Traffic Engineering Design, Second Edition

Richardson, Gail Ryder; Matthews, Paul; Guest, Peter

doi:10.1201/b12858

Cited by 5 publications

(4 citation statements)

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“…It is also understood that the quantum of work depends on the types of data required and traffic conditions. Another disadvantage of this method is that only a limited length of survey stretch, around 200 m [33] to 400 m [73] can be recorded depending on the resolution of images and field of view of the camera. The requirement of an elevated position is also a limitation of this method.…”

Section: Video-recording Methodsmentioning

confidence: 99%

Towards Behavioral Modeling of Drivers in Mixed Traffic Conditions

Munigety

Mathew

2016

Transp. in Dev. Econ.

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Mixed traffic conditions characterized by the presence of different vehicle types and weak lane discipline are common in the developing world. Different maneuvering capabilities of different vehicle types lead to vehicle-type dependent longitudinal and lateral movement driving behaviors. Weak lane discipline allows drivers to simultaneously look for possible lateral movements while progressing longitudinally. This integrated driving behavior gives rise to various driving phenomena like tailgating, multiple-leader following, swerving and filtering. However, very few studies exist in the literature that attempt to model these typical driving behaviors of mixed traffic streams. Moreover, most of these studies are not often readily available. Thus, a comprehensive review of the studies that consider modeling driver behavior in mixed traffic conditions is presented in this paper. Often, models developed for mixed traffic conditions stemmed out of the basic principles employed in the development of homogeneous traffic models. Hence, this paper first reviews the lane-based macro-, micro-and meso-scopic models in tandem and identifies their strengths and weaknesses in describing the mixed traffic system. A thorough understanding and conceptualization of any system is possible by analyzing large sets of empirical data. Therefore, a brief review on traffic data requirements to understand and model the driver behavior and, data extraction tools to obtain the trajectories of vehicles is presented next. Driver behavioral models form the core of any microscopic traffic simulation model. Core behavioral models such as carfollowing and lane-changing models which describe the longitudinal and lateral movements of drivers respectively are reviewed next. However, these two behavioral models may not be able to describe the integrated driving behavior independently. Therefore, various integrated driver behavioral models are briefed next. A simulation framework is essential to implement the driver behavioral models and evaluate their capabilities in representing larger scale traffic systems. Hence, a brief review of various simulation frameworks is presented subsequently. Finally, the challenges that are involved in modeling driver behavior in mixed traffic conditions are discussed and some useful research directions are proposed.

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Section: Video-recording Methodsmentioning

confidence: 99%

Towards Behavioral Modeling of Drivers in Mixed Traffic Conditions

Munigety

Mathew

2016

Transp. in Dev. Econ.

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“…The study and also the research on optimization of fuzzy control in traffic signal control continues in making progress until now [5,6,7,14,16,17].…”

Section: If Cycle Time and Arrivals (Vehicle Arrival Rate) And Queue mentioning

confidence: 99%

Enhanced adaptive traffic signal control system using camera sensor and embedded system

Afif

Rachmadi

Wibowo

et al. 2011

2011 International Symposium on Micro-NanoMechatronics and Human Science

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Traffic plays an important role in social stability and community development. Without an appropriate traffic signal control system, the possibility of traffic congestion will be very high and causes various negative impacts. The traffic signal control system with video camera sensor is implemented in embedded systems using BeagleBoard-xM. The system uses Viola-Jones method and Haar Training in detecting the vehicle object from a video frame. Then, Euclidean distance and kalman filter methods are used in tracking the vehicle. The ability of kalman filter in predicting the next position of the object is a very important feature for multi-object tracking. The number of counted vehicles in each lane at the intersection then will be processed using Fuzzy Logic to determine optimal cycle time and split time.

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“…The common type of intersection is the un-signalized intersection, which is used to regulate low volume of traffic flow between the major and minor streets [12]. Slinn et al [13] proposed the following selection criteria for intersections: two lightly trafficked residential roadspriority junction: the through carriageway of a motorway -grade separation: heavily trafficked urban cross roads with heavy pedestrian flows -traffic signals: and suburban dual carriageways with substantial heavy goods traffic -conventional roundabout. According to the procedures outlined for two-way stop controlled (TWSC) intersections in [10], estimating level of service requires evaluation of critical gap, follow-up time, and impedance and capacity calculations.…”

Section: Introductionmentioning

confidence: 99%

Operational evaluation of Obafemi Awolowo University main gate – Ede Road intersection

Mohammed¹,

Oyebode²,

Oyefeso³

2020

Nig. J. Tech.

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Vehicular traffic at Obafemi Awolowo University has increased over the years, resulting in delay at The Main Gate – Ede Road Intersection. This paper evaluated its present level of service with a view to addressing this situation. Geometric survey of the intersection was carried out. Peak hour traffic studies were conducted for a week and the traffic characteristics and volume were determined using standard procedure. The level of service (LOS) of the intersection was thereafter obtained. The geometrics of the intersection showed that, two lanes exist on the East Bound (EB) and West Bound (WB) approaches, as well as a dual lane on the North Bound (NB) and South Bound (SB) approaches. The traffic volume count was 1378, 931, 1168 and 1123 veh/h for the NB, SB, EB and WB respectively. The level of service at the intersection is B, thus implying that it exhibits a slight delay. Keywords: Level of Service, Road intersection, Road geometry, Traffic delay

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Traffic Engineering Design, Second Edition

Cited by 5 publications

References 0 publications

Towards Behavioral Modeling of Drivers in Mixed Traffic Conditions

Towards Behavioral Modeling of Drivers in Mixed Traffic Conditions

Enhanced adaptive traffic signal control system using camera sensor and embedded system

Operational evaluation of Obafemi Awolowo University main gate – Ede Road intersection

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