastructure communication, and the prediction accuracy of urban traffic conditions can significantly increase. This study uses the C++/Qt programming language and framework to build a simulation platform. A two-way six-lane intersection is set up on the simulation platform. In addition, two speed guidance algorithms based on optimizing the travel time of a single vehicle or multiple vehicles are proposed. The goal of optimization is to minimize the travel time, with common indicators such as average delay of vehicles, average number of stops, and average stop time chosen as indexes of traffic efficiency. When the traffic flow is not saturated, compared with the case of no speed guidance, single-vehicle speed guidance can improve the traffic efficiency by 20%, whereas multi-vehicle speed guidance can improve the traffic efficiency by 50%. When the traffic flow is saturated, the speed guidance algorithms show outstanding performance. The effect of speed guidance gradually enhances with increasing penetration rate, and the most obvious gains are obtained when the penetration rate increases from 10% to 40%. Thus, this study has shown that speed guidance in the connected vehicle environment can significantly improve the traffic efficiency of intersections, and the multi-vehicle speed guidance strategy is more effective than the single-vehicle speed guidance strategy.

Coupling National Performance Management Research Data Set and the Highway Performance Monitoring System Datasets on a Geospatial Level

Integration of various datasets is crucial given the emphasis placed on holistic reporting of performance measures of various variables related to road transportation by the Moving Ahead for Progress in the 21st Century (MAP-21) Act. None is more confounding than the merger of geospatial datasets, which is necessary, for example, to combine vehicle travel time and volume information for road segments. Such a merged dataset is released through the National Performance Management Research Dataset (NPMRDS). The NPMRDS is supposed to exclusively cover the National Highway System (NHS) and Strategic Highway Network (STRAHNET) sub-selected from the Highway Performance Monitoring System (HPMS). However, one finds that the coverage is not perfect. There are not only many extra road segments included in the NPMRDS, but also some NHS/STRAHNET roads segments are not fully covered by corresponding NPMRDS segments. Further, one finds very little literature about the method Texas Transportation Institute uses to orchestrate the conflation. Therefore, it was endeavored to create a conflation algorithm which might perform better. The benchmark for the proposed algorithm is the identification of the segments wrongly conflated during the creation of the NPMRDS geospatial dataset. The proposed methodology uses a combination of five measures of similarity between the HPMS and NPMRDS segments. The proposed method successfully identifies significant numbers of mismatched segments: about 5% excess NPMRDS segments, and about 3% HPMS segments without NPMRDS counterpart.

Simulation of the Bluetooth Inquiry Process for Application in Transportation Engineering

In recent years, Bluetooth technology has been adapted for use as a sensor for measuring vehicle travel times along a segment of roadway. However, using the Bluetooth technology in advanced traffic management systems has been limited in part, because there is a lack of tools, such as simulation, to predict the behavior of the system before it is developed and deployed. A number of studies have been published describing the Bluetooth technology, inquiry, and pairing process. Most of these studies have focused on the simulation of the first successful inquiry and reduction of the pairing time. However, in many traffic sensing applications, Bluetooth detectors are designed to stay in the inquiry stage and will continuously perform inquiry scans. These detectors will not proceed to the paring stage and multiple inquiry scans may occur on each device during the time these devices remain in the detection zone of the detector. In this paper, we propose a simulation framework that considers multiple inquiry scans and the effect of distance from the detector on the inquiry process. The simulation model was calibrated and validated using the field data collected from two custom-built Bluetooth detectors. The simulation framework has been made into a simulation software tool entitled blue synthesizer, which can be combined with commercially available trafficion microsimulation models to evaluate the use of Bluetooth technology within advanced traffic management systems.

Evaluation of the Use of a City Center through the Use of Bluetooth Sensors Network

In order to achieve the objectives of Smart Cities, public administrations need to take measures to regulate mobility, which undoubtedly requires a high level of information and sensorization. Until the implementation of the connected vehicle takes place, it is still necessary to install sensors to obtain information about mobility. Bluetooth sensors are becoming a useful tool due to the low cost of equipment and installation. The use of Bluetooth sensors in cities, with short distances between sensors, makes it necessary to propose new classification algorithms that allow the trips of pedestrians and vehicles to be differentiated. This article presents the study carried out in the city of Valencia to determine the use of motor vehicles in the historic center and propose a new classification algorithm to distinguish between an onboard Bluetooth device and the same device carried by a pedestrian when it is not possible to use the travel time for the classification due to the short distance between sensors. This causes very similar or even indistinguishable travel times for vehicles and for pedestrians. We also propose an algorithm that allows vehicles to be classified according to what type of trip is made always through the historical center of Valencia, whether it is to make a shorter itinerary through the city or to access the center for any type of business. This algorithm would enable the Origin-Destination matrix of an urban network with short distances between sensors if they are available in all entries and exits. Likewise, the results obtained have allowed to positively evaluate the algorithm defined to distinguish between trips made by a pedestrian or a vehicle in a city, using the MAC address of their mobile devices with very short distances among sensors. The results of this study show that it is possible to use Bluetooth technology, with low cost installations, to evaluate the use of the city by motor vehicles.

The vehicle routing and scheduling problem with cross-docking for perishable products under uncertainty: Two robust bi-objective models

• Extending the applicability of cross-dock to distribute the perishable products. • A bi-objective model for VRPCD which minimizes the cost and maximizes the freshness. • The model reduces the temporary storage of items with a high deterioration rate. • Two robust models, considering the uncertainty of travel time and freshness-life. • The effect of uncertainty in travel time is higher than that of the freshness-life. This paper presents a bi-objective MILP model for the vehicle routing and scheduling problem with cross-docking for perishable products. It is demonstrated that considering merely one objective sacrifices the other one and that the L 1 metric method makes a suitable trade-off. Two robust models are developed when the travel time of the outbound vehicles and the freshness-life of the products are uncertain. The results show that the effect of the appearing uncertainty in the travel time on the deterioration of the objectives is higher than the effect of the freshness-life of the products, and using the proposed model, the freshness of the delivered products increases by 74.14% on average without increasing the distribution cost, which can decrease the waste.

An optimum route analysis of fire rescue according to fire station location (Case study: Residence area in Makassar’s central business district)

Fire is a common problem in the last three years in Makassar. Operational Staff of Fire Department Makassar record (January-April) 32 cases of fire disaster in 2015, 44 cases in 2016, and 35 cases in 2017, even on 2018 recently occurs on April and May. The fire disaster is likely to attack in city residences area, in which it is very important especially for fire disaster mitigation. The fire rescue is needed effective route considering the travel time and distance to reach the location of the fire. Determine the route with optimum options will be helpfully the fire rescue to reduce the risk and prevent the situation from getting worse. This research has an objective to give information of optimum route that will use by the fire rescue. The optimum route according to the fire station location using Quantum Geographic Information System (QGIS). The QGIS has required the topology, length, target that finally give the shortest route. The travel time of vehicle also required to the condition of the traffic. Finally, the result of the research shows the optimum route of the fire station rescue to the residence area in the central business district in Makassar.

Research on Evaluation and Prediction Method of Link Travel Time Based on Floating Car Data by Simulation

Using the floating car data obtained by simulation to carry out theoretical research on link travel time evaluation and prediction, it has the advantage of conveniently setting different situations and providing reference for practical applications. In this paper, we have acquired the floating car data based on microscopic simulation, and then the complex trapezoidal quadrature formula is used to obtain link travel time of a single vehicle. When setting different ratios of floating cars, the average link travel time is obtained by the mean-median method. The results show that the effect is better than the arithmetic average method, and the higher the ratio of floating cars, the higher the accuracy of evaluation. The markov model has been used to correct the gray prediction model, with that we establish travel time prediction model based on the grey markov chain. The experimental results show that the prediction accuracy is high.

A model for taxi pooling with stochastic vehicle travel times

Taxi pooling means the sharing of a taxi by more than one passenger with at least a semi-common route. Currently, a trial-and-error process is adopted, taking into account expected travel times, for taxi pooling, a method which is neither effective nor efficient. This is because stochastic disturbances arising from variations in the taxi travel times that occur in actual traveling are neglected. In the worst case scenario, where vehicle travel times fluctuate wildly during operations, the planned schedule can be disturbed enough to lose its optimality. Therefore, in this study, a network flow technique is used to construct a stochastic taxi pooling model incorporating stochastic vehicle travel times. A solution algorithm is also proposed to efficiently solve the problem. The performance of the proposed models and the use of the solution method in practice are evaluated by executing numerical tests using real data with suitable assumptions. The test results show that the stochastic model and the solution method could be useful references for practice.

Development of Benefit Cost Analysis Tools for Evaluating Transportation Research Projects

Transportation research projects are a vital element for transportation agencies to accumulate new technology and knowledge to improve the efficiency and safety of transportation infrastructure. The purpose of this paper is to develop benefit cost analysis (BCA) tools to assist transportation agencies in evaluating transportation research projects. The BCA tools provide analysis methods for estimating the benefits for changes in the level of service (LOS) of a roadway, reductions in the vehicle travel time, changes in vehicle operating costs and reductions in the number of crashes. Three case studies were investigated to illustrate the usage of the BCA tools. The first case study evaluated the effectiveness of variable speed limit systems implemented along I-80 in southern Wyoming. The BCA tools estimated a benefit cost ratio of 6.64 indicating that the implementation of the project was economically justifiable. The second case study was a recent study investigating and developing mitigation strategies for the effects of truck traffic along the I-80 in southern Wyoming resulting in a benefit cost ratio of a 9.23 indicating that the project had the potential to be economically viable upon implementation. The final case study evaluated the effect of wildlife overpass and underpass crossings on the migrations of pronghorn and mule deer. The benefit cost ratio for the research project was 0.42 indicating that the project was not economically beneficial after the first year of implementation. The case studies indicated that the BCA tools are a beneficial tool for quantifying the economic benefits of a transportation research project.

A Novel Approach for Online Car-Hailing Monitoring Using Spatiotemporal Big Data

Car-hailing service has increasingly become popular and fundamentally changed the way people travel in the era of sharing economy. Although such service brings convenience to people's lives, it also causes safety and property concerns. Many studies have been conducted to access the efficiency and effectiveness of car-hailing, but little has been done on its safety monitoring. However, with the rapid development of information technologies such as Internet of Things (IoT), Geographical Information Science (GIS) and automatic monitoring, a more advantageous approach than the current simple drivers screening and testing is feasible. A new model including five indexes i.e. region dangerous index, offset distance of the origin-destination, real-time speed under traffic conditions, vehicle travel time and passenger information, is therefore proposed in this paper based on big data mining of the historical vehicle GPS trajectory data. Experiments were conducted to validate the model in the Gangzha District of Nantong City, China. Several other types of data were used in the experiments, e.g. points of interest (POI), road network data and urban image. The results showed that the proposed model effectively monitored the vehicle when it was driving in a “potentially dangerous area”. In addition, the model could accurately identify the driver's abnormal driving behaviors, such as bypass and abnormal stop. The prediction accuracy of the experiments was 92.06%, among which the discrimination accuracy of the abnormal stop was 100% and that of the detour was 90.57%. All these validate the applicability of the model for future management systems for car-hailing services.

Queue Length Estimation for Signalized Intersections Using License Plate Recognition Data

Queue length is an important variable in evaluating the performance of traffic management systems, especially under congested conditions. This problem has been studied in the literature based on different kinds of traffic sensors, such as loop detectors and other mobile sensors. Automatic Number Plate Recognition systems and Automatic Vehicle Identification systems have received significant attentions due to their active deployments in recent years, which provides massive License Plate Recognition (LPR) data sources. In this paper, new methods for queue length estimation at signalized intersections are proposed using LPR data and signal schemes, with the key point being the intrinsic connections between travel time of individual vehicles and queue composition in each cycle. The queue length in the previous cycle is calculated by considering the detailed trajectories of individual vehicles. Due to the hysteresis of the queue length in the previous cycle, the queue length in the immediate past cycle is formulated as a prediction problem using regression analysis. The algorithms were evaluated using field data of Guiyang city in China, and the proposed models? results fully coincide with the experimental findings even in congested conditions.

The evaluation of traffic characteristic analyzed by vissim (case study: underpass construction at Metro Pondok Indah Road)

Government of DKI Jakarta build road infrastructure such as fly over and/or underpass to reduce congestion and delay at the main junctions. One of that is underpass construction at Metro Pondok Indah Road. The impact of this project during construction is make the road narrowing (bottleneck) and cause longer travel time of vehicle and decreased average speed. This research tries to simulate this situation using Vissim as a modeling traffic tool and then compared with actual conditions. Some calibrations of driving behavior parameters have been done using GEH formula to adjust the parameter to the acceptance level at value less than 5.0, so it can conclude that simulation using Vissim can represent actual condition during traffic congestion and normal condition especially in Jakarta traffic. These adjusted parameters may represent the actual traffic condition in Jakarta.

CAPACITY PLANNING OF URBAN ROADS IN CONDITION OF PASSENGERS’ TRAVEL MODE CHOICE

Introduction.The authors conduct the research of the urban passenger transportation problem. Municipal authorities and passengers are regarded as participants of the passenger transportation system. Moreover, the municipal authorities have to optimize road width and public transport frequency. The road consists of a bus lane and lanes for personal vehicles. The vehicle travel time depends on the number of road lanes and passengers’ choice of the travel mode. The passengers’ goal is to minimize total travel costs, including time value. Therefore, the passengers try to find the optimal ratio between public transport and cars.Materials and methods.The mathematical model for choosing the mode of transportation is based on the exponential distribution of the passenger cost. Time of movement on personal transport is described by the BPR model. The conflict between municipal authorities and the passengers is described as a theoretic model.Results.The existence of Nash equilibrium in the model is proved. In addition, the numerical example shows the influence of time value and intensity of passenger flow on the equilibrium of the road width and of public transport frequency.Discussion and conclusions.The presented model allows optimizing the capacity of the road network in conditions of allocated lanes for public transport and the choice of transportation for passengers. Further research would be aimed at managing the number of parking spaces.The task is also to generalize the model of the urban passenger transport network, directions and intersections, which describe the real city roads.

Analysis of railway connections and public transport on selected Szczecin routes

The purpose of the conducted research was to assess railway connections and public transport in the context of the choice of means of transport. The research consisted in examining the actual travel time of regional passenger trains and public transport vehicles and determining the number of passengers in public transport vehicles under conditions of actual operation. The conducted research may be one of the factors confirming the possibility of using the existing infrastructure and the railway connection network in Szczecin.