Passenger Car Units at Different Levels of Service for Capacity Analysis of Multilane Interurban Highways in India

Mehar, Arpan; Chandra, Satish; Velmurugan, S.

doi:10.1061/(asce)te.1943-5436.0000615

Cited by 40 publications

(19 citation statements)

References 6 publications

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“…For example, with an increase in the traffic volume, PCUs calculated in Arasan and Krishnamurthy [7] show increasing and decreasing trends at lower and higher volumes, respectively. Similarly, in Mehar et al [55], only a decreasing trend is observed with the increase in traffic volume. While the logic of the specific method used is needed to explain these trends, they must be consistent with our intuition that the operating conditions change with the traffic volume.…”

Section: Methods Based On Areas and Speeds Of Vehiclesmentioning

confidence: 94%

“…In addition to its simplicity, no hypothetical scenario of passenger cars only traffic is needed to be considered in this method and it is not necessary to make use of relations based on any equivalence criterion. These advantages are, probably, the reason for its extensive usage in the later studies [55,56]. This idea is even extended to define motorcycle equivalent factors for the studies in countries where it is more meaningful to take Motorcycle as the design vehicle type [12,37].…”

Section: Methods Based On Areas and Speeds Of Vehiclesmentioning

confidence: 99%

“…However, care must be taken to avoid vehicles with significantly different characteristics to be grouped into the same category [55,56]. Multiple sources exist in the literature for these standard categories and their average dimensions [6,16,45].…”

Section: Classification and Sizes Of The Different Vehicle Typesmentioning

confidence: 99%

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Review of Studies on Mixed Traffic Flow: Perspective of Developing Economies

Kiran

Verma

2016

Transp. in Dev. Econ.

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The traffic scenario in developing economies is fundamentally different from that of the developed economies. The latter is predominantly composed of passenger cars and can be aptly termed as ''homogeneous'' traffic, whereas the former is composed of vehicle types with a wide variety of static and dynamic characteristics, which occupy the same right of way, resulting in an unsynchronized movement of the vehicles. Another distinguishing characteristic of this traffic is the absence of lane-discipline, resulting from the wide variation in sizes and maneuvering abilities of the vehicles. These distinctions result in some phenomena like vehicle creeping, which are absent in the homogeneous traffic. Hence, this type of traffic can be referred to as ''heterogeneous disordered'' or ''mixed'' traffic. A review of the literature has shown that most of the studies in such traffic make use of the methods and concepts developed for homogeneous traffic. Very few studies have attempted to capture and understand the distinctive characteristics of the mixed traffic. The primary objective of this paper is to provide a review of the studies on various mixed traffic characteristics in developing economies, identify their limitations and provide guidelines for the future research. Also, a detailed methodology of the simulation process for the mixed traffic is given, reflecting the ''gap-filling'' rather than the conventional ''car-following'' behavior. A comparison of the past modeling approaches is also presented and the accuracy of their implementation is discussed.

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Section: Methods Based On Areas and Speeds Of Vehiclesmentioning

confidence: 94%

Section: Methods Based On Areas and Speeds Of Vehiclesmentioning

confidence: 99%

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Review of Studies on Mixed Traffic Flow: Perspective of Developing Economies

Kiran

Verma

2016

Transp. in Dev. Econ.

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“…The present study is further targeted to the estimation of capacity by developing speed-flow diagram. Among ten different driver behaviour parameters (CC0 to CC9) given in Wiedemann Model 99 only two of them namely; CC0 (standstill distance) and CC1 (time headway) are found to be significant as the traffic flow reaches to capacity (Mehar et al, 2013). These are the two parameters which govern the safety distance between the vehicles in the simulation model.…”

Section: Calibration Of Vissimmentioning

confidence: 99%

“…Park and Kwak (2011) also evaluated the results of calibration and validation procedure by comparing the distribution of simulation output with field data. Mehar et al, (2013) investigated the sensitivity of different driving behaviour parameters given in VISSIM model on capacity. Authors identified two parameters in the Widemann 99 model as CC0 and CC1 affecting the simulated capacity significantly.…”

Section: Studies Based On Simulationmentioning

confidence: 99%