Influential vectors in fuel consumption by an urban bus operator: Bus route,driver behavior or vehicle type?

Energy costs account for an important share of the total costs of urban and suburban bus operators. The purpose of this paper is to expand empirical research on bus transit operation costs and identify the key factors that influence bus energy efficiency of the overall bus fleet of one operator and aid to the management of its resources.We estimate a set of multivariate regression models, using cross-section dataset of 488 bus drivers operating over 92 days in 2010, in 87 routes with different bus typologies, of a transit company operating in the Lisbon’s Metropolitan Area (LMA), Rodoviária de Lisboa, S.A.Our results confirm the existence of influential variables regarding energy efficiency and these are mainly: vehicle type, commercial speed, road grades over 5% and bus routes; and to a lesser extent driving events such as: sudden longitudinal decelerations and excessive engine rotation. The methodology proved to be useful for the bus operator as a decision-support tool for efficiency optimization purpose at the company level.     

Analytical and simulation approaches to understand combined effects of transit signal priority and road-space priority measures

Transit signal priority (TSP) may be combined with road-space priority (RSP) measures to increase its effectiveness. Previous studies have investigated the combination of TSP and RSP measures, such as TSP with dedicated bus lanes (DBLs) and TSP with queue jump lanes (QJLs). However, in these studies, combined effects are usually not compared with separate effects of each measure. In addition, there is no comprehensive study dedicated to understanding combined effects of TSP and RSP measures. It remains unclear whether combining TSP and RSP measures creates an additive effect where the combined effect of TSP and RSP measures is equal to the sum of their separate effects. The existence of such an additive effect would suggest considerable benefits from combining TSP and RSP measures. This paper explores combined effects of TSP and RSP measures, including TSP with DBLs and TSP with QJLs. Analytical results based on time-space diagrams indicate that at an intersection level, the combined effect on bus delay savings is smaller than the additive effect if there is no nearside bus stop and the traffic condition in the base case is under-saturated or near-saturated. With a near-side bus stop, the combined effect on bus delay savings at an intersection level can be better than the additive effect (or over-additive effect), depending on dwell time, distance from the bus stop to the stop line, traffic demand, and cycle length. In addition, analytical results suggest that at an arterial level, the combined effect on bus delay savings can be the over-additive effect with suitable signal offsets. These results are confirmed by a micro-simulation case study. Combined effects on arterial and side-street traffic delays are also discussed.     

Understanding the impacts of a combination of service improvement strategies on bus running time and passenger’s perception

Transit agencies implement many strategies in order to provide an attractive transportation service. This article aims to evaluate the impacts of implementing a combination of strategies, designed to improve the bus transit service, on running time and passenger satisfaction. These strategies include using smart card fare collection, introducing limited-stop bus service, implementing reserved bus lanes, using articulated buses, and implementing transit signal priority (TSP). This study uses stop-level data collected from the Société de transport de Montréal (STM)’s automatic vehicle location (AVL) and automatic passenger count (APC) systems, in Montréal, Canada. The combination of these strategies has lead to a 10.5% decline in running time along the limited stop service compared to the regular service. The regular route running time has increased by 1% on average compared to the initial time period. The study also shows that riders are generally satisfied with the service improvements. They tend to overestimate the savings associated with the implementation of this combination of strategies by 3.5-6.0 min and by 2.5-4.1 min for both the regular route and the limited stop service, respectively. This study helps transit planners and policy makers to better understand the effects of implementing a combination of strategies to improve running time and passenger’s perception of these changes in service.     

User perspectives in public transport timetable optimisation

The present paper deals with timetable optimisation from the perspective of minimising the waiting time experienced by passengers when transferring either to or from a bus. Due to its inherent complexity, this bi-level minimisation problem is extremely difficult to solve mathematically, since timetable optimisation is a non-linear non-convex mixed integer problem, with passenger flows defined by the route choice model, whereas the route choice model is a non-linear non-continuous mapping of the timetable. Therefore, a heuristic solution approach is developed in this paper, based on the idea of varying and optimising the offset of the bus lines. Varying the offset for a bus line impacts the waiting time passengers experience at any transfer stop on the bus line.In the bi-level timetable optimisation problem, the lower level is a transit assignment calculation yielding passengers’ route choice. This is used as weight when minimising waiting time by applying a Tabu Search algorithm to adapt the offset values for bus lines. The updated timetable then serves as input in the following transit assignment calculation. The process continues until convergence.The heuristic solution approach was applied on the large-scale public transport network in Denmark. The timetable optimisation approach yielded a yearly reduction in weighted waiting time equivalent to approximately 45 million Danish kroner (9 million USD).     

Intermodal Transit System Coordination

In urban areas where transit demand is widely spread, passengers may be served by an intermodal transit system, consisting of a rail transit line (or a bus rapid transit route) and a number of feeder routes connecting at different transfer stations. In such a system, passengers may need one or more transfers to complete their journey. Therefore, scheduling vehicles operating in the system with special attention to reduce transfer time can contribute significantly to service quality improvements. Schedule synchronization may significantly reduce transfer delays at transfer stations where various routes interconnect. Since vehicle arrivals are stochastic, slack time allowances in vehicle schedules may be desirable to reduce the probability of missed connections. An objective total cost function, including supplier and user costs, is formulated for optimizing the coordination of a general intermodal transit network. A four-stage procedure is developed for determining the optimal coordination status among routes at every transfer station. Considering stochastic feeder vehicle arrivals at transfer stations, the slack times of coordinated routes are optimized, by balancing the savings from transfer delays and additional cost from slack delays and operating costs. The model thus developed is used to optimize the coordination of an intermodal transit network, while the impact of a range of factors on coordination (e.g., demand, standard deviation of vehicle arrival times, etc) is examined.     

Using Focus and NomiNal Group Techniques for a Better Understanding of the Transit Disadvantaged Needs

The research presented in this paper explores the context, method, and value of focus group research in transit needs assessments. Group participatory research can generate data that are not easily obtained by other methods. The paper focuses on lessons from three Nebraska communities whose transit disadvantaged rely on community-based paratransit services. Because of the size of the paratransit population and the inability to control who showed up to the focus group sessions, a modified group research protocol was adopted in order to garner information from whomever attended the session. The population parameters and the number of people at the meetings were anticipated by the researchers and mitigated by incorporating nominal group techniques. Research findings from the focus group sessions are discussed paying particular attention to the candid and policy-specific comments made by the focus group participants. The paper concludes with an application of focus group research in transit planning.     

Passenger waiting time and information acquisition using automatic vehicle location for verification

Bus riders utilize a variety of information media to learn how to travel to their destinations and to learn when they should arrive at bus stops. As part of the OCTA (Orange County Transit Authority) Transit Probe evaluation, 1199 passengers were surveyed to measure relationships between information acquisition and waiting time. A unique aspect of the survey was that some of the data could be correlated with automatic‐vehicle‐location (AVL) measurements of bus lateness at stops. Insights are provided as to the types of information riders acquire based on the nature of the trip and demographic characteristics. Insights are also provided as to factors affecting perceived waiting time. We found age group, whether a person needs to arrive at a destination by a specific time, primary language, and whether the person is a first‐time user of the bus line to be significant causal factors.     

Traffic noise studies in a tropical environment

This paper reports upon a survey of traffic noise annoyance in three residential districts of Trinidad, West Indies. Householder perceptions were solicited by means of a questionnaire survey and direct measurements of traffic noise levels were taken. The results were compared with surveys elsewhere. It was concluded that household status had little effect on annoyance perception, that at L₁₀ levels greater than 70 dB(A) at a dwelling facade the noise level is unacceptable. L₁₀ levels less than 65 dB(A) at the building facade are not perceived as annoying in the environment considered.     

Continuous approximation for skip-stop operation in rail transit

Operating speed of a transit corridor is a key characteristic and has many consequences on its performance. It is generally accepted that an increased operating speed for a given fleet leads to reduced operating costs (per kilometer), travel and waiting times (three changes that can be computed precisely), an improved comfort and level of service, which can attract new passengers who are diverted from automobile (items harder to estimate precisely). That is why several operation schemes which aim to increase the operating speed are studied in the literature, such as deadheading, express services, and stop skipping.A novel category of solutions to this problem for one-way single-track rail transit is to perform accelerated transit operations with fixed stopping schedules. The concept is quite simple: as the time required for stopping at each station is an important part of travel time, reducing it would be a great achievement. Particular operations that take advantage of this idea already exist. This paper focuses on one of them: the skip-stop operation for rail transit lines using a single one-way track. It consists in defining three types of stations: AB stations where all the trains stop, and A and B stations where only half of the trains stop (stations type A and B are allocated interchangeably). This mode of operation is already described in the literature (Vuchic, 1973, Vuchic, 1976, Vuchic, 2005) and has been successfully implemented in the Metro system of Santiago, Chile.This work tackles the problem with a continuous approximation approach. The problem is described with a set of geographically dependent continuous parameters like the density of stations for a given line. Cost functions are built for a traditional (all-stop) operation and for skip-stop operation as described above. A simple example is presented to support this discussion. Finally, a discussion about the type of scenarios in which skip-stop operations are more beneficial is presented.     

Evaluating the effects of bus design on passenger flow: Is agent-based simulation a feasible approach?

In this paper, we propose an agent-based simulation approach that is capable of simulating the flow of passengers on board buses and at bus stops. The intention is that it will be applied during vehicle development to analyze how vehicle design affects passenger flow, and thus also how it affects system performance such as dwell time. In turn, this could aid the developers in making design decisions early in the development process. Besides introducing the simulation tool itself, the paper explores the realism of the data generated by the tool. A number of passenger flow experiments featuring a full-scale bus mockup and 50 participants were carried out. The setup of these experiments mirrored a number of ‘bus journeys’ (regarding vehicle design, number of passengers boarding/alighting at each stop and so on) that had previously been simulated using the simulation tool. When the data from the simulations were compared with the data from the passenger flow experiments, it could be concluded that the tool is indeed able to generate realistic passenger flows, although with some errors when a large number of passengers board/alight. The simulated dwell times were rationally affected by the tested bus layout aspects. It was concluded that the tool makes it possible to evaluate how variations in bus layouts affect passenger flow, providing data of sufficiently high quality to be useful in early phases of vehicle design.