The main issue in Putrajaya’s bus services is related to time and cost. Optimal travel time require optimal routes and shortest distance. Minimizing travel time means minimizing operational cost. This paper reviews and evaluates the density of passengers and maximum number of passengers as parameters to obtain an optimum route. The mathematical model was utilized to analyze the passenger density with the improvements of the constraint to the number of passengers. The study based on data from intra-city bus services during off-peak hours. The main focus of this optimization is to compare the passenger density and the number of passengers as the parameters in decision making for bus routes. The result shows that the passenger density is better than the number passengers to assess bus routes.

Passenger waiting time is included in the estimated travel time. Waiting time will be unstable and unpredictable in estimation because of inconsistencies of bus arrival times at stops. These can result an unreliable of bus service. This paper examines the waiting time due to three factors; delay resulting from inaccuracies of bus departure time, delay during the process of boarding and alighting passengers and delay when the bus unable to maintain constant velocity because of saturated traffic flow. The research used the combination of mathematical model and Design Expert Research Methodology Surface (RSM) applications which has pivotal role in acquire optimum waiting time based on constraints delay between two arrival times at stop. The optimum waiting time obtained from the output design target in range 0-15 minutes were 4 minutes for route L01 and 5.87 minutes for L05. The estimated waiting time obtained from this research can be used as a key feature in the design of buses operating to minimize the delay and at the same time get the reliability of passengers.

Bus arrival time is very important to passengers, not only at the origin terminal but also at every stop. If there is no predicted arrival time at a stop, the headway designed should match the bus frequency at the stop. The uncertainty in bus arrival time can hinder the headway from matching the bus frequency at the stops. Moreover, lack of information on the service route and actual arrival times at stops leads to difficulty for passengers in planning their trips. Observation surveys were conducted to collect data on the problems of bus arrival frequency and uncertain arrival times at a selected stop with multiple routes during off-peak hours in Putrajaya Malaysia. This paper proposes a method to estimate arrival times at bus stops using the adaptive neuro fuzzy inference system (ANFIS) and several models are proposed to predict arrival times using MATLAB Curve Fitting Tool. All the proposed models exhibited RMSE close to 0 and R 2 close to 1.