Dwell Time Analysis and Priority Granting for Bus Service in Budapest

Public transport has always been a structuring factor in urban development and form. Buses, which are one of the essential public services, do not require expensive infrastructure, can be introduced quickly and run as frequently as necessary to meet the demand. Budapest is known by the diversity of its transportation modes and their high frequency, nevertheless, it still faces traffic congestion issues. Thus, the priority granting for the buses is essential to minimize the travel time delays.This research analysis investigates the bus service's situation on the chosen corridor based on personal data collection in peak-hours at the bus stops and on-board using GPS tracker. This research aims to study the dwelling bus’s impact on car delays and targets to optimize the situation by implementing bus priority. The iterative models coded with Octave calculates the vehicles’ delays function of the arrival time and dwelling time of the bus and analyses all scenarios depending on the time the bus is ready to leave the stop and adjusting it by either holding the bus at bus stops or allowing an immediate departure with speed adjustment or green light extension. The objective of the proposed priority model is not only to minimize the bus delays, but also the average vehicle delays on the different branches of the intersection. The prioritization system takes into consideration the non-violation of the maximum holding time, maximum green time extension and maximum red time in the intersection’s branches where the bus stop exists

Estimating Uncertainty of Bus Arrival Times and Passenger Occupancies

Travel time reliability and the availability of seating and boarding space are important indicators of bus service quality and strongly influence users’ satisfaction and attitudes towards bus transit systems. With Automated Vehicle Location (AVL) and Automated Passenger Counter (APC) units becoming common on buses, some agencies have begun to provide real-time bus location and passenger occupancy information as a means to improve perceived transit reliability. Travel time prediction models have also been established based on AVL and APC data. However, existing travel time prediction models fail to provide an indication of the uncertainty associated with these estimates. This can cause a false sense of precision, which can lead to experiences associated with unreliable service. Furthermore, no existing models are available to predict individual bus occupancies at downstream stops to help travelers understand if there will be space available to board. The purpose of this project was to develop modeling frameworks to predict travel times (and associated uncertainties) as well as individual bus passenger occupancies. For travel times, accelerated failure-time survival models were used to predict the entire distribution of travel times expected. The survival models were found to be just as accurate as models developed using traditional linear regression techniques. However, the survival models were found to have smaller variances associated with predictions. For passenger occupancies, linear and count regression models were compared. The linear regression models were found to outperform count regression models, perhaps due to the additive nature of the passenger boarding process. Various modeling frameworks were tested and the best frameworks were identified for predictions at near stops (within five stops downstream) and far stops (further than eight stops). Overall, these results can be integrated into existing real-time transit information systems to improve the quality of information provided to passengers

Optimization of headway, stops, and time points considering stochastic bus arrivals

With the capability to transport a large number of passengers, public transit acts as an important role in congestion reduction and energy conservation. However, the quality of transit service, in terms of accessibility and reliability, significantly affects model choices of transit users. Unreliable service will cause extra wait time to passengers because of headway irregularity at stops, as well as extra recovery time built into schedule and additional cost to operators because of ineffective utilization of allocated resources. This study aims to optimize service planning and improve reliability for a fixed bus route, yielding maximum operator’s profit. Three models are developed to deal with different systems. Model I focuses on a feeder transit route with many-to-one demand patterns, which serves to prove the concept that headway variance has a significant influence on the operator profit and optimal stop/headway configuration. It optimizes stop spacing and headway for maximum operator’s profit under the consideration of demand elasticity. With a discrete modelling approach, Model II optimizes actual stop locations and dispatching headway for a conventional transit route with many-to-many demand patterns. It is applied for maximizing operator profit and improving service reliability considering elasticity of demand with respect to travel time. In the second model, the headway variance is formulated to take into account the interrelationship of link travel time variation and demand fluctuation over space and time. Model III is developed to optimize the number and locations of time points with a headway-based vehicle controlling approach. It integrates a simulation model and an optimization model with two objectives - minimizing average user cost and minimizing average operator cost. With the optimal result generated by Model II, the final model further enhances system performance in terms of headway regularity. Three case studies are conducted to test the applicability of the developed models in a real world bus route, whose demand distribution is adjusted to fit the data needs for each model. It is found that ignoring the impact of headway variance in service planning optimization leads to poor decision making (i.e., not cost-effective). The results show that the optimized headway and stops effectively improve operator’s profit and elevate system level of service in terms of reduced headway coefficient of variation at stops. Moreover, the developed models are flexible for both planning of a new bus route and modifying an existing bus route for better performance

Modelling bus bunching and holding control with vehicle overtaking and distributed passenger boarding behaviour

Headway fluctuation and bus bunching are commonly observed in transit operations, while holding control is a proven strategy to reduce bus bunching and improve service reliability. A transit operator would benefit from an accurate forecast of bus propagation in order to effectively control the system. To this end, we propose an ‘ad-hoc’ bus propagation model taking into account vehicle overtaking and distributed passenger boarding (DPB) behaviour. The latter represents the dynamic passenger queue swapping among buses when bunching at bus stops occurs and where bus capacity constraints are explicitly considered. The enhanced bus propagation model is used to build the simulation environment where different holding control strategies are tested. A quasi first-depart-first-hold (FDFH) rule is applied to the design of headway- and schedule-based holding control allowing for overtaking, with the objective to minimise the deviation from the targeted headway. The effects of control strategies are tested in an idealized bus route under different operational setting and in a real bus route in Guangzhou. We show that when the combined overtaking and queue-swapping behaviour are considered, the control strategies can achieve better headway regularity, less waiting time and less on-board travel time than their respective versions without overtaking and DPB. The benefit is even greater when travel time variability is higher and headway is smaller, suggesting that the control strategies are preferably deployed in high-frequency service

Modelling and management of multi-modal urban traffic

This research aims to model and manage bus regularity with consideration of the interaction between buses and surrounding traffic in an integrated multi-modal system. A parsimonious macroscopic simulation framework is first developed to estimate multi-modal road traffic conditions and the bus-traffic interaction based on the variational formulation of kinematic waves. The proposed simulation platform can capture shocks, dispersion of vehicle platoons, moving bottlenecks and traffic characteristics effectively with data collected from Central London. Second, different bus holding strategies are implemented on the proposed simulation platform in order to evaluate and compare their performance on improving bus service regularity and impact on transport system efficiency. It is shown that the two-way holding strategy performs the best in terms of regulating headway at low-traffic level. At high-traffic level, the two-way holding strategy and the forward holding strategy have a similar performance. However, the efficiency of buses and road traffic can be severely compromised due to bus holding at stops and the consequential delay on road traffic, especially under heavy traffic conditions. In order to mitigate these challenges, the third part of this thesis presents a range of signal-based bus holding strategies which are responsive to road traffic dynamics. Proposed control strategies are implemented on the proposed simulation platform to evaluate their performance. They are also compared with traditional stop-based holding strategies and numerical results suggest improved bus service regularity and transport efficiency