Passenger Car and Heavy Truck Cold Cranking Studies - Effects of Oil Viscosity and Vehicle Type

2009 ◽  
pp. 137-137-24 ◽  
Author(s):  
AG Alexander ◽  
GA MacAlpine ◽  
CJ May ◽  
CR Smith
Keyword(s):  
Oil Viscosity ◽  
Passenger Car ◽  
Vehicle Type ◽  
Heavy Truck

Passenger Car Equivalents of Light Duty Trucks and the Costs of Mixed Vehicle Traffic: Evidence from Michigan

2011 ◽  
Author(s):  
Sarah B. Cosgrove
Keyword(s):  
United States ◽  
The United States ◽  
Transportation System ◽  
External Cost ◽  
Passenger Car ◽  
Vehicle Type ◽  
Light Duty ◽  
Different Types ◽  
Detroit Area ◽  
Instrumented Vehicles

This study uses naturalistic data from drivers operating instrumented vehicles to estimate the following distance by vehicle type and compute the passenger car equivalents of light duty trucks (LDTs). Unlike most previous studies, this study separates LDTs by vehicle type and produces evidence that cars follow different types of LDTs at different distances. While car drivers follow pickup trucks more closely, they follow SUVs and minivans at a greater distance. The external cost on the transportation system is estimated to be approximately $37 million annually in the Detroit area and $2.05 billion annually for the United States as a whole.

scholarly journals Car Ratings Take a Back Seat to Vehicle Type: Outcomes of SUV Versus Passenger Car Crashes

2021 ◽  
Vol 2 (4) ◽  
Author(s):  
Dietrich Jehle ◽  
Albert Arslan ◽  
Chirag Doshi ◽  
Clay O'Brien
Keyword(s):  
Passenger Car ◽  
Vehicle Type ◽  
Back Seat ◽  
Car Crashes

An Investigation of Engine Oil Viscosity Loss in Passenger Car Service and Its Characterization

1992 ◽  
Author(s):  
Julian H. Dancy ◽  
David L. Alexander ◽  
Scott O. Lindholm ◽  
David C. DiBerto
Keyword(s):  
Engine Oil ◽  
Oil Viscosity ◽  
Passenger Car

Does Separating Trucks from Other Traffic Improve Overall Safety?

2005 ◽  
Vol 1922 (1) ◽  
pp. 156-166 ◽  
Author(s):  
Dominique Lord ◽  
Dan Middleton ◽  
Jeffrey Whitacre
Keyword(s):  
Clear Understanding ◽  
Mixed Traffic ◽  
Contributing Factors ◽  
Truck Traffic ◽  
Passenger Cars ◽  
Construction Costs ◽  
Passenger Car ◽  
Good Opportunity ◽  
Crash Data ◽  
Vehicle Type

Decision makers have long speculated that building separate roads for trucks and passenger cars, or at least separating these into their own lanes, would accomplish two major objectives: (a) roadways would be made safer for passenger cars and (b) roadways designed specifically for a select class of vehicles rather than for all vehicles might represent overall savings in construction costs. This paper addresses the first objective. Recent studies on the evaluation of safety effects of truck traffic levels on general freeway facilities have not provided a clear understanding of how they affect the number of crashes. In some cases, studies have been contradictory. In addition, no studies have specifically compared passenger car–only with mixed-traffic freeway facilities. The research on which this paper is based aimed to assess whether more homogeneous flows of traffic by vehicle type are safer than the current mixed-flow scenario. An exploratory analysis of crash data was conducted on selected freeway sections of the New Jersey Turnpike for 2002. These sections operate as a dual–dual freeway facility: divided inner and outer lanes. At these locations, the inner lanes have the special characteristic of being for passenger cars only (homogeneous traffic). The selected sections, therefore, offer a very good opportunity to compare the crash experience between passenger car–only and mixed-traffic rural freeway facilities. The results of the study show that outer lanes experience more crashes, both when raw numbers are used and when exposure is included in the analysis. It was shown that truck-related crashes contribute significantly to the total number of crashes on the outer lanes. In fact, trucks are overinvolved in crashes given the exposure on these sections. Although the outcome of this study suggests that separating truck traffic from passenger cars for freeway facilities improves safety, further work is needed to understand the contributing factors leading to truck-related crashes in the outer lanes.

Vehicle and Occupant Response in Heavy Truck to Passenger Car Sideswipe Impacts

2001 ◽  
Author(s):  
C. Brian Tanner ◽  
John F. Wiechel ◽  
Dennis A. Guenther
Keyword(s):  
Passenger Car ◽  
Heavy Truck

scholarly journals Analysis of Vehicle-Following Heterogeneity Using Self-Organizing Feature Maps

2014 ◽  
Vol 2014 ◽  
pp. 1-11 ◽  
Author(s):  
Jie Yang ◽  
Ruey Long Cheu ◽  
Xiucheng Guo ◽  
Alicia Romo
Keyword(s):  
Relative Velocity ◽  
Data Sets ◽  
Feature Maps ◽  
Passenger Cars ◽  
Passenger Car ◽  
Feature Map ◽  
Car Following ◽  
Vehicle Type ◽  
Vehicle Trajectories ◽  
Self Organizing

A self-organizing feature map (SOM) was used to represent vehicle-following and to analyze the heterogeneities in vehicle-following behavior. The SOM was constructed in such a way that the prototype vectors represented vehicle-following stimuli (the follower’s velocity, relative velocity, and gap) while the output signals represented the response (the follower’s acceleration). Vehicle trajectories collected at a northbound segment of Interstate 80 Freeway at Emeryville, CA, were used to train the SOM. The trajectory information of two selected pairs of passenger cars was then fed into the trained SOM to identify similar stimuli experienced by the followers. The observed responses, when the stimuli were classified by the SOM into the same category, were compared to discover the interdriver heterogeneity. The acceleration profile of another passenger car was analyzed in the same fashion to observe the interdriver heterogeneity. The distribution of responses derived from data sets of car-following-car and car-following-truck, respectively, was compared to ascertain inter-vehicle-type heterogeneity.

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

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.

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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