CHAPTER ONE 1. 1 INTRODUCTION The at-grade intersection form over 90% of the road network in the nation’s highway system. It plays an important role in the road network, where traffic flows in different directions converge. It is imperative that where two or more roads meet, there is always a need to make a provision for intersections design in other to channel traffic into different streams. Due to several interaction that takes place between road users and traffic control systems, capacity of intersections are always much lower than that of their approach carriage way.
This often results into serious delay due to reduction in capacity. Report shows that the nation’s population has increased seriously from the last census conducted, so also is the population of resident of Akure metropolis. This, however, increased the vehicle ownership and traffic volume in the links has increased dramatically due to continuous high speed growth of her economy, which causes traffic congestions and often results into serious delay of the road users.
The transport infrastructure put in place in the city of Akure hasn’t been able to ameliorate traffic congestion in the city, especially at the city center. The improvement in the income of civil servant and the windfall arising from it to the private sector also has shown that there is rapid rate at which people bought vehicles. This has brought increase in vehicle within the state. With the increasing trend of vehicle, it is certain that the design volume of most intersections wouldn’t be able to cater for the present traffic situation especially during the peak periods of the day.
This constitute to the delay experience often at the city’s intersections. Intersections in this country are operated through traffic control signals or by traffic warden, but most intersection within the city of Akure is under the operation on traffic officers. These two forms of control systems are sometimes found to be inadequate and irrelevant during the peak hour of the day, especially when the traffic volume of the approach lane to an intersection is beyond the design traffic volume.
Inadequate traffic control system or improper channelization of traffic, however, sometimes creates more problems than they can solve. Today at most intersections, it is understood that unnecessary stops and delays lead to drivers discomfort particularly under extreme traffic condition, thereby increases travel time and fuel consumption rate. This is always as a result of insufficient capacity of these intersections and often led to drivers and pedestrian discomfort. This has caused many road users their precious time, as the adage says “Time is money”.
Civil servant and business executives are sometimes deprived access on time to their offices and businesses due to endless time mostly spent at the nation’s intersection. It has been observed that some intersections within the city, no longer accommodate the increased in volume of traffic especially during the peak period of the day in respect to delays and inadequate capacity experiences at locations such as Cathedral/Ondo road junction, Youth center junction and Owo /Ijapo road junction. It is imperative to know why users experience such delay and at times traffic jam.
This, therefore call for a research work to know how the traffic operations and the level of service on these intersection can be improve in other to enhance the standard of living of resident of Akure metropolis. 1. 2 OBJECTIVES OF THE STUDY The aim of this study is to evaluate the average delay of three major intersections based on local traffic conditions. The objectives of this study are as follow. 1. To determine the average daily traffic volume of these intersection 2. To estimate the capacity of each intersection 3. To measure the effectiveness of each intersection in other to estimate or determine their level of service 4.
To know the existing geometric features and their sizes in relation to capacity. 5. To know the traffic control systems and how it can be improved. 1. 3 JUSTIFICATION OF RESEARCH Since democratic government took place in the nation’s political system. The standard of living of public servant and their private counterpart has improved. The increment in their salary structure has influenced increase in the traffic volume of vehicle within the city of Akure. This makes road users to spend endless time before getting to their various destinations.
Despite the relocation of the central market to another location in the city of Akure, some arterial still experiences unbearable delay by road users, this is always as a result of reduction in capacity of the intersection. It prompts for a research work on study of delays on few of these intersections and how it can be alleviated. CHAPTER TWO 2. 1 LITERATURE REVIEW Traffic delays and queues are principal performance measures that enter into the determination of intersection level of service (LOS), in the evaluation of the adequacy of lanes, and in the estimation of fuel consumption and emissions.
Since numerous transport authorities decided that an acceptable LOS is one of the basic parameters to be fulfilled in signal control design, the obtained minimum delay being the foremost goal to the traffic engineers. Delays estimation at intersections has been extensively studied in the literature and several methods for estimating vehicle delay at intersections under traffic control system have been widely used. However, it seems that the exploration on the method for estimating the delay is still continuously conducted. This is may be due to the consideration of various variables which could affect the delays.
As an example, the 1994 Highway Capacity Manual (HCM) stated that the stopped delay can be multiplied by a factor of 1. 3 to obtain an approximate estimate of the total delay. Whereas several studies have found that this factor should be variable rather than just a constant value (Olszewski, 1993; Quiroga and Bullock, 1999; Mousa, 2002). The change of the primary factor for measuring the LOS at signalized intersection from stopped delay (HCM1994) to control delay (HCM1997 and 2000) also depicts the continuing improvement by incorporating current research findings.
Dion et al (2004) illustrated five delay models for intersection under traffic control system: deterministic queuing model, shock wave delay model, steady-state stochastic delay model, time-dependent stochastic delay model, and finally, microscopic simulation delay model. The time-dependent stochastic delay model have been proposed over the years and have been incorporated into a number of capacity guides, such as those from the United States (TRB 1994, 1997, 2000), Australia (Akcelik, 1981) and Canada (ITE, 1995).
Delay in the realm of signalized intersections is associated with the time lost to a vehicle and/or driver because of the operation of the signal and the geometric and traffic conditions present at the intersection (Click, 2003). While delay in the HCM 2000 context is defined as the difference between the travel time actually experienced and the reference travel time that would result during ideal conditions; in the absence of traffic control, in the absence of geometric delay, in the absence of any incidents, and when there are no other vehicles on the road.
There are several different types of delay that can be measured at an intersection, and each serves a different purpose to the transportation engineer. The signalized intersection capacity and LOS estimation procedures are built around the concept of average control delay per vehicle. Control delay is the portion of the total delay attributed to traffic signal operation for signalized intersections (TRB, 2000). Control delay (overall delay) can be categorized into deceleration delay, stopped delay and acceleration delay.
Stopped delay is easier to measure, while overall delay reflects better the efficiency of traffic signal operation (Olszewski, 1993). Typically, transportation professionals define stopped delay as the delay incurred when a vehicle is fully immobilized, while the delay incurred by a decelerating or accelerating vehicle is categorized as deceleration and acceleration delay, respectively. Various components of vehicular delay at signalized intersection including control delay used in the HCM (Quiroga and Bullock, 1999).
In the 2000 version of the HCM, control delay is comprised of initial deceleration delay, queue move-up time, stopped delay, and final acceleration delay, though in earlier versions it included only stopped delay. Besides the control delay, there is another type of delay which vehicles experienced at intersection under traffic control system. This type of delay is identified as geometric delay. Luttinen and Nevala (2002) define geometric delay as the time lost due to the intersection geometry. Geometric delays may be large for turning movements.
Total delay of a vehicle is the sum of control delay and geometric delay. On the other hand, the drivers’ perception and reaction time to the changes of the signal display at the beginning of the green interval and during yellow interval to mechanical constraints and to individual driver behavior also contribute to the traffic delay at signalized intersection. Husch and Albeck (2004) explain that during simulation process using SimTraffic micro simulation software, there are input parameters called as driver parameters.
These parameters involve yellow deceleration, yellow reaction time, green reaction time, headways and gap acceptance factor. All these driver parameters depend on driver type. Green reaction time is the amount of time it takes the driver to respond to a signal changing to green. More aggressive drivers will have a shorter reaction time to green lights. This value ranges from 0. 8 to 0. 2 seconds. While headways are the amount of time between vehicles drivers try to maintain. When traveling at 30 ft/s a vehicle with 1-second headway will try to maintain 30ft between it and the leading vehicle.
Gap acceptance factor is an adjustment to the approach gap times. This is the gap vehicles will accept at unsignalized intersections, for permitted right turns, and for left turns on red. These values range from 1. 15 to 0. 85 second. The higher values represent more conservative drivers (Husch and Albeck, 2004). 2. 2 DELAY MODEL IN HCM2000 After the release of the Highway Capacity Manual 1994, numerous researches have been undertaken to assess the changes that were made in the delay estimation model with respect to the 1985 version of the manual.
Using the 1994 HCM version of the equation, traffic engineers were unable to: a) discriminate between fixed time and actuated control operation; b) evaluate oversaturated intersections or variable-length analysis periods; c) evaluate intersections using variable demand profiles on the intersection approaches; d) consider the filtering and metering effects of upstream signals; and e) fully consider the effects of progression on delay (Troutbeck and Kittelson, 1998). Prevedouros and Koga (1996) compared the 1985 and 1994 delay models using field data.
In another research project, Akcelik (1996) extended the 1994 HCM delay progression factor to account for the prediction of queue length, queue clearance time, proportion of stopped vehicles in a queue, and queue move-up rate. Fambro and Rouphail (1997) proposed a generalized delay model that corrected some of the problems found in the 1994 HCM model and that is now the delay model found in the HCM 2000. In the HCM 2000, the average delay per vehicle for a lane group is given by Equations 1 to 4(TRB, 2000). d = d1 ? fpf + d2 + d3 ? r (1) with di=0. 5c [1-gc]2 [1-min(X, 1. 0). C] g (2) d2=900T [(X-1) +v(X-1)2 + 8K I X] cT (3) fpf= (1-P)f p 1-g (4) C Where: d = average overall delay per vehicle (seconds/vehicles), d1 = uniform delay (seconds/vehicles), 2 = incremental, or random, delay (seconds/vehicles), d3 = residual demand delay to account for over-saturation queues that may have existed before the analysis period (seconds/vehicles), PF = adjustment factor for the effect of the quality of progression in coordinated systems, C = traffic signal cycle time (seconds), g = effective green time for lane group (seconds), X = volume to capacity ratio of lane group, c = capacity of lane group (vehicles/hour), K = incremental delay factor dependent on signal controller setting (0. 50 for pretimed signals; vary between 0. 4 to 0. 50 for actuated controllers), I = upstream filtering/metering adjustment factor (1. 0 for an isolated intersection), T = evaluation time (hours), P = proportion of vehicles arriving during the green interval, fp = progression adjustment factor. In this delay model the residual delay components d3 make use of vehicles instead of passenger car units to quantify traffic flows. The period analysis T is reported in hours instead of minutes, but this change is reflected in the use of a different multiplication factor in each term involving the variable T.
In Equation 3, parameters k and I are introduced in the last term of the equation, and this term reduces to 0. 5 and 1. 0 when the values associated with pre-timed traffic signal control at an isolated intersection are used respectively. CHAPTER THREE PROJECT METHODOLOGY 3. 1 STUDY AREA Akure lies within 7° 15? north of the Equator and Longitude 5° 05? east of the Greenwich Meridian (See Figure 1). The area towards Ado-Ekiti and Idanre are hilly and studded with large granite formation, rising to 410 meters and 496 meters above sea level respectively.
Traffic survey and intersection reconnaissance survey will be carried out at three busy intersections in Akure, named Cathedral/Ondo road intersection, Youth center junction and Owo /Ijapo road intersection. 3. 2 TRAFFIC VOLUME STUDIES DATA COLLECTION Traffic volume count for left turning movement, right turning movement and through movement would be conducted on each of the approach lane at the intersection, using one person each for lane. Heavy vehicle would be separated from the light vehicles. This would be done in the AM and PM peak periods, between (7-9) AM, (12-2) PM and (4-6) PM.
The volume computed would be used to determine the capacity and volume/capacity ratio. 3. 3 DELAY STUDIES DATA COLLECTION Data on delays will be conducted according to the highway capacity manual, where two observers are sited at one approach of each intersection. The following tasks are performed by the two observers: •Observer 1 –Keeps track of the end of standing queues for each cycle by observing the last vehicle in each lane that stops due to the traffic control officer or device. This count includes vehicles that arrive on going but stop or approach within one car length of queued vehicles that have not yet started to move.
At intervals between 10 s to 20 s, the number of vehicles in queue is recorded on the field sheet. The regular intervals for these observations should be an integral divisor of the cycle length. Vehicles in queue are those that are included in the queue of stopping vehicles (as defined above) and have not yet exited the intersection. For through vehicles, “exiting the intersection” occurs when the rear wheels cross the STOP line; for turning vehicles, “exiting” occurs when the vehicle clears the opposing vehicular or pedestrian flow to which it must yield and begins to accelerate.
At the end of the survey period, vehicle-in-queue counts continue until all vehicles that entered the queue during the survey period have exited the intersection. •Observer 2 During the entire study period, separate counts are maintained of vehicles arriving during the survey period and of vehicles that stop one or more times during the survey period. Stopping vehicles are counted only once, regardless of how many times they stop. Data collected will be analyzed using the following equations in order to compute the total control delay, and to estimate the level of service.
TQ = 0. 9 (Is x ? Viq) VT TQ = average time-in-queue, s/veh Is = time interval between time-in-queue counts ?Viq = sum of all vehicle-in-queue counts during survey period, vehicle VT = total number of vehicles arriving during survey period, vehicle To make adjustment for acceleration/deceleration delay requires that two values be computed: •The average number of vehicles stopping per lane, per cycle, and •The proportion of vehicles arriving that actually stop group. V SLC = VSTOP Nc x NL FVS = VSTOP VT
V SLC = number of vehicles stopping per lane, per cycle, vehicle VSTOP = total count of stopping vehicles, vehicle Nc = number of cycles in the survey NL = number of lanes in the survey lane group FVS = fraction of vehicles stopping The final estimate of control delay can be calculated as follows d = TQ + (FVS x CF) The value of CF is a correction factor that is given at the table below Adjustment Factor for Acceleration/Deceleration Delays Free Flow Speed (mile/h)| | | < 7 vehs| 8 – 9 vehs| 20 – 30 vehs| lt; 37>37 – 45> 45| +5+7+9| +2+4+7| -1+2+5| CONTRIBUTION OF RESEARCH 1. This research can assist traffic engineer and road planner in future intersections design. 2. Guideline on how the quality of movement at intersection can be improved. 3. Traffic volume trend observed can be inferred to any future intersection designs. 4. This can help to generate timing for signal control system. REFRENCES Akcelik, R. (1996), Progression Factor for Queue Length and Other Queue-Related Statistics, Transportation Research Record 1555, 99-104 Dion, F. t al (2004), Comparison of Delay Estimates at Under-Saturated and Over-Saturated Pre-Timed Signalized Intersections, Transportation Research Part B 38 (2004), 99–122. Fambro, D. , and N. Rouphail (1997), Generalized Delay Model for Signalized Intersections and Arterials, Transportation Research Record 1572, 112-121. Mousa, R. M. (2002), Analysis and Modeling of Measured Delays at Isolated Signalized Intersections, Journal of Transportation Engineering Vol. 128 No. 4. Quiroga, C. A. , and Bullock, D. (1999), Measured Control Delay at Signalized Intersections, Journal of Transportation Engineering Vol. 25 No. 4. Olszewski, P. (1993), Overall Delay, Stopped Delay, and Stops at Signalized Intersections, Journal of Transportation Engineering Vol. 119 No. 6. Prevedouros, P. D. , and Koga, C. A. (1996), Comparison of 1985 and 1994 Signalized Intersection Delay Estimates, ITE Journal Vol. 66 No. 7. Troutbeck, R. and Kittelson, W. (1998), An Overview of the 1997 HCM Update, ITE Journal Vol. 68 No. 7. Click, M. (2003), Variables Affecting the Stopped to Control Delay at Signalized Intersection, TRB 2003 Annual Meeting.
Akcelik, R. et al (2002), aaSIDRA Traffic Model Reference Guide, Akcelik & Associates Pty Ltd, Australia. Husch, D. , and Albeck, J. (2004), SimTraffic Version 6, Trafficware, California. Luttinen, R. , and Nevala, R. (2002), Capacity and Level of Service of Finnish Signalized Intersections, Finnra Reports 25/2002. Transportation Research Board (2000), Highway Capacity Manual 2000, National Research Council, Washington D. C. Wallace, C. E. et al (1998), TRANSYT-7F Version 9, McTrans University of Florida, Florida.