Average Headway Research Articles

Space–time collision avoidance and train dynamics constraints-driven optimal control for heterogeneous heavy-haul trains platoon operation considering air brake delay

The potential of heavy-haul train platoon operation technology in improving railway freight capacity is increasingly recognised, with extensive trial research currently underway. This study firstly utilising longitudinal train dynamics devised a space–time collaborative collision avoidance model for trainsets, accounting for air brake delay. Secondly, an air brake application strategy was proposed, focusing on collision avoidance and managing speeds on steep ramps. Subsequently, a constraint-driven optimal control scheme tailored for heavy-haul train platooning operations within an open railway environment was developed, which simulates train platooning amidst real-world dynamic traffic flow scenarios, offering a global perspective on railway network operations. Finally, we comprehensively evaluate the impact of line conditions on key platoon control parameters based on realistic railway operation scenarios. Findings show that constraint-driven optimal control, integrating train dynamics and space–time collaborative collision avoidance, effectively replicates the dynamic traits of train platoons. The consideration of air braking delays is crucial due to heterogeneous train formations and steep ramps, which can easily cause collisions. Moreover, on real-world railway lines, the average headway of heavy-haul trains weighing 10,000 tons and below can be compressed to 99.82 s when operating in platoons, significantly enhancing transportation capacity compared to existing semi-automatic blocking systems.

Car-following model based on spatial expectation effect in connected vehicle environment: modeling, stability analysis and identification

In driving situations, if drivers have advanced access to downstream traffic conditions ahead of time, they may modify their driving behavior accordingly. This proactive approach can help reduce frequent acceleration and deceleration of vehicles and minimize traffic congestion. This paper considers the average headway of downstream vehicles to predict the traffic conditions of downstream roads. Based on the full velocity difference (FVD) model, we propose a car-following model that incorporates spatial expectation effect (SEFVD). Firstly, a linear stability analysis is performed on the SEFVD model, and the results indicate that the critical value of the SEFVD model is relatively small, and the stabilization region increases gradually with the number of vehicles downstream. Secondly, employing perturbation amplitudes on a virtual circular road, a numerical simulation of the SEFVD model is carried out and compared with the FVD model. The results demonstrate that the SEFVD model has the ability to suppress the formation of traffic oscillations and stabilize vehicle formation more quickly. Simulation results for the 11 cars starting from a traffic signal indicate that the delay time and kinematic wave speed of the SEFVD model are within reasonable limits. To evaluate the changes in energy use, we also carried out energy consumption experiments. The experimental findings show that the SEFVD model uses less energy compared to the FVD model. Finally, the parameters of the models are calibrated and verified by using NGSIM data. The total calibration error of the SEFVD model (m = 2) decreases by 42.97% compared to the FVD model, and the total validation error decreases by 29.3%. The results show that the proposed model can fit the actual data well, and the fitting error is smaller.

Urban rail transit network topology evolutionary stage has influence on rail ridership: Insights from linear mixed-effects models with heterogeneity in variances

Determining the impact of the evolutionary stage (ES) of urban rail transit (URT) network topology on daily ridership (DR) can be beneficial for policymakers when analyzing recent stagnated ridership in some cities. This paper used city-level data from 26 Chinese cities from 2013 to 2019 to investigate this. Eleven variables comprising socioeconomic attributes (population density and the average wage of employees), the availability of other transit modes (the number of taxis, the number of private cars, the bus network length, and the street network length), service-related attributes (the number of trains in operation, the average headway during peak period, the opened days, and rail fare), and a network topological characteristic (the average path length) were introduced as covariates. In addition, city class was introduced as a grouping variable to capture the unobserved characteristics of the investigated cities. Two linear mixed-effects models (M1 and M2) were developed, with an interaction term between city class and ES being introduced in M2. The variances were allowed to vary to account for the heterogeneity of the predictor, which improved the overall fit of the models. The estimation results reveal a significant positive within-subject effect of ES on DR in both models, which varied according to city class. This implies that for each city, improving ES increased DR and the scale of the increase in DR is associated with the city’s class. However, there is no evidence of a relationship between ES and DR across different cities. In addition, the heterogeneity in the variance indicates that underestimating the variances of the effects could lead to inaccurate conclusions. The results of this study can help transit agencies in mastering ridership and assessing the designs of URT network topology.

An agent-based urban simulation to assess the system-wide, spatial, and modal impacts of the deployment of an automated vehicle corridor with mixed traffic: a case study in New York City

Self-driving car companies aim to offer hands-off journeys with Automated Vehicle (AV) technology, but public skepticism persists on safety aspects of AVs. A proposed solution involves creating dedicated AV corridors with traffic control and interruptions. Realistically, full penetration of AVs is unlikely to occur in the near future while mixed traffic of AVs with human driven vehicles is more likely. This study applies this concept to a hypothetical scenario in NYC, proposing an AV corridor from the Staten Island Expressway to the Brooklyn Battery Tunnel. The goal is to assess the network-wide impacts of a limited AV deployment from a multi-modal perspective. The NYC transportation system is modeled using MATSim, an open-source agent-based modeling platform. Although each traveler is treated as an agent making multi-modal trip making decisions, it does not model microscopic behavior of cars. Thus, the modeling approach for AVs has to be a macroscopic one, where average headways are reduced on the AV (with mixed traffic) corridor portion of the overall network based on a link capacity relationship adopted from a study on Advanced Cruise-Assist Highway Systems [1]. Two reduced headway scenarios are simulated in this MATSim NYC model, 1.1 and .85 second headways. Results indicate that Scenario B (1.1-second headway) is preferable over Scenario A (0.85 second headway), mitigating potential congestion on connectors, especially on Victory Boulevard in Staten Island. This study suggests implementing Scenario B for a smoother corridor-wide introduction of AVs to avoid congestion on connectors of the AV corridor to the rest of the NYC network.

Unlocking potential capacity benefits of electric vehicles (EVs) with adaptive cruise control (ACC)

Today’s mainstream vehicles are partially automated via Adaptive Cruise Control (ACC) that relies on on-board sensors to automatically adjust speed to maintain a safe following distance. Contrary to expectations for automated vehicles, ACC may reduce capacity at bottlenecks because its delayed response and limited initial acceleration during queue discharge could increase the average headway. Fortunately, EV’s unique powertrain characteristics such as instantaneous torque and regenerative braking could allow ACC to adopt shorter headways and accelerate more swiftly to maintain shorter headways during queue discharge, therefore reverse the negative impact on capacity. This has been verified in a series of field experiments, which demonstrate that EVs with ACC could potentially achieve a capacity as high as 2,931 veh/hr/lane in steady-state conditions, and it can be sustained in non-steady-state conditions where speeds fluctuate and queues form.

Buffer Time Optimization in the Function of Timetable Stability

Timetable stability depends on the regularity of trains. Any deviation from the planned timetable leads to its instability. Railway network characteristics determine the capacities of the transport service. Depending on the capacity calculation method, time components are added to the minimum headway to ensure timetable stability. The UIC 405 method is simple and can be used on all railways. The disadvantage is that the calculations are based on average data. According to the method, the minimum headway consists of the time of the average headway interval, additional time and the buffer time. The additional time is precisely defined by the number of APB sections, while the buffer time is in the average value. When creating the timetable, the goal is optimal utilisation of the infrastructure. If the headway is too long, the capacity is not used, and if it is too short, timetable instability will ensue. Instead of averaging, this work calculates a buffer time that depends on the ratio of the travel time of the previous and the following trains. In this way, the headway is optimised and the calculation of the UIC 405 method is improved.

V2V‐enabled cooperative adaptive cruise control strategy for improving driving safety and travel efficiency of semi‐automated vehicle fleet

AbstractAlthough highly automated vehicle fleets have committed a safe and efficient traffic flow, the next few years are likely the human‐driven vehicles (HDV) and intelligent vehicles (IV) mixed in large‐scale traffic network, where the interaction of HDVs with IVs will become more frequent. In this study, the authors investigate the traffic flow performance in a widespread of V2V environment deployed for all types of HDVs and IVs, levelled from L0 to L5. Based on this assumption, the vehicle movements and operations are collected and assembled into a V2X BSM dataset, and to any vehicle in fleet, the sequential movements and driving behaviours of the vehicle ahead can be predicted in the short term and considered as the input to cooperative adaptive cruise control (CACC) model of the controlled vehicle. The predicted motion of the vehicle ahead is applied to rolling optimization process of a given MPC framework, which calculates appropriate longitudinal operation for each car‐following vehicle and keeps optimal equilibrium state of the vehicle fleets in heterogeneous traffic flow. The experimental results showed that when the front vehicle generates random acceleration/deceleration in saturated and over saturated traffic state, in the car‐following case, the improved CACC controller maintains average car‐following distance at 20–40 m, the acceleration variation in the range [−0.1, 0.25], the gap error changed within [−10, 13], and controls the relative speed variation from −0.25 to 0.3 m/s, compared to an average headway of 20–140 m, acceleration variation in the range [−1.6, 0.65], gap error changed within [−21, 30], and a relative speed variation from −1.75 to 4.1 m/s by the traditional CACC controller. In the car‐in and car‐out cases, the vehicle controlled by the improved CACC controller had a travel displacement of 4050 m, a speed fluctuation interval of [18.7, 27.7], and an acceleration variation range of [−0.15, 0.2], while the vehicle controlled by the traditional MPC controller had a travel displacement of 3800 m, a speed fluctuation interval of [13.8,27.7] and an acceleration variation range of [−2.9, 0.6]. The improved CACC model can adapt more accurately and quickly to the maneouvre of vehicle ahead in V2V environment, which can effectively improve the capacity of heterogeneous traffic flow and the safety and comfort of driving.

A capacity model of signalized intersection with dedicated lanes for automated vehicles

ABSTRACT This paper proposes a capacity model to address the impact of automated dedicated lanes on the capacity of the signalized intersection. Firstly, the car-following modes in the mixed traffic flow are analyzed, and the influence of the setting of the automated dedicated lanes on the average headway is discussed. Secondly, a new capacity model with automated dedicated lanes is derived based on the classic capacity model. Then, a signalized intersection capacity model considering the automated dedicated lanes is further derived based on the saturation flow rate method. Finally, numerical simulation experiments are designed to discuss the key parameters on the traffic capacity of a signalized intersection. The results show that (i) the automated dedicated lanes are conducive to improving the traffic capacity; (ii) when the penetration rate of CAVs is less than 52%, the traffic capacity of the signalized intersection can be increased by nearly 1.25 times with the automated dedicated lanes. These findings can provide theoretical support for designing and optimizing signalized intersections in high levels (i.e. L3-L5) CAVs environments.

Impact of a First-In–First-Out Rule on the Merge of a Metro Line with a Junction

On a metro line with a junction, the merge of the line is a key point for the operation. This paper proposes a discrete event traffic model for a metro line with a junction. It is based on the line’s existing signaling system and determines trains’ departure times at all line nodes. Furthermore, the model estimates trains’ average headway and frequency. We apply our model to Paris metro line 13, which is currently not operated with a FIFO (first-in–first-out) rule on the merge. Thus, we seek to evaluate the effect of a FIFO rule on the nominal frequency. Compared to the current line operation, we also test the FIFO rule as a control strategy for daily disturbances. At the steady state, we show that the train frequency is maximized regardless of the distribution of the trains on the three parts of the line (the central part and two branches). Then, we study the train frequency in two disturbed situations that often occur on a metro line. We show that the FIFO rule reduces the impact of these disturbances in time and intensity. This research is motivated by the Paris metro operator, as the considered line is expected to be fully automated in the coming years. The operator wants to better understand the potential benefits of new operating rules and how operating protocols can improve the throughput and reliability of the system. This work is the first step in seeing frequency evolution on a line with a junction.

Resilience assessment and recovery of distribution network considering the influence of communication network

Aiming at the existing research ignoring the influence of communication network (CN) on resilience recovery strategy and evaluation of distribution network (DN), this paper will discuss the impact of communication network state on resilience recovery and construct corresponding quantitative evaluation indexes. Firstly, a comprehensive importance evaluation index is constructed for communication failures to determine the order of communication restoration in the failure area. Then the emergency communication recovery in the fault area is carried out by using 5G micro base station. Second, a quantitative evaluation index of the impact of communication on distribution network status recovery is established, considering the fluctuation of distributed power output and load. At the same time, thermal rating constraints are considered in load transfer and island formation, and the effects of static and dynamic thermal rating (DTR) on load recovery are compared. Considering the influence of emergency resource warehouse location on repair time during fault repair, the location of the resource warehouse is determined through spectral clustering to improve repair efficiency. At the same time, the average headway time is introduced to quantify the impact of extreme weather on traffic, modify the road resistance model, and then use the minimum road method to establish an emergency recovery strategy that considers the effects of extreme weather. The IEEE-123 node system is used as an example to verify the rationality of the resilience recovery strategy and the resilience assessment with communication impact.

Study of Passenger Perceptions for Public Transport During Covid 19 in Pekanbaru, Indonesia

During the COVID-19 pandemic, the manager of the Trans Metro Pekanbaru bus limited the number of passengers, operating hours, and rit. This policy follows the implementation of a transition period to the new normal in Pekanbaru City. With the enactment of this government policy, it has made an impact on the performance of Trans Metro Pekanbaru public transportation during the COVID-19 pandemic. This study analyzes the performance of Trans Metro Pekanbaru public transportation during the COVID-19 pandemic based on passenger operations and perceptions. The research methods used in this study are quantitative and qualitative. The data analysis used is the analysis of operational performance data during the COVID-19 period, and the analysis of passenger perceptions of service performance during the COVID-19 period. The results of this study show that the operational performance of Trans Metro Pekanbaru public transportation during the COVID-19 pandemic based on load factor, headway, and frequency indicators is considered poor. The average load factor value on all routes is below 70%, with the highest and lowest average values being 42% on the Ramayan – Pandau route and 2% on the Unilak – Palas Raya route. The average headway value on all routes is more than 10 minutes, with the highest average score being 63 minutes on the BRPS - UIN and Ramayana - Unilak routes. The average frequency value on all routes is only 1-3 vehicles/hour on average, with the highest average value being 5 vehicles/hour on the Ramayana - Pandau route. Based on passenger perceptions, it shows that passengers' perceptions of the quality of Trans Metro Pekanbaru public transportation services during the COVID-19 pandemic are considered good. This can be seen from the average score of respondents' assessment of 74.86%.

Road Performance Analysis Using PCE MC Value 0.17 on Rungkut Madya Road

Passenger Car Equivalent (PCE) is a conversion factor from various types of vehicles into passenger car units (pc). The PCE value in the 2014 Indonesian Road Capacity Guidelines called PKJI 2014 has a long period with the present. The purpose of this study is to prove that there is a change in current traffic characteristics with the traffic characteristics described in the PKJI 2014. To prove this, the study was conducted by comparing road performance using the PCE MC value according to the PKJI 2014 with research that has been done previously with the results of PCE MC using the modified average headway time method showing 0.17 results. The location of this research was carried out on the Rungkut Madya road (2/2 UD), Surabaya City, East Java, Indonesia. The results obtained from this study are the use of PCE MC according to the PKJI 2014, resulting in a theoretical speed value close to the actual speed value compared to using modified PCE MC. So that the calculation of the performance of the Rungkut Madya road or other roads with similar characteristics does not require modification of the PCE MC value.

Characterization of heavy vehicle headways in oversaturated interrupted conditions: Towards development of passenger car equivalency factors

Passenger car equivalency (PCE) of heavy trucks is often studied using filed observation and microscopic simulation models, especially for signalized intersections. While the Highway Capacity Manual recommends a single value regardless of the percentage of those heavy vehicles, literatures have shown that this equivalency is affected by different factors, including the trucks percentage. This research aims to examine the PCE under different level of traffic and heavy trucks demands. First, field measurements were collected and used to examine the characteristics of heavy vehicle and passenger car headways in oversaturated interrupted flow conditions. Field observations were then used to calibrate a microscopic simulation model. The model was then used to evaluate impact on headways of different levels of congestion and heavy vehicle percentages. Field results show that truck headways are about 2.3 those of passenger cars. The results also show that trucks are 1.5 more likely to be first in a queue when compared to passenger cars and 1.7 times more likely to be in first four vehicles in a standing queue. Passenger cars immediately behind trucks had longer than average headway. The simulation results suggest that PCE increases nonlinearly with increase in congestion level and with percentage of trucks; PCE's increase becomes less marked once sever congestion (stop-and-go with increasing queue lengths) conditions set in.

Impact of Deep Reinforcement Learning on Variable Speed Limit strategies in connected vehicles environments

The Variable Speed Limit (VSL) control is considered in the context of connected vehicles acting as moving sensors, while their obedience to speed limit is enforced by a mandatory Intelligent Speed Adaptation (ISA) system. The objective of this study is to extend spatially static differential VSL control by introducing novel VSL strategies that are based on spatially dynamic speed limit zones. The spatial configuration of speed limit zones requires a novel traffic state representation based on the set of consecutive matrices which encode each vehicle position and speed within the controlled motorway during the control time step. The actions for all proposed VSL strategies are computed by the same Deep Reinforcement Learning (DRL) approach based on the Deep Deterministic Policy Gradient (DDPG) architecture. The DDPG learning models contain integration of Convolution and Long Short-Term Memory (LSTM) known as ConvLSTM layers, along with the Convolution and Fully Connected layers. Thus, those models can learn complex spatio-temporal traffic dynamics based on proposed traffic state representation. The results show that proposed VSL strategies have achieved higher overall motorway throughput compared to one which is based on the static speed limit zones and baseline cases (no-control and Simple Proportional Speed Controller algorithm). Simultaneously, they achieved a minimal increase in the number of aggressive braking, while the average headway is increased. All proposed VSL control approaches are simulated and analyzed by using a synthetic microscopic motorway model and characteristic traffic scenario for urban motorways.

ANALISIS EFEKTIFITAS ANGKUTAN UMUM SUMBAWA - EMPANG, EMPANG - SUMBAWA

Increased demand for transportation services to support community activitiesSumbawaEmpang or vice versa, the number of public transportation from time to time continuesincrease without any limitation on the number of fleets, so that the transportation performance does notis known. To overcome this, the number of public transportation needs to be adjusted to theavailable passenger needs by analyzing the performance of public transport.The purpose of this study is to determine the effectiveness of public transport performance inthe Sumbawa Empang route and vice versa. The method used by doingapproach based on the Director General of Land Transportation NoSK.687/AJ.206/DRJD/2002 concerning the operational performance of public transport. Research resultThe load factor values ??obtained are 87.4% and 89.7% in the category of transportation performancequite good, the average frequency is 2 vehicles/hour, the average headway is 26 minutes and 23 minutes,service time is 9.30 hours and 8.30 hours in the category of poor transportation performance, andaverage speed 27.12 km/hour and 38.52 km/hour, travel time 4.05 hours and 2.57hours, the average waiting time is 13 minutes and 12 minutes in the category of good transportation performance.The results of data analysis show that the performance of Sumbawa Empang public transportation,There are four parameters of the Sumbawa Empang that do not reach the effective category that isdoes not meet and exceeds the standard, so there needs to be improvements from the Departmentcommunication.

Car Following Behaviours on Multilane Highways in Kuwait: A Case Study on Road 40 during Winter Season

The car following behaviour of a driver is the process of following the drivers to create an adjustment in the leading vehicle behaviour. In a condition, where the traffic volume is in a free-flowing situation, the selection of vehicles speed is typically limited by some factors such as weather conditions, lighting, and road geometry features. This study aims to investigate the effects of climates on driver’s car following behaviour and speed flow relationships for highways in Kuwait. The case study was conducted at Road 40 in Kuwait using RTMS Sx-300 device which is known as a radar device particularly used for monitoring traffic. The data was gathered between the periods from 29th December 2018 to 5th January 2019 within winter. MATLAB code was written to analyse and classify the gathered data. Then, the models were built using R-software. The study depicts that nearly 24.87% of the vehicles move between 60 km/h and 69 km/hour. Additionally, the vehicles were segmented according to their types i.e., Truck, Small, Medium and Large Sized Cars, in order to find the impact of following pattern on the vehicle average. It has been found that no significant association remains amidst the type of following pattern and the headway. Ultimately, a liner regression of data was developed to calculate a liner equation that shows the average headway as an element of speed for sixteen diverse following patterns. It has been recognized that an association could be supposed in medium-sized and small-sized vehicles. It has been observed that headway average could be placed in a linear equation for large, medium, and small as well as truck vehicles. It is worthy to denote that when data is bigger, the exactitude of a study enhances. Findings from each model of liner regression has more than 80% confidence level. The models of regression are deliberated as statistically significant where, the R (square) figures lies amidst 0.99 till 0.6. As per the findings, speed is the key influencing factor for headway value. The type of car does affect headway with drivers behind Heavy Good Vehicles and cars at the similar speed. According to the data, cars are identified to keep more headway when behind Heavy Good Vehicles in contrast with when behind other cars. These results will help the drivers to understand their behaviour that are associated with car crashes. Thus, increase road safety awareness and reduce traffic congestion in Kuwait.

Analysis of Spatial-Temporal Characteristics of Operations in Public Transport Networks Based on Multisource Data

Operational efficiency and stability are two critical aspects to measure bus systems. Influenced by many stochastic factors, buses always suffer from delay and bunching. Traditional studies focus on a single route and lack research on the systematic evaluation of bus network. In this paper, we propose a data-driven framework to analyze the efficiency and stability based on small granularity GPS trajectory data from the perspective of entire bus network. The IC card data and route data are used to extract the boarding passenger number and topological structure, respectively. The results show that the average headway of stations follows a lognormal distribution. Moreover, the distribution of arrival efficiency of stations is inhomogeneous and a small number of stations have large values. In addition, the relationships among average headway of stations, boarding passenger number, bus number, and complex network indicators are revealed. It is found that the average headway of station is negatively correlated with other indicators, which implies that complex network connections and more passenger flows could weaken the efficiency of bus operations. This paper provides a way to evaluate the operational performance of bus networks and could give help for monitoring and optimizing the daily operation of bus systems.

TRAIN HEADWAY OPTIMISATION USING VIRTUAL BLOCKS

Although the implementation of a new Automatic Train Protection (ATP) system increases the safety level, it also exerts some impact on the blocking time in block sections, and consequently, on the headway between trains. At the same time, ATP systems introduce a train positioning system based on odometry calculation and reporting back to the trackside system. This paper describes the concept of using virtual blocks based on train position reporting in the ATP system for purposes of non-occupancy determination. Virtual blocks can be used to reduce headways on railway lines without increasing the number of trackside signalling devices. Preliminary capacity assessment was performed to calculate the average headway depending on the signalling system with reference to a case study.

Analisa Kinerja Angkutan Umum Penumpang Perkotaan Ditinjau Dari Tingkat Pelayanan di Kota Tuban

Passenger public transportation in Tuban is one of the means of transport used by the community to meet the transport needs. Total fleet of public transport passengers registered and active operating as many as 40 vehicles, consisting of 30 units of passenger public transportation route A and 10 units of passenger public transportation route B, with a capacity of 12 passengers/vehicle. Passenger public transportation operates from 06.00 - 17.00 with the number of trips ranging from 7-8 trips/day every vehicle and can carry 9-10 passengers/trip every vehicle. The waiting time of passenger route A average of 3 minutes, and route B average of 9 minutes. The purpose of research is to determine the performance and productivity of the passenger public transportation of Tuban. The research using empirical methods to obtain information from observations in the field and these observations are presented in the form of data.The research results it is known that the performance and productivity of public transportation on route A and B. Route A has an average load factor of 81,39%, an average frequency of 20,97 vehicles/hour, an average headway of 2.88 minutes, an average travel time of 3,50 minutes/km, an average travel speed of 21,52 km/hour, and a productivity 7,62 trips/day-vehicle, with 74,45 passengers/day-vehicle. Route B has an average load factor of 78,19%, an average frequency of 7,15 vehicles/hour, an average headway of 8,93 minutes, an average travel time of 2,39 minutes/km, an average travel speed of 21,78 km/hour, and a productivity 7,74 trips/day-vehicle, with 72,6 passengers/day-vehicle..

The Performance Evaluation of Passenger Terminal: A Case Study of Type B Terminal in Sigli, Aceh Province

This research was conducted to determine the performance of the facilities and operations of the terminal using a direct survey method in the field. The primary data was collected by recording the number plate, entrance and departure time, number of passengers, vehicles entering and leaving, number of passengers getting on and off as well as the parking and vehicle number for visitors to the terminal. The survey was conducted for a duration of 9 hours daily starting from 8.00 am to 5.00 pm for a week. The results showed some facilities are not available at the terminal such as the administration room, supervisor room, platform, user fees, information room, first aid room, service room, restroom, warehouse, and spare parking space. Moreover, some facilities were observed not to be up to the required standard such as the office space, vehicle circulation, waiting room, and the toilet. Concerning the transportation characteristics, it was discovered that the highest number of passengers embarking and disembarking at the terminal per day was 8 and 4 while the highest number of those entering and leaving was recorded to be 361 and 367 respectively. Furthermore, the highest number of transportations was found to be 94 vehicles while the highest average headway time of arrival and departure was 8.81 minutes and 10.34 minutes and the values for load factor for arrival and departure of transportation was 38.33% and 39.47% respectively. The highest average waiting time was observed to be 7.62 minutes and the parking number and space requirements were found to be 72 for two-wheeled, 6 for three-wheeled, and 15 for four-wheeled vehicles with the highest average duration recorded to be 55.23, 56, and 58.58 minutes, respectively.