Association of intersection approach speed with driver characteristics, vehicle type and traffic conditions comparing urban and suburban areas

2007 ◽  
Vol 39 (2) ◽  
pp. 216-223 ◽  
Author(s):  
Bor-Shong Liu
Keyword(s):  
Suburban Areas ◽  
Vehicle Type ◽  
Traffic Conditions ◽  
Approach Speed

scholarly journals Acceleration and Deceleration Rates of Various Vehicle Categories at Signalized Intersections in Mixed Traffic Conditions

2021 ◽  
Vol 49 (4) ◽  
pp. 324-332
Author(s):  
Sushmitha Ramireddy ◽  
Vineethreddy Ala ◽  
Ravishankar KVR ◽  
Arpan Mehar
Keyword(s):  
Close Relation ◽  
Accurate Estimation ◽  
Signal Design ◽  
Driver Behaviour ◽  
Vehicle Type ◽  
Traffic Conditions ◽  
Light Commercial Vehicle ◽  
Acceleration And Deceleration ◽  
Vast Variation ◽  
Two Wheeler

The acceleration and deceleration rates vary from one vehicle type to another. The same vehicle type also exhibits variations in acceleration and deceleration rates due to vast variation in their dynamic and physical characteristics, ratio between weight and power, driver behaviour during acceleration and deceleration manoeuvres. Accurate estimation of acceleration and deceleration rates is very important for proper signal design to ensure minimum control delay for vehicles, which are passing through the intersection. The present study measures acceleration and deceleration rates for four vehicle categories: Two-wheeler, Three-wheeler, Car, and Light Commercial Vehicle (LCV), by using Open Street Map (OSM) tracker mobile application. The acceleration and deceleration rates were measured at 24 signalized intersection approaches in Hyderabad and Warangal cities. The study also developed acceleration and deceleration models for each vehicle type and the developed models were validated based on field data. The results showed that the predicted acceleration and deceleration models showed close relation with those measured in the field. The developed models are useful in predicting average acceleration and deceleration rate for different vehicle types under mixed and poor lane disciplined traffic conditions.

scholarly journals Penghitungan Objek Berdasarkan Berdasarkan Jenis Kendaraan Bermotor pada CCTV Lalu Lintas Berbasis Pengolahan Citra Digital Menggunakan Metode Background Subtraction dan Blob Detection

2020 ◽  
Vol 2 (2) ◽  
pp. 92-99
Author(s):  
Andhika Putra Cahyono ◽  
Utomo Budiyanto
Keyword(s):  
Traffic Engineering ◽  
Moving Objects ◽  
Road Traffic ◽  
Confusion Matrix ◽  
Digital Processing ◽  
Detection Methods ◽  
The Road ◽  
Blob Detection ◽  
Vehicle Type ◽  
Traffic Conditions

In the road traffic space which is often encountered by passing traffic type of vehicle. To find out the traffic conditions that are needed to calculate vehicle traffic, such as using counting or recording CCTV video. This continues the long and long process that was completed on the error data and the slow pace of traffic engineering decisions. This method is difficult to do in full because of the limited number of counters. This can be done by involving digital processing and CCTV video to be able to classify and transfer vehicle type objects. There are several methods for sharing object imagery, such as SIFT, edge detection and Monte Carlo. This research tries to use the Background Substraction and Blob Detection methods because of its superiority in determining objects and backgrounds and being able to maintain moving objects as well as analyzing screen area calculations. The results of testing with this method obtained the MSE value at the threshold of 100 and 3x3 kernel filter with a pixel area of motorcycle 34-63 pixel-X, 67-155 pixel-Y and cars 73-200 pixel-X, 79-307 pixel-Y and bus / truck 130-128 pixel-X, 305-376 pixel-Y. On evaluation, use the confusion matrix obtained in the morning with an average total of 92% and at night with a total average of 73%. It can be concluded by using CCTV installation parameters and the method used can yields higher accuracy in the morning than at night with the weakness of compiling objects that can make it easier to make objects and test the night to obtain light from vehicle lights generated as vehicle objects the flight.

scholarly journals Incorrect U-turning of vehicles at intersections with traffic lights

2021 ◽  
Vol 57 (1) ◽  
pp. 131-145
Author(s):  
Tomasz Krukowicz ◽  
Krzysztof Firląg ◽  
Ewelina Sterniczuk
Keyword(s):  
Road Safety ◽  
Road Network ◽  
Field Tests ◽  
Video Observation ◽  
Traffic Lights ◽  
The Road ◽  
Vehicle Type ◽  
Traffic Conditions ◽  
Road Geometry ◽  
The Impact

The article describes the problem of incorrect U-turns at intersections with traffic lights. Statistical data on road incidents related to U-turns are presented. Then, the international, Polish and foreign regulations concerning u-turning at intersections with traffic lights were analysed. The situations in which U-turns are allowed or prohibit-ed are presented. The differences in design rules for junctions with U-turns in different countries have been taken into account. A literature review was also carried out that outlined various current U-turns around the world, including the design of turning places, the location of turning points, road safety when turning, and the impact of U-turns on traffic conditions. The further part of the article presents the results of field tests of the U-turn at 6 intersections located in Warsaw. The research was conducted by video observation. The results were broken down by age, gender, place of regis-tration of the vehicle, type of vehicle, and the effect of incorrect turning. Data on road incidents at the examined intersections were also analysed. Data from the database kept by the Police were compared with the measure-ment data. A regression analysis was performed between the types of recorded incorrect manoeuvres and the number of accidents at the intersection. The results of statistical analysis carried out do not indicate the existence of a relationship between the number of identified incorrect U-turns and the number of road incidents at inter-sections. Based on the research, it was found that the phenomenon of incorrect U-turns at intersections with traffic lights is common, and the use of directional (protected) signals does not eliminate this phenomenon. The conclusions indicate practical solutions to reduce the number of illegally U-turning vehicles. The recommended actions are related to the stage of shaping the road network, designing the road geometry and organizing traffic and traffic lights, and auditing road safety, as well as the stage of road operation.

Capacity of Unsignalized Intersections with Mixed Vehicle Flows

2003 ◽  
Vol 1852 (1) ◽  
pp. 265-270 ◽  
Author(s):  
Wenquan Li ◽  
Wei Wang ◽  
Dazhi Jiang
Keyword(s):  
Traffic Flow ◽  
Field Testing ◽  
Mixed Traffic ◽  
Vehicle Type ◽  
Traffic Conditions ◽  
Unsignalized Intersections ◽  
Capacity Theory ◽  
Capacity Model ◽  
Set Up ◽  
Gap Acceptance Theory

On the basis of gap-acceptance theory, mixed traffic flow composed of two representative vehicle types—heavy and light vehicles—is analyzed with probability theory. A capacity model is set up for an unsignalized intersection in which the minor-stream mixed traffic flows cross m major lanes and the traffic flow headways fit the M3 distribution; it is an extension of minor-lane capacity theory for one vehicle type and one major-stream traffic flow. A more complicated case with minor-stream flow composed of discretionary vehicle types is also considered, and the corresponding formula is given. After field testing in China, the conclusion is drawn that this model is better for analyzing Chinese traffic conditions than are other existing models.

Investigation of Crossing Conflicts by Vehicle Type at Unsignalized T-Intersections under Varying Roadway and Traffic Conditions in India

2021 ◽  
Vol 147 (2) ◽  
pp. 05020011
Author(s):  
Jaydip Goyani ◽  
Aninda Bijoy Paul ◽  
Ninad Gore ◽  
Shriniwas Arkatkar ◽  
Gaurang Joshi
Keyword(s):  
Vehicle Type ◽  
Traffic Conditions

scholarly journals Estimating Lateral Placement and Lane Indiscipline of Urban Mixed Traffic in Developing Country: An ANN Assisted Approach

2020 ◽  
Author(s):  
Harish Kumar Saini ◽  
Subhadip Biswas
Keyword(s):  
Mixed Traffic ◽  
Static And Dynamic Characteristics ◽  
Vehicle Type ◽  
Traffic Conditions ◽  
Vehicle Category ◽  
Traffic Stream ◽  
The Subject ◽  
Potential Factors ◽  
Traffic Composition ◽  
Urban Mixed Traffic

Information of lateral placement and lane indiscipline are useful in simulation of a mixed traffic stream and identifying the distressed portion of a pavement. In spite of these utilities, inadequate investigation was made to estimate the lateral placement of vehicles under prevailing traffic conditions. In a typical mixed traffic situation, vehicles having different static and dynamic characteristics take any lateral gap across the carriageway left empty by other surrounding vehicles and move in an untidy manner. It leads to variation in lateral placement of vehicles governed by the subject vehicle type. This paper explores the potential factors that influence lateral placement of vehicles and presents an Artificial Neural Network based approach to quantify lateral placement and lane indiscipline in context of undivided urban roads. Further, sensitivity analysis revealed how different traffic parameters like traffic volume, traffic composition and directional split influence lateral placement and lane indiscipline of a vehicle category.

A spring-mass-damper system dynamics-based driver-vehicle integrated model for representing heterogeneous traffic

2018 ◽  
Vol 32 (11) ◽  
pp. 1850135 ◽  
Author(s):  
Caleb Ronald Munigety
Keyword(s):  
Simulation Models ◽  
Integrated Model ◽  
Heterogeneous Traffic ◽  
Microscopic Simulation ◽  
Car Following ◽  
Vehicle Type ◽  
Traffic Conditions ◽  
Proposed Model ◽  
Mass Damper ◽  
The Stability

The traditional traffic microscopic simulation models consider driver and vehicle as a single unit to represent the movements of drivers in a traffic stream. Due to this very fact, the traditional car-following models have the driver behavior related parameters, but ignore the vehicle related aspects. This approach is appropriate for homogeneous traffic conditions where car is the major vehicle type. However, in heterogeneous traffic conditions where multiple vehicle types are present, it becomes important to incorporate the vehicle related parameters exclusively to account for the varying dynamic and static characteristics. Thus, this paper presents a driver-vehicle integrated model hinged on the principles involved in physics-based spring-mass-damper mechanical system. While the spring constant represents the driver’s aggressiveness, the damping constant and the mass component take care of the stability and size/weight related aspects, respectively. The proposed model when tested, behaved pragmatically in representing the vehicle-type dependent longitudinal movements of vehicles.

Deriving Pedestrian Risk Index by Vehicle Type and Road Geometry at Midblock Crosswalks under Heterogeneous Traffic Conditions

2020 ◽  
Vol 146 (10) ◽  
pp. 04020123
Author(s):  
Avinash R. Chaudhari ◽  
Ninad Gore ◽  
Shriniwas Arkatkar ◽  
Gaurang Joshi ◽  
Srinivas S. Pulugurtha
Keyword(s):  
Risk Index ◽  
Heterogeneous Traffic ◽  
Vehicle Type ◽  
Traffic Conditions ◽  
Road Geometry

Development of Passenger Car Equivalents for Freeways, Two-Lane Highways, and Arterials

1997 ◽  
Vol 1572 (1) ◽  
pp. 51-58 ◽  
Author(s):  
Lily Elefteriadou ◽  
Darren Torbic ◽  
Nathan Webster
Keyword(s):  
Full Range ◽  
Simulation Models ◽  
Heavy Vehicles ◽  
Highway Capacity ◽  
Passenger Car ◽  
Highway Capacity Manual ◽  
Vehicle Type ◽  
Traffic Conditions ◽  
Recreational Vehicles ◽  
The Impact

Passenger car equivalents (PCEs) have been used extensively in the Highway Capacity Manual to establish the impact of trucks, buses, and recreational vehicles on traffic operations. PCEs are currently being used for studying freeways, multilane highways, and two-lane highways. A heavy-vehicle factor is directly given for the impact of heavy vehicles at signalized intersections (and indirectly along arterials). These PCE values are typically based on a limited number of simulations and on older simulation models. In addition, the impact of variables such as traffic flow, truck percentage, truck type (i.e., length and weight/horsepower ratio), grade, and length of grade on PCEs has not been evaluated in depth for all facility types. The methodology for developing PCEs for different truck types for the full range of traffic conditions on freeways, two-lane highways, and arterials is described. Given the scope of this research and the variability of traffic conditions to be examined, simulation was selected as the most appropriate tool. The resulting PCE values for freeways, two-lane highways, and arterials indicated that some variables, such as percentage of trucks, do not always have the expected effect on PCEs, whereas other variables, such as vehicle type, are crucial in the calculations. Generally, major differences in PCEs occurred for the longer and steeper grades. There was great variability in PCE values as a function of the weight/horsepower ratio as well as of vehicle length.

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