A Comprehensive Review on Traffic Prediction for Intelligent Transport System

Suhas, S.; Kalyan, Varichitty; Katti, M. R.; Prakash, B. V. Ajay; Naveena, C

doi:10.1109/icraect.2017.33

Cited by 21 publications

(8 citation statements)

References 23 publications

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“…The fundamental relationship between volume and speed is that with the increase in traffic volume, the average speed of its space will decrease until the critical density (maximum volume) is reached. (Altintasi, 2017); (Suhas, 2017); (MKJI, 1997). The relationship between volume and speed is shown in figure 1 Once the critical density is reached, the average speed of space and volume will decrease.…”

Section: Relationship Of Traffic Flow and Volume Vehicle Speed And Tr...mentioning

confidence: 99%

The Effectiveness Analysis of Frontage Road on Jalan Margonda Raya, Depok

Assalam¹,

Rifai²,

Taufik³

2023

IJOMS

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Highways are the central infrastructure that supports land transportation. Therefore, the highway strongly supports various activities and human needs in land mobilization so that it can achieve its goals both in economic and non-economic terms. In particular, on some highways, there is a system that divides the road into two special lanes: the frontage road and the fast lane. This study aimed to assess the effectiveness of the frontage road on Jalan Margonda Raya, Depok. The data retrieval method is to survey directly and retrieve data through CCTV during peak hours on the road. From the results of this study, the average speed of a motorcycle is 26.625 km / h, which is below the standard free current speed based on the 1997 MKJI of 32.64 km / h, while the average speed of light vehicles (angkot) is 9.9375 km / h, which is below the standard free current speed based on MKJI 1997 which is 41.48 km / h and also obtained a saturation degree value of 1.1105 which means that the frontage road on Jalan Margonda Raya has a Level of Service F value. Therefore, it can be concluded that the frontage road on Jalan Margonda Raya has conditions of forced current, low speed, volume above capacity, and long lines (traffic jams).

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Section: Relationship Of Traffic Flow and Volume Vehicle Speed And Tr...mentioning

confidence: 99%

The Effectiveness Analysis of Frontage Road on Jalan Margonda Raya, Depok

Assalam¹,

Rifai²,

Taufik³

2023

IJOMS

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“…P. Martin-Martin et al stated that his work presents the viability of the different ML techniques for their application in the problem of autonomous driving [10]. S. Suhas et al in his review on Traffic Prediction for ITS focused much on aggregating previous on traffic prediction, highlighting marked changes in trends and provide research direction for future work [11]. A. Zeer et al wrote in his work that aimed at conducting systematic analysis ITS and summarized their work into issues in ITS and techniques used to solve the issues [12].…”

Section: IImentioning

confidence: 99%

Intelligent Transport Systems

Kazembe¹

2022

IJRASET

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Growing economic activities aand others are among the factors that make many cities busy places today especially in traffic systems. Road networks that seem to be spacious sometimes become completely congested so much so that traffic mobility looks standstill. This impacts negatively on traffic users resources in terms of time management, fuel and other resource. This paper discusses the background trend in traffic activities amid congestion environment and proposes an Intelligent Traffic System that uses Machine Learning technique of predictive classification and regression to help traffic users determine forehand on the congestion status of available roads or highways. This further suggests that if the road user tries to avoid congestion, then the congestion levels will minimize. For simplicity, the data that has been used for congestion has been from a csv file containing previous datasets of local roads or highways.

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“…In 2012, Castro et al [9] presented a method based on traffic flow, which is the number of vehicles per unit of time. Suhas et al [10] showed in a review paper that volume is the most common feature used in traffic prediction. However, methods based on the number of vehicles like flow and volume may not be suitable for GPS data because they are sparse.…”

Section: Literature Reviewmentioning

confidence: 99%

From Massive Trajectory Data to Traffic Modeling for Better Behavior Prediction in a Usage-Based Insurance Context

Blais

Badard

Duchesne

et al. 2020

IJGI

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Usage-Based Insurance (UBI) is an insurance framework that has made its appearance in the last few years. It allows direct measurement of the traveling of policyholders, hence the growing interest of the industry to better understand driving behaviors. UBI generates large data volumes, from which events can be extracted, like harsh brakes or accelerations. Still, these events are measured without contextual information, which limits their explanatory power. Traffic is one of these types of contextual information that may have great potential, but access to such data remains an issue. Solutions exist, like traffic data from external providers, but for insurance companies that conduct business over large areas, this could result in very large costs. This paper demonstrates that data from insurance companies acquired via UBI can be used to model traffic. A method based on link travel time is proposed and tested on four Canadian cities. Then, routes created with the model are compared with those created using Google Maps. The results show that for 38 routes with an average length of around 5 km, the difference between the travel time of the routes of the proposed model and Google Maps is as small as one second on average.

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A Comprehensive Review on Traffic Prediction for Intelligent Transport System

Cited by 21 publications

References 23 publications

The Effectiveness Analysis of Frontage Road on Jalan Margonda Raya, Depok

The Effectiveness Analysis of Frontage Road on Jalan Margonda Raya, Depok

Intelligent Transport Systems

From Massive Trajectory Data to Traffic Modeling for Better Behavior Prediction in a Usage-Based Insurance Context

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