Vehicle Travel Speed Research Articles

Standardizing Vehicle Travel Speed Data for Road Safety

ABSTRACTIn 2022, almost 50,000 people died in road crashes in the United States, with speeding implicated in 29% of these fatalities. Despite known links between vehicle speed and crash occurrence and severity, there are no federal guidelines for collecting vehicle travel speed (VTS) data. Cities with open VTS data are using unstandardized datasets, which complicates large‐scale and cross‐jurisdictional analysis. We conducted a qualitative assessment of open data repositories for the 25 largest U.S. cities, using a framework of knowledge representation, evaluated twelve metadata components, and determined the potential usability of these datasets. Our knowledge representation framework includes five data elements: speed metric, timestamp, geospatial representation, posted speed and vehicle type. Findings show that one‐quarter of these cities have open VTS datasets. Of those cities, none has a VTS dataset containing all the elements defined in our framework. This suggests the need to design information policy standards for the collection and sharing of open VTS data.

Levelized cost of long-distance large-scale transportation of hydrogen in China

Hydrogen plays a crucial role in supporting the transition to clean energy systems, and effective hydrogen transportation technologies are essential for the development of the hydrogen economy. However, long-distance, large-scale hydrogen transportation costs in China, particularly for liquid hydrogen trucks (LH2 tank trucks) and gaseous hydrogen pipelines (GH2 pipelines), remain unknown. Using the latest data from the ongoing hydrogen project in China and a techno-economic model, this study estimates the delivery costs of hydrogen over long distances for LH2 tank trucks and GH2 pipelines, and compares them with those of GH2 trucks. Specifically, we analyze the levelized cost of hydrogen transportation (LCOT) for these different technologies at varying distances and conduct sensitivity analyses on how these LCOT would change with factors such as vehicle travel speed, electricity prices, and pipeline capacity. Results show that for short distances (<150 km), GH2 trucks are most cost-effective, with costs around 28.96–34.26 CNY/ton-km. For long distances (>200 km), GH2 pipelines and LH2 tank trucks are more suitable, with pipelines being more cost-effective at higher capacity utilization rates. Lower electricity prices further reduce the LCOT for LH2 tank trucks. Policy recommendations on promoting the development and application of hydrogen transportation technologies are also provided.

Multi-objective arterial coordination control method based on induction control and vehicle speed guidance

The fixed green wave speed and staged statistical flow used in arterial signal coordination are not adaptable to the fluctuations in vehicle travel speed and traffic flow on roads, resulting in a mismatch between the signal scheme and the optimal green wave speed and traffic flow demand. This discrepancy negatively impacts the efficiency of intersection traffic. In traditional signal control systems, the cycle and green light timing are typically set independently. However, such a setting method poses problems in practical operation. In this paper, we combine vehicle arrival and vehicle location information, and consider the interaction of speed guidance and dynamic signal optimization to construct a model. This study is developed along the following steps: in the vehicle-road coordination environment, based on the MAXBAND model, a global coordination scheme is obtained, incorporating the speed guidance method; then, based on the vehicle saturation of the inlet lane of the arterial intersection, a multi-objective optimization model for arterial signal coordination under vehicle speed guidance is established based on global coordination with the maximum green wave bandwidth and the minimum delay of arterial vehicles, the minimum number of arterial stops and the minimum delay in the minor direction road as the optimization objectives. Based on global coordination, adopting an integrated control mechanism of cycle and green light timing allows for dynamic adjustments according to real-time traffic conditions. The improved multi-objective particle swarm algorithm is chosen to solve the model, and the simulation environment is built based on the COM interface of VISSIM software and C# platform. Three adjacent intersections of Ganjiang Middle Road in Nanchang are selected as case studies, and the methods in this paper are compared with the current timing scheme, the MAXBAND method and the optimization scheme under speed guidance only, respectively. The results show that the model proposed in this paper achieves significant optimization effects on the indicators of arterial delay, arterial stopping times and the delay of minor roads.

Impact of real-time weather conditions on crash injury severity in Kentucky using the correlated random parameters logit model with heterogeneity in means

The present study investigated the impact of real-time weather (air temperature, relative humidity, precipitation, wind speed, and solar radiation) on crash injury severity. Recent crash data (January 2016 to April 2021) on Interstate-75 in the state of Kentucky were merged with real-time weather information (retrieved from Kentucky Mesonet stations) at the 1-hour level. The severity index “SI” (i.e., the ratio of percent severe crashes to percent exposure of a specific weather state during the crash period) was introduced to evaluate the impact of different real-time weather states on fatal and severe injury crashes. Furthermore, the standard mixed logit (MXL), correlated mixed logit (CMXL), and correlated mixed logit with heterogeneity in means (CMXLHM) models were fitted and compared to identify the risk factors contributing to crash injury severity while accounting for unobserved heterogeneity. The results showed that the CMXLHM model was statistically superior to the CMXL and MXL models based on various goodness-of-fit measures (e.g., Akaike information criterion “AIC” and McFadden pseudo R-squared). Results from the SI analysis and CMXLHM model showed that real-time weather-related factors (e.g., air temperature ≥ 70 0F and relative humidity ≥ 90 %) were significantly associated with higher severe injury likelihood. Further, driving under the influence (DUI), young drivers, and vehicle travel speed were associated with greater injury severities. On the other hand, presence of horizontal curve, passenger cars, and hourly traffic volume were associated with lower injury severity likelihood. The study outcomes can help in incident management by suggesting specific real-time weather-related states to feed to dynamic message signs (DMS) to enhance travelers’ safety along the interstates.

Hyper-heuristic algorithm for traffic flow-based vehicle routing problem with simultaneous delivery and pickup

Abstract To address the realistic problem of seriously reducing distribution efficiency and increasing distribution cost caused by road traffic congestion, this paper constructs a time-dependent speed describing vehicle travel speed and road traffic flow by simulating the change of urban traffic flow, to establish a vehicle route problem model considering traffic flow with distribution cost and customer satisfaction as optimization objectives. To solve this problem, a hyper-heuristic algorithm based on tabu search is designed in this paper, in which the underlying search operator is selected more efficiently by a high-level heuristic strategy. In addition, the correctness of the model and the effectiveness of the algorithm are verified by conducting simulation experiments on several benchmark sets. Experiment results are shown as the travel speed of the vehicle increases, the average customer satisfaction in lc1-type instances increases to 0.94. And the impact of urban traffic changes on logistics costs and customer satisfaction is further analyzed.

Analysis of dynamic response of three-span bridge using vehicle load data from Road Administration Department IV in Vietnam

In many studies, the dynamic response of bridges is influenced by various factors. Multiple factors, such as vehicle loads, road roughness, vehicle-bridge interactions, and travel speed, impact the dynamics of a three-span bridge on highways. Because the mass of the vehicle, including the cargo, fluctuates randomly, a probabilistic methodology based on the Monte Carlo method is utilized to produce random anomalies for dynamic analysis. To examine the Song Gieng bridge, data from the Road Administration Department IV on heavy vehicle loads and overloaded vehicles are utilized to produce random vehicle loads. The analytical results indicate that there is a discrepancy in the probability distribution rules between the vehicle load (input random variable) and the dynamic impact factor (output random variable). This implies that their mapping connection is not monotone. Compared with the threshold values specified in the bridge design standards of Vietnam and the United States, the dynamic impact factor obtained in this study is significantly different. These findings can provide additional guidance for practicing engineers.

A branch-cut-and-price algorithm for the time-dependent electric vehicle routing problem with time windows

The adoption of electric vehicles (EVs) within last-mile deliveries is considered one of the key transformations towards more sustainable logistics. The inclusion of EVs introduces new operational constraints to the models such as a restricted driving range and the possibility to perform recharges en route. The discharge of the typical batteries is complex and depends on several variables, including the vehicle travel speed, but most of the approaches assume that the energy consumption depends only on the distance traveled. This becomes relevant in different logistics contexts, such as last-mile distrubtion in large cities and mid-haul logistics in retail, where traffic congestion affects severely the travel speeds. In this paper, we introduce a general version of the Time-Dependent Electric Vehicle Routing Problem with Time Windows (TDEVRPTW), which incorporates the time-dependent nature of the transportation network both in terms of travel times and the energy consumption. We propose a unifying framework to integrate other critical variable times arising during the operations previously studied in the literature, such as the time-dependent waiting times and non-linear charging times. We propose a state of the art branch-cut-and-price (BCP) algorithm. Based on extensive computational experiments, we show that the approach is very effective solving instances with up to 100 customers with different time dependent configurations. From a managerial standpoint, our experiments indicate that neglecting the travel speeds can affect the quality of the solutions obtained, where up to 40 percent of the infeasibilities induced by neglecting the time dependency can be caused by exceeding the battery capacity.

Experimental Study of the Correlation between the Wear and the Braking System Efficiency of a Vehicle

The growing number of vehicles leads to increasingly intense and congested traffic, which will additionally put demand on the braking system, and drivers behave more aggressively. As a result, the braking system must be durable and efficient. For this purpose, the study of the braking system behavior in conditions of intense and moderate traffic is required to increase the safety of traffic participants—respectively, to demonstrate the need for more frequent replacement of some braking system elements. Thus, a series of successive tests were performed on a vehicle, through which the degree of wear of the brake pads and discs was monitored periodically, resulting in the efficiency evolution of the braking system. The tests were carried out both in the laboratory (on a dynamometer) and in traffic to establish the efficiency of the braking system according to some parameters considered essential. The experimental tests showed that the recommendations regarding the frequency of replacement of brake pads and discs are inconsistent with their actual wear. Therefore, the aim of this paper is to establish the braking system efficiency of a vehicle, subject to testing depending on the vehicle mass, travel speed, distance driven, and braking time, based on experimental tests, on stand and in-traffic, according to the road safety regulations. The validation of the braking system efficiency of the tested vehicle was done by measuring the stopping distance and time in relation to the initial speed, the mass of the vehicle, the number of kilometers traveled, and conditions of intense and moderate traffic.

Crash Frequency Minimization with Severity Mitigation in Road Geometric Design Using Chance Constraint Programming Optimization

Crash frequency and crash severity are two major aspects of transportation safety. In this paper, we propose a decision-making scheme combining statistical analysis and optimization modeling to be used in transportation safety study. We conduct a safety analysis, a travel speed analysis, and an optimization analysis to develop a two-stage decision scheme to minimize crash frequency while mitigating crash severity, using data collected in urban environments in Lincoln, Nebraska. In the safety analysis and the travel speed analysis, we study the impact of lane width and other related road geometric design parameters on annual crash frequency and vehicle travel speed using count models and linear regression models, respectively. In the optimization analysis, the proposed two-stage stochastic programming model determines the lane width and other road geometric design parameters in the first stage, and then the posted road speed limit in the second stage for each scenario. To mitigate crash severity, we use a chance constraint to restrict a certain percentile of the vehicle travel speed to comply with the posted road speed limit. This two-stage decision scheme is shown to be effective for the data collected in Lincoln, Nebraska, when restricting the vehicle travel speed of up to two positive standard deviations from the mean travel speed to be under the posted speed limit. The application of a stochastic programming model that utilizes regression analysis results serves as an innovative decision scheme that effectively connects statistical analysis and optimization studies in road geometric design for transportation safety. Its objective is to minimize crash frequency while simultaneously mitigating crash severity. This methodology has extensive potential for application in various environments to assist in the reduction of both crash frequency and crash severity.

Perceptions of surveillance: Exploring feelings held by Black community leaders in Boston toward camera enforcement of roadway infractions

Roadway camera enforcement programs have been found to effectively reduce vehicle travel speeds, as well as decrease the number and severity of collisions. Despite a wealth of evaluative research confirming this enforcement approach's aptitude at promoting safer roadway behavior, fewer than 50 % of US states currently host camera-based programs. Public opposition is frequently cited as the cause for the slow proliferation of this enforcement strategy. However, with public demand for police reform having an increasing presence on the national political stage, how might feelings toward camera technology currently stand among groups most marginalized by existing enforcement systems, and how might those feelings vary by type of enforcement application? Through a series of focus groups, this work centers Black voices on matters of surveillance and roadway enforcement by discussing sentiment toward camera programs with Black community leaders. This discussion is contextually situated in Boston, Massachusetts, where legislation that would allow for camera enforcement of roadway infractions is actively being deliberated in the State Senate. Findings culminate in a list of right-sizing and procedural recommendations for policy makers hoping to gain support for camera enforcement, improve roadway safety, and advance racial equity in our systems of policing and governance.

Analisis Kinerja Ruas Jalan (Studi Kasus Jalan Tangkuban Perahu, Denpasar Barat)

Denpasar city is one of the big cities that has a very high population, it can be seen from the population of Denpasar city of 962,900.000 million people, (BPS, 2020). Over time, the traffic density on the road has increased, in addition to the increasing number of residents and the increasing number of private vehicle ownership, it is also caused by the location adjacent to shopping centers and restaurants. This research was conducted using primary data. Primary data was obtained from survey results in the form of traffic survey data,Road Capacity, Degree of Saturation, and Level of Service using the 2014 PKJI method. Based on the results of the discussion, it can be concluded that the performance of the Tangkuban Perahu road is at Level of Service F, which means it is very bad, with the following indicators. The peak hour volume is 2394 cur/hour. Capacity 2381 cur/hour. The side resistance is 98,4, for the side resistance class it is classified as very low, which is 0.96. The degree of saturation (DJ) &gt; 1.00 is 101 cur/hour. The average travel speed of vehicles at a distance of 100m is 21,69 km/hour.

An Integrated Model of Continuous Review Inventory and Vehicle Routing Problem with Time Windows

Item stock-out or shortage is a great issue for customer satisfaction and can be countered by providing safety stocks. This study discusses an authorized distributor of smartphone and tablet computer products in Indonesia. Currently, the company is considering a plan to take over the role of a logistics service company to reduce the total logistics costs that must be incurred by making improvements in terms of inventory management. Inventory management can also protect the company from the impact of inflation and price increases that will impose logistics costs. This study has assumed that the vehicle travel speed or travel time between two nodes is fixed. This study contributes to minimizing total logistics costs by integrating the concept of a continuous review lot size-reorder point (Q, R) inventory model with lost sales and vehicle routing problems with time windows (VRPTW). Continuous review (Q, R) inventory model with lost sales shows the retailers’ cycle demand ranges from 130 to 234 units. This condition leads to the value of the expected average annual inventory cost IDR 27.263.204.625,59. Based on the VRPTW calculation, the total distribution cost per trip is IDR 445.631.642,7. Based on the current total distribution costs, it was found that the total distribution costs were IDR 849.454.616,2, so there is a decrease in distribution costs of 47.54%. The total logistics cost that must be incurred by the company to deliver smartphone products to 10 retailers in Jakarta and its surrounding areas is IDR 27,708,836,268.29.

Alternative Bus Stop Configuration: An Analysis of the Effects of Bus Bulbs

Bus bulbs are sections of sidewalk that extend from the curb of a parking lane to the edge of the through lane. A major advantage of using bus bulbs is the creation of additional space at a bus stop for shelters, benches, and other bus patron improvements when the inclusion of these amenities would otherwise be limited without the additional space.Several large cities on the West Coast have begun to explore bus bulbs as one of many strategies used in developing a transit preferential program. Researchers visited four transit agencies that use bus bulbs (San Francisco, Portland, Seattle, and Vancouver, British Columbia) to observe and document existing and planned bus bulbs. Before and after studies were conducted to determine if there was a change in pedestrian and traffic operations after the installation of bus bulbs. The bus bulb design was clearly an improvement in pedestrian space as compared to the bus bay design. The average amount of available space for pedestrians and transit patrons alike improved from 19 to 44 square feet/pedestrian (1.8 to 4.1 sq m/ped) after the bulb was constructed. The replacement of a bus bay with a bus bulb improved vehicle and bus speeds on the block. The block with the farside stop saw a statistically significant increase in vehicle travel speed during both nonpeak (9.5 to 15.7 mph [15.3 to 25.3 km/h]) and peak (11.4 to 20.9 mph [18.4 to 33.6 km/h]) periods.

A Chaotic Genetic Algorithm with Variable Neighborhood Search for Solving Time-Dependent Green VRPTW with Fuzzy Demand

Aiming at the time-dependent green vehicle routing problem with fuzzy demand, this paper comprehensively considers the dispatch costs, time window penalty costs, fuel costs, and the effects of vehicle travel speed, road gradient, and vehicle load on fuel consumption, a mixed integer programming model is formulated based on pre-optimization and re-optimization strategies. The traditional vehicle routing problems are modeled based on a symmetric graph. In this paper, considering the influence of time-dependent networks on route optimization, modeling is based on an asymmetric graph, which increases the complexity of the problem. In the pre-optimization stage, a pre-optimization scheme is generated based on the credibility measure theory; in the re-optimization stage, a new re-optimization strategy was used to deal with the service failure node In order to solve this problem, we developed a chaotic genetic algorithm with variable neighborhood search, pseudo-randomness of chaos was introduced to ensure the diversity of initial solutions, and adaptive neighborhood search times strategy and inferior solution acceptance mechanism were proposed to improve the performance of the algorithm. The numerical results show that the model and algorithm we proposed are effective.

Development of transportation loading spectra for building modules based on a vehicle-module interaction model

The wastage associated with the damage of single building modules when subjected to dynamic loading (termed transportation loading) from heavy vehicles during road transportation is a primary deterrent to the adoption of modular construction. In this paper, generalized transportation loading spectra were developed to quantify transportation loading for the structural design of building modules. First, a shaking table test was conducted on a scaled-down model representing the module transportation scenario to explore the resonant responses between the vehicle and module. Then, a proposed vehicle-module interaction model accurately simulated the vertical acceleration responses derived from the shaking table test. Finally, the vehicle-module interaction model was extended to a realistic module transportation situation; the acceleration power spectral densities (PSDs) on the vehicle chassis from the extended models characterized the loading spectra. A parametric study involving vehicle type, module category, road roughness, and travel speed demonstrates that the loading spectra consist of five scalable PSDs under Class A-E roads (from A-H classification of ISO 8608). Three peaks are observed in each PSD, with two high peaks consistent with measured PSDs from the literature. Among the spectra, PSDs under B-D roads are applicable for most module transportation scenarios.

Research on 4WS Agricultural Machine Path Tracking Algorithm Based on Fuzzy Control Pure Tracking Model

This paper presents a path tracking algorithm based on a fuzzy control pure tracking model for autonomous navigation of 4WS agricultural machines. The aim of this research is to implement path tracking for unmanned 4WS agricultural machinery and to solve the problem of difficult determination of forward-looking distances in pure tracking algorithms. By using the pure tracking algorithm model and a fuzzy controller, this paper converts the heading deviation and lateral deviation in one control cycle into the sum of lateral deviation as the first input to the fuzzy controller and the vehicle travel speed as the second input to the fuzzy controller, thus outputting the actual forward-looking distance. In order to verify the practicality, accuracy, and path tracking precision of the proposed path tracking algorithm, a straight-line path tracking test under variable speed conditions and a turning path tracking test under non-fixed forward-looking distance conditions were carried out using a test platform after simulation on MATLAB/Simulink in this paper. The test results show that: in the straight-line path tracking process, the maximum overshoot is 0.123 m, and after stable driving, the maximum lateral deviation of the straight-line tracking part is 0.058 m and the steady-state deviation is 0.039 m; in the bow-turn path tracking process, the absolute value of the maximum lateral deviation of the actual driving trajectory of the farm machine from the desired path is 0.139 m, and the average tracking deviation is 0.041 m. It can be seen that the path tracking control algorithm proposed in this paper has good tracking accuracy as well as convergence, and can meet the demand for the autonomous navigation function of 4WS agricultural machinery, which has a certain application value.

Detecting spatiotemporal traffic events using geosocial media data

Social media platforms enable efficient traffic event detection by allowing users to produce geo-tagged content (e.g., tweets) known as geosocial media data. Geosocial media data improve road safety by providing timely updates for traffic flow and traffic control. Recent studies on traffic event detection with geosocial media data have been focused around keyword-based query approaches, where the event content was inferred by predetermined categories, to retrieve relevant traffic events. Spatiotemporal features associated with traffic-related posts have not been fully investigated. In this study, we filtered irrelevant posts with association rules. A spatiotemporal clustering-based method was then used to retrieve traffic events from these filtered posts, where the content of detected events was automatically inferred with a set of representative terms. For comparison, a typical text classification-based method was also used by classifying the posts filtered from association rules into different categories. By validating the detection results with vehicle travel speed data, we demonstrate that the former outperforms the latter in terms of the number of correctly detected traffic events from one-year of Twitter data in Toronto, Canada. Our proposed approach helps organizations and governments to be aware of when and where traffic events occur by identifying event hotspots and peak periods, which improves both traffic management and urban planning.

Numerical Investigation on the Dynamic Performance of Steel–Concrete Composite Continuous Rigid Bridges Subjected to Moving Vehicles

Assembly construction is the main feature of industrialized bridges, and π-shaped section steel–concrete composites that are continuously rigid have been widely used in engineering fields in recent years; however, their dynamic responses and corresponding impact coefficients in positive and negative moment regions need to be further studied. First, considering the interface slip model, we established a finite element model for the π-shaped continuous region section of the steel–concrete composite on the Sutai Expressway Tongfu No. 3 viaduct. Second, the bridge deck unevenness parameters were generated by preparing a MATLAB program with random calculations and were added to the bridge deck as the excitation load along with the vehicle load. Such parameters are defined on the basis of considering the vertical degrees of freedom of the four wheels and of one vehicle rigid body. Finally, we analyzed the displacement or stress impact coefficients as the dynamic response index of the bridge by adjusting the vehicle travel speeds, vehicle weights, interface slip stiffness values, and deck unevenness values. The results show that the change in vehicle travel speed and the change in vehicle load weight have some influence on the change in the dynamic effect of the combined beam, but this change is not significant. Moreover, the unevenness and interface slip strength changes have a large effect on the dynamic effect of the combination beam, which can significantly change the impact coefficient of the combination beam bridge. The worse the unevenness of the bridge deck is, the lower the grade of interface slip for the steel–concrete composite bridges and the higher the impact coefficient. We calculated the recommended impact coefficient values of the steel–concrete composite bridge based on the specifications for various countries, and they range from 1.16 to 1.4; such values are similar to the finite element calculation results.

Modeling of urban road network traffic carrying capacity based on equivalent traffic flow

The determination of the traffic carrying capacity of road network is of great significance to the scale control of urban vehicles and the control of transportation systems. Existing related works have proposed calculation models and solutions for different application environments. However, these studies have problems such as diversification of capacity definitions, incorrect analysis of factors, and excessive model constraints. In response to these problems, this paper aims to determine the connotation of traffic carrying capacity and put forward a novel calculation model for carrying capacity. Firstly, in-depth analysis found that the key factor affecting the number of vehicles is the service level of road network. Then, the connotation of traffic carrying capacity is clarified, that is, the maximum number of vehicles travelling simultaneously in the road network under a certain service level. Second, based on the definition of carrying capacity and the characterization relationship between average travel speed and service level, the calculation of carrying capacity is transformed into the establishment of relationship between average travel speed and maximum number of vehicles. The construction of this relationship includes five steps, which are proposal of equivalent lane, division of traffic basic units, construction of basic unit travel time model, calculation of basic unit carrying capacity, and calculation of road network carrying capacity. In particular, the proposal of equivalent lane achieves the conversion from intermittent flow to continuous flow, and the abstraction of traffic flow further unifies the operation process into a unified mode of free travel and stacked release. Finally, the VISSIM simulation software is employed to verify and evaluate the proposed models. The results show that the average relative error between the simulated data and the calculated data obtained from the model is -0. 46%. Findings from this study will provide an innovative idea for the evaluation of urban road network performance. It can also provide a basis for urban managers to improve service level of road network and optimize the design of transportation system.

The Method of Dynamic Identification of the Maximum Speed Limit of Expressway Based on Electronic Toll Collection Data

To overcome the drawbacks of the maximum speed limit information of expressways (i.e., long update cycle and great complexity of information recognition), in this work, an Electronic Toll Collection (ETC) gantry data-based method for dynamically identifying the maximum speed limit information of expressways is proposed. Firstly, the characteristics of the ETC gantry data are analyzed, and then data are cleaned and reconstructed, after which an algorithm is proposed for constructing a vehicle travel speed data set. Secondly, the speed feature vector model of the road section is established by taking the relationship among the speed distribution feature, time domain feature, and the maximum speed limit of the road section into consideration. Then, a data supplement algorithm is constructed to solve the problem of the imbalance of data samples. Finally, the combined GC-XGBoost classification algorithm is used to train and learn the potential speed limit features, and it is verified through the Fujian Provincial Expressway ETC data and the speed limit information provided by the Fujian Traffic Police. The result shows that the accuracy of the method in the recognition of the maximum limited speed information of the expressway is 97.5%. Compared with the traditional limited speed information recognition and extraction methods, the proposed approach can identify the maximum limited speed information of each section of the expressway more efficiently. It can also accurately identify the dynamic change of the maximum limited speed information, which is able to provide data support for intelligent expressway management systems and map providers.