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American Journal of Engineering Research (AJER) Volume 2 Issue 12
  American Journal of Engineering Research (AJER) 2013 Page 235 American Journal of Engineering Research (AJER) e-ISSN : 2320-0847 p-ISSN : 2320-0936 Volume-02, Issue-12, pp-235-243 Research Paper Open Access Effect of Trotros on Saturation Flow at Selected Signalized Intersections on the 24 th  February Road, Kumasi, Ghana A. Obiri-Yeboah 1 *, A. S. Amoah 1 , P.C. Acquah 1   1 Civil Engineering Department, Kumasi Polytechnic, P. O. Box 854, Kumasi, Ghana Abstract:-    Trotros constitute a good proportion of urban traffic on the 24 th  February Road. The effect of the Trotros on saturation flow at signalized intersections could therefore be substantial. This research studies and analyses the effect of Trotros on the saturation flow at selected signalised intersections by collecting data along the route. A strong correlation was observed between the measured saturation flow using the headway method and the proportion of Trotros stopping per hour suggesting that their presence indeed impact on the capacity significantly and should therefore be considered in the capacity analysis of signalized intersections. The effect of Trotros on saturation flow rate was incorporated in the Highway Capacity Manual (HCM) model by comparing the field saturation flow to the adjusted saturation flow using the HCM model. Results show that saturation flow measured using the modified HCM equation is generally closer to observed saturation flow values. Keywords:    Capacity, Kumasi, Ghana, Saturation Flow, Traffic signals, Trotro I.   INTRODUCTION   The first traffic signal was installed in 1868 and it exploded. In 1918 the first three coloured light signals were again installed almost 50 years later and since then traffic signals are now used throughout the world, using the three colour signals of green, red and amber [1]. Traffic signals have since become the most common form of traffic control measure used in urban areas of most countries. It is a known fact that most developed countries have developed models based on their conditions, to analyse the capacity of signalised intersections. These models are best suited for their developed conditions where flow is homogeneous and lane discipline can be adhered to. In most developing countries like Ghana, Trotros are a major mode of transportation. The Trotro is a mini-van used as the main form of public transportation see Fig 1. In the city of Kumasi, Ghana, Trotros constitute about 40% of the total volume, 58% cars and the remaining 2% being trucks and others [2]. Because of this high proportion of Trotros, urban traffic characteristics in developing countries are significantly different from those of developed countries where the mini-vans do not operate as commercial vehicles. These Trotros create a nuisance in the traffic stream by dropping off and picking up passengers at unapproved locations, sometimes within the trafficked lanes thereby impeding the flow of other traffic upstream and creating a bottleneck within the system as is shown in Fig 2 below. Lane changing and overtaking manoeuvres by these Trotros are also not same as is in-built in the HCM capacity analysis model. It is therefore not possible to use their model directly since it has been developed under different driver and driving behaviours within similar traffic streams. Hence the need to modify these models to suit prevailing local conditions [3].  American Journal of Engineering Research (AJER) 2013 Page 236 Figure 1: Trotro loading at a Trotro station Figure 2: Trotro loading within the traffic stream during green indication Saturation flow rate is the basic parameter used to derive capacity of signalized intersections. It is calculated based on the minimum headway that the lane group can sustain across the stop line. Several attempts have been made previously to model saturation flow. Also, effect of approach volume and increasing percentage of bicycles on the saturation flow was studied. The study has shown that the saturation flow increases with the increase in approach volume. A field survey was conducted by [4] to find saturation flow and verify saturation flow and traffic volume adjustment factors used in various capacity manuals throughout the United States at Signalised intersections. Saturation flow headways for more than 20,000 observations were collected. Various factors like road geometry, traffic characteristics, and environmental and signal cycle lengths were considered to develop series of modified adjustment factors to determine modified saturation flow rates while calculating signalised intersection capacity [4]. The HCM (2000) [5] developed by Transportation Research Board (TRB), USA, includes a model (1) to calculate saturation flow rate considering the effect of various factors. It assigns an adjustment factor to each  parameter, which can be calculated using empirical formulas proposed in the manual. These adjustment factors are multiplied to the base saturation flow So,which is considered to be 1900 passenger cars (pc) per hour of green time per lane (pcphgpl) for signalised intersections, to obtain the saturation flow rate S of the intersection  American Journal of Engineering Research (AJER) 2013 Page 237 approach.  Rpb Lpb LT  RT  LU abb p g  HV wo  f   f   f   f   f   f   f   f   f   f  nf  S S     (1) Where, S = saturation flow rate for the lane group in vehicles per hour of green. S o  = ideal saturation flow rate in pcphgpl n = number of lanes in the lane group f  w  = adjustment factor for lane width f  HV  = adjustment factor for heavy vehicles f  g  = adjustment factor for approach grade f   p  = adjustment factor for parking characteristics f   bb  = adjustment factor for blocking effect of local buses that halt within the intersection area f  a  = adjustment factor for area type (Central Business District or other areas) f  LU  = adjustment factor for lane utilization f  RT  = adjustment factors for right-turns in the lane group f  LT  = adjustment factors for left-turns in the lane group. f  Lpb  = pedestrian-bicycle adjustment factor for left-turn movements; and f  Rpb  = pedestrian-bicycle adjustment factor for right-turn movements. As can be seen from (1), the effect of type of vehicles is considered only in terms of heavy vehicle adjustment factor which is obtained using the following equation: (2) Where %HV is the heavy vehicle percentage and ET is the passenger car equivalent of the corresponding heavy vehicle. The effect of the Trotros (loading and offloading within and around the trafficked lanes in the local setting) in mixed traffic conditions is not reflected. Attempts have been made to model the effects ofmixed traffic flow on saturation flow. A proposed probabilistic approach based on first-order second-moment method to estimate saturation flow at signalized intersections, under heterogeneous traffic conditions was investigated [6]. They make a comparison between the conventional method of estimating saturation flow i.e. headway method and their newly proposed probabilistic approach. The authors found probabilistic approach to be more appropriate for Indian condition. An analysis of the traffic characteristics and operations at signalised intersections of Dhaka, Bangladesh concluded that there is a need for different modelling approaches to analyse the saturation flow rates at the intersections of developing nations and the concept of passenger car unit (PCU), which is widely used as a signal design parameter, is not applicable in case of mixed traffic comprising of both motorised and non-motorised vehicles [7]. A trial new microscopic simulation technique, where a co-ordinate approach to modelling vehicle location is adopted has also been developed [8]. Based on these simulation results an equation was developed to estimate the saturation flow from the influencing variables like road width, turning proportion, percentage of heavy and non-motorised vehicles. A Simulation model HETEROSIM was  proposed by [9] to estimate the saturation flow rate of heterogeneous traffic. Simulation results were used to study the effect of road width on saturation flow measured in passenger car units (PCU) per unit width of road. An analysis of the impacts of different light-duty trucks (LDTs) [10] and [11] on the capacity of signalized intersections. Simple regression models have also been developed to estimate saturation flow at signalized intersections having heterogeneous traffic [12]. Summarizing the review of past literature, it is clear that the model proposed by [5] can be adapted to developing countries after necessary calibration. Considering this, the objective of the current research is to study the impact of the Trotro category of vehicles on saturation flow rate and to modify the HCM 2000 model to suit Ghanaian conditions incorporating the contribution of Trotros. II. METHODOLOGY 2.1 Site Selection and Description The signalized intersections were selected based on their accident and safety records in the past, the reducing impacts of other factors and levels of congestion associated with the selected intersections. Fig. 3 shows the map of Kumasi. Selected intersections are shown with a yellow circle and labelled accordingly. All selected intersections are located on the 24 th  February Road. Detailed descriptions are given in subsequent sub headings.  American Journal of Engineering Research (AJER) 2013 Page 238 Figure 3: Map Showing Location of Study Sites 2.1.1 24  th   February/Bomso Road Intersection (Bomso Intersection) The intersection with Bomso and 24 th  February roads is signalised and it is about 550 meters west of the KNUST junction. The intersection has four (4) legs with one (1) approach/entry and exit lanes on each leg of the minor roads, (Bomso/Ayigya roads), and two (2) approach/entry and exit lanes on the 24th February road. It is the intersection of a Principal arterial and Collector roads, namely:    24th February Road  –   Principal Arterial    Bomso Road  –   Collector Road    Ayigya Road  –   Collector Road On the approach from Adum there is a lay-bye where Trotros and taxis stop for passengers. The average lane width is 3.62m, median of 2.0m and the terrain is relatively flat. Roadside friction is mainly attributable to street hawking and transit activity on the two lay-byes on the approach from and exit to Adum. Traffic composition consists of 58% cars, 37% medium buses (Trotros) and 5% trucks. The layout is shown in Fig 4. TO BOMSOTO AYIGYA TO TECH TO ADUM N L              A              Y             B              Y             E                Figure 4: General Layout of Bomso Signalized Intersection 2.1.2 24  th   February/Eastern Bypass Intersection (Anloga Intersection) The Anloga intersection is a signalised intersection comprising three (3) principal arterials. It is about 2.6 km west of the KNUST junction. The intersection has four (4) legs with the following configuration:    East/West approaches - 24th February road, having two (2) approach through and exit lanes     North-East approach - Okomfo Anokye road, having one (1) approach through lane and two (2) exit lanes
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