Comments on Effects of Vehicle Type and Age on Driver Behaviour at Signalized Intersections

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.

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A Comparative Study on Drivers’ Stop/Go Behavior at Signalized Intersections Based on Decision Tree Classification Model

Journal of Advanced Transportation ◽

10.1155/2020/1250827 ◽

2020 ◽

Vol 2020 ◽

pp. 1-13 ◽

Cited By ~ 1

Author(s):

Sheng Dong ◽

Jibiao Zhou

Keyword(s):

Decision Making ◽

Decision Tree ◽

High Speed ◽

Signalized Intersections ◽

Speed Limit ◽

Vehicle Type ◽

Decision Tree Classification ◽

Signal Change ◽

Signal Period ◽

Instantaneous Speed

The stop/go decisions at signalized intersections are closely related to driving speed during signal change intervals. The speed during stop/go decision-making has a significant influence on the dilemma area, resulting in changes of stop/go decisions and high complexity of the decision-making process. Considering that traffic delays and vehicle exhaust pollution are mainly caused by queuing at intersections, the stop-line passing speed during the signal change interval will affect both vehicle operation safety and the atmospheric environment. This paper presents a comparative study on drivers’ stop/go behaviors when facing a transition signal period consisting of 3 s green flashing light (FG) and 3 s yellow light (Y) at rural high-speed intersections and urban intersections. For this study, 1,459 high-quality vehicle trajectories of five intersections in Shanghai during the transition signal period were collected. Of these five intersections, three are high-speed intersections with a speed limit of 80 km/h, and the other two are urban intersections with a speed limit of 50 km/h. Trajectory data of these vehicle samples were statistically analyzed to investigate the general characteristics of potential influencing factors, including the instantaneous speed and the distance to the intersection at the start of FG, the vehicle type, and so on. Decision Tree Classification (DTC) models are developed to reveal the relationship between the drivers’ stop/go decisions and these possible influencing factors. The results indicate that the instantaneous speed of FG onset, the distance to the intersection at the start of FG, and the vehicle type are the most important predictors for both types of intersections. Besides, a DTC model can offer a simple way of modeling drivers’ stopping decision behavior and produce good results for urban intersections.

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Speeds of Right-Turning Vehicles at Signalized Intersections during Green or Yellow Phase

Transportation Research Record Journal of the Transportation Research Board ◽

10.1177/03611981211011642 ◽

2021 ◽

pp. 036119812110116

Author(s):

Kay Fitzpatrick ◽

Michael P. Pratt ◽

Raul Avelar

Keyword(s):

Pedestrian Safety ◽

Operational Efficiency ◽

Signalized Intersections ◽

Signalized Intersection ◽

Radius Of Curvature ◽

Vehicle Type ◽

Curvature Equation ◽

Site Characteristics ◽

Preceding Vehicle ◽

Selection Of

The operation and design of signalized intersections involves tradeoffs between operational efficiency and safety for a variety of users, including motorists, pedestrians, and bicyclists. Additionally, the mix of vehicle types in the fleet sometimes requires special considerations. These concerns especially apply to the selection of curb radius at the corners, where right-turning vehicles operate close to pedestrians. Larger curb radii accommodate the swept paths of trucks and allow right turns to occur at higher speeds but may compromise safety and security for pedestrians by increasing the crossing distance and increasing the frequency of higher-speed turns. The authors collected right-turn vehicle speeds at 31 urban signalized intersection approaches in Texas with radii ranging from 15 to 70 ft. The authors calibrated a model to predict right-turn speeds as a function of site characteristics including curb radius, leading headway, vehicle type (car versus truck), maneuver of the preceding vehicle (through versus right turn), and signal indication (yellow or green). The analysis results indicate that right-turn speeds increase slightly with increasing radius, if the preceding vehicle proceeds through (rather than turning right) at the intersection, or if the signal indication is yellow rather than green. The calculated 85th percentile turning speed is generally higher than the assumed speed calculated using the radius of curvature equation. These trends should be considered if the intersection is expected to have notable volumes of pedestrians or trucks, as lower speeds are desirable for pedestrian safety, but larger radii may be necessary to accommodate turning trucks.

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Unbalanced Multiple Left Turn Lane Usage Modelling: From Individual Choice to Aggregate Volume

Journal of Advanced Transportation ◽

10.1155/2019/5107327 ◽

2019 ◽

Vol 2019 ◽

pp. 1-13

Author(s):

Li Li ◽

Qing-Chang Lu ◽

Dong Zhang ◽

Ping Wang ◽

Gui-Ping Wang

Keyword(s):

Discrete Choice ◽

Traffic Control ◽

Choice Model ◽

Signalized Intersections ◽

Influential Factors ◽

Individual Choice ◽

Left Turn ◽

Vehicle Type ◽

Traffic Distribution ◽

Turning Radius

Diverse lane preferences of left-turn drivers lead to unbalanced traffic distribution on multiple left-turn lanes. The preferences can be measured in terms of lane usage at macroscopic level and individual lane choice at microscopic level. The data of lane volume and individual lane choices are collected at eight dual or triple left-turn lanes equipped in signalized intersections in China. Linear regression model with dummy variables and discrete choice model were applied to analyse drivers’ lane choosing patterns at macroscopic and microscopic levels, respectively, and results of the two studies are mutually verified and complemented. The drivers’ lane preferences are found to vary with approach configurations, traffic control, and the number of lanes available. Static influential factors, such as turning radius inside the intersection, the design of shadowed lane, and intersection skewedness, as well as dynamic influential factors, including queue length, heavy vehicle in queue back and subject vehicle type, could affect the drivers’ lane preferences. The findings of this study have important implications for intersection design and traffic control in practice.

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Characterization of the Noise Emissions of a Passenger Vehicle

Volume 8: Mechanics of Solids, Structures and Fluids; Vibration, Acoustics and Wave Propagation ◽

10.1115/imece2011-63392 ◽

2011 ◽

Author(s):

Jose´ Luis San Roma´n ◽

Vicente Di´az ◽

Pedro Cobo ◽

Carolina A´lvarez-Caldas ◽

Jose´ Antonio Calvo ◽

...

Keyword(s):

Engine Speed ◽

Can Bus ◽

Noise Pollution ◽

Passenger Vehicle ◽

Noise Emission ◽

Driver Behaviour ◽

Vehicle Type ◽

Physical Measurements ◽

Speed Engine

One of the main sources of noise pollution in cities is vehicle traffic. In this paper a characterization of the noise emission of a passenger vehicle has been carried out. With this aim a representative driving route for noise emission has been defined in order to study the influence of the driver typology and vehicle type. Therefore, this investigation has been developed in three phases: Firstly, usual driving in an urban area like Madrid has been characterized with a specific driving route. In addition, several vehicle models with great presence in the existing fleet of cars have been selected. Several drivers have covered the driving route at different times of the day and previous parameters have been measured in each test in order to determine average values of behavior. Secondly, the type of vehicles and drivers influence in noise emissions has been deeply analyzed. To achieve this aim a sample of vehicles has been instrumented to obtain physical measurements of the variables that can influence the noise emission level. Positions, velocities, accelerations (longitudinal and lateral) and time have been analyzed using a GPS sensor. Parameters such as, engine speed, engine load, throttle position and engine temperature have been studied through the vehicle CAN BUS and a set of microphones has measured the emitted noise in several points of the vehicle. In order to study the ecological and safety impact in urban and interurban roads by means of the measurement of noise emissions the analysis of the driver behaviour is of paramount importance. To conclude, the previous data has been analyzed and noise equivalent levels have been identified with different test configurations.

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PASSENGER CAR EQUIVALENT AT SIGNALIZED INTERSECTIONS WITH COUNTDOWN TIMER IN MALANG CITY

Jurnal Rekayasa Sipil dan Lingkungan ◽

10.19184/jrsl.v2i01.6441 ◽

2018 ◽

Vol 2 (01) ◽

pp. 99

Author(s):

Dikka Anggoro ◽

Harnen Sulistio ◽

Achmad Wicaksono ◽

Sonya Sulistyono

Keyword(s):

Video Camera ◽

Signalized Intersections ◽

Heavy Vehicle ◽

Heavy Vehicles ◽

Highway Capacity ◽

Passenger Car ◽

Vehicle Type ◽

Digital Video Camera ◽

Significant Difference ◽

Passenger Car Equivalent

Passenger car equivalents (PCE) is used in highway capacity analysis to convert a mixed vehicle flow into an equvalent passenger car flow. PCE value for a vehicle is not constant but varies with traffic and roadway conditions arround. In this study, PCE for motorcycle, light vehicle and heavy vehicle were developed at signalized intersection on saturation condition with and without countdown timer (CDT) in Malang City and to evaluate the value of analysis pcu and MKJI 1997 pcu. PCE data were collected at five intersection; Ciliwung, Dieng, BCA, L.A. Sucipto and Rampal intersection. A digital video camera was utilized for data collection and linier regresion method was used to calculate the PCE values. The analysis result shows for the average pcu value for the type of motorcycle (MC) at countdown timer on and off condition is 0,294 and 0,293. As for the types of heavy vehicles (HV) at countdown timer on and off conditions are 1.565 and 1.507. While to evaluate the pcu value, there is a significant difference between the value of pcu analysis results with the value of MKJI 1997 with a level of confidence in the significance of 95%. For percentage of motorcylce type (MC) if the percentage value of 75% the pcu value will increase. While for heavy vehicle type (HV) if the percentage is above 1.5% then the value of emp will increase because HV type has big dimension. Ekivalensi mobil penumpang (emp) digunakan untuk analisis kapasitas jalan. Nilai emp untuk kendaraan tidaklah konstan atau sama tetapi memiliki nilai yang bervariasi. Pada penelitian ini mencari nilai emp untuk jenis kendaraan sepeda motor (MC) dan kendaraan berat (HV) pada simpang bersinyal pada kondisi jenuh dengan menggunakan countdown timer (CDT) pada kondisi on dan off. Data nilai emp dikumpulkan pada lima simpang di Kota Malang; Simpang Ciliwung, Dieng, BCA, L.A. Sucipto dan Rampal. Video kamera digunakan untuk merekam dan pengumpulan data dan untuk menghitung nilai emp menggunakan metode regresi linier. Hasil yang diperoleh menunjukan bahwa nilai rata-rata untuk sepeda motor pada kondisi CDT on dan off ialah 0,294 dan 0,293. Sedangkan untuk kendaraan berat (HV) untuk kondisi CDT on dan off ialah 1,565 dan 1,507. Sedangkan untuk evaluasi nilai emp terdapat perbedaan yang signifikan diantara nilai emp hasil analisis dengan nilai emp MKJI 1997 dengan tingkat kepercayaan sebesar 95%. Untuk persentase jenis MC, apabila persen kendaraan bermotor meningkat sebesar 75% maka nilai empnya akan meningkat. Sedangkan untuk HV, apabila persen kendaraan berat (HV) meningkat sebesar 1,5% maka nilai empnya akan meningkat dikarenakan dimensi yang besar.

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