Multichannel queueing behaviour in urban bicycle traffic

The objective of this paper is to propose a method to analyse and describe cyclists’ behaviour at signalized intersections with specific focus on the multichannel (multi-lane) queue phenomenon. As we observed, cyclists form queues without a fixed-lane and FIFO discipline, for which the classical, car-oriented analytical approach becomes insufficient. Cyclists’ multichannel queueing behaviour is common and characterized by substantial degree of variability, especially in case of shorter queues which emerge regularly at cycle crossings. Although cyclist behaviour has been widely studied by transportation research community, their queueing behaviour picture is still incomplete. Namely, there is no method addressed to analyse the full scope of these phenomena and to quantify their impact on the cyclist queue performance. To bridge this gap, we introduce the technique to observe multichannel queues and report relevant observations, which we then complement with a methodological framework to analyse obtained results and provide a complete multichannel queue description. We video-record cyclists as they enqueue to one of multiple channels, form the queue and smoothly merge into a single lane again as the queue discharges. We apply the method to analyse results from a pilot study of 160 cyclists forming 50 queues in the city of Krakow, Poland. The proposed method allows us to analyse and quantify the observed queue performance and its characteristics: the number of channels, their emergence process, channel and queue lengths, discharge process with FIFO violations, starting and discharging times. Findings from pilot study reveal that both queue length and discharge times strongly depend on queue formation process. The contribution of this paper is the method to describe multichannel cyclist queueing behaviour, enriching current picture of bicycle flow and cyclists’ behaviour. Since the method has been developed on relatively short queues (up to 10 cyclists), findings included in this paper primarily refer to such queue sizes. Nonetheless, the method is formulated in a generic way, applicable also for longer bicycle queues. Possible practical implications are new estimates for queue lengths and discharge times - useful for bicycle infrastructure design and traffic engineering purposes

Investigating the Impact of Public Transport Service Disruptions upon Passenger Travel Behaviour—Results from Krakow City

Public transport (PT) service disruptions are common and unexpected events which often result in major impediment to passengers’ typical travel routines. However, attitudes and behavioural responses to unexpected PT disruptions are still not fully understood in state-of-the-art research. The objective of this study is to examine how PT users adapt their travel choices and what travel information sources they utilize once they encounter sudden PT service disruptions. To this end, we conduct a passenger survey among PT users in the city of Kraków (Poland), consisting of a series of stated- and revealed-preference questions. Results show that passengers’ reported choices during past PT disruptions mostly involve adjusting the current PT travel routine, exposing a certain bias with their stated choices (which tend to overestimate the probability of modal shifts). Factors influencing travel behaviour shifts include frequency and recency of PT disruption experience, as well as propensity to arrive on-time. With regards to travel information sources, staff announcement and personal experience play an important role in recognizing the emerging disruption, but real-time information (RTI) sources are the most useful in planning the onward journey afterwards. Based on these, we highlight the implications for future RTI policy during PT service disruptions; in particular, the provision of a reliable time estimate until normal service conditions are resumed. Such RTI content could foster passengers’ tendency to use PT services in uncertain conditions, especially as their stated wait time tolerance often matches the actual duration of PT disruptions

Should I stay or should I board? Willingness to wait with real-time crowding information in urban public transport

Overcrowding is a major phenomenon affecting travel experience in urban public transport, whose negative impacts can be potentially mitigated with real-time crowding information (RTCI) on public transport vehicle departures. In this study, we investigate the willingness to wait (WTW) with instantaneous RTCI to avoid the in-vehicle (over)crowding the passenger faces, focusing specifically on urban crowding context (i.e. bus and tram systems). We conduct a stated-preference survey in Krakow (Poland), where we examine the choice probability between boarding now a more crowded vehicle vs. waiting at the stop for a less-crowded PT departure, and estimate a series of discrete choice models.Results show that 50–70% of respondents consider skipping a first departure which is excessively overcrowded and 10–30% would skip a vehicle with moderate standing crowding on-board. Acceptable waiting times typically range between 2 and 13 min, depending on crowding level and propensity to arrive on-time, but may even exceed 20 min in individual cases. These findings indicate that RTCI can induce a substantial WTW, affecting travel behaviour. We discuss its implications for mitigating service disruptions and demand management policies, including prospective support for public transport recovery in the aftermath of covid-19 crisis

Estimating Macroscopic Volume Delay Functions with the Traffic Density Derived from Measured Speeds and Flows

This paper proposes a new method to estimate the macroscopic volume delay function (VDF) from the point speed-flow measures. Contrary to typical VDF estimation methods it allows estimating speeds also for hypercritical traffic conditions, when both speeds and flow drop due to congestion (high density of traffic flow). We employ the well-known hydrodynamic relation of fundamental diagram to derive the so-called quasi-density from measured time-mean speeds and flows. This allows formulating the VDF estimation problem with a speed being monotonically decreasing function of quasi-density with a shape resembling the typical VDF like BPR. This way we can use the actually observed speeds and propose the macroscopic VDF realistically reproducing actual speeds also for hypercritical conditions. The proposed method is illustrated with half-year measurements from the induction loop system in city of Warsaw, which measured traffic flows and instantaneous speeds of over 5 million vehicles. Although the proposed method does not overcome the fundamental limitations of static macroscopic traffic models, which cannot represent dynamic traffic phenomena like queue, spillback, wave propagation, capacity drop, and so forth, we managed to improve the VDF goodness-of-fit from R2 of 27% to 72% most importantly also for hypercritical conditions. Thanks to this traffic congestion in macroscopic traffic models can be reproduced more realistically in line with empirical observations

Estimating Macroscopic Volume Delay Functions with the Traffic Density Derived from Measured Speeds and Flows

This paper proposes a new method to estimate the macroscopic volume delay function (VDF) from the point speed-flow measures. Contrary to typical VDF estimation methods it allows estimating speeds also for hypercritical traffic conditions, when both speeds and flow drop due to congestion (high density of traffic flow). We employ the well-known hydrodynamic relation of fundamental diagram to derive the so-called quasi-density from measured time-mean speeds and flows. This allows formulating the VDF estimation problem with a speed being monotonically decreasing function of quasi-density with a shape resembling the typical VDF like BPR. This way we can use the actually observed speeds and propose the macroscopic VDF realistically reproducing actual speeds also for hypercritical conditions. The proposed method is illustrated with half-year measurements from the induction loop system in city of Warsaw, which measured traffic flows and instantaneous speeds of over 5 million vehicles. Although the proposed method does not overcome the fundamental limitations of static macroscopic traffic models, which cannot represent dynamic traffic phenomena like queue, spillback, wave propagation, capacity drop, and so forth, we managed to improve the VDF goodness-of-fit from R2 of 27% to 72% most importantly also for hypercritical conditions. Thanks to this traffic congestion in macroscopic traffic models can be reproduced more realistically in line with empirical observations

Changes in commuters travel behaviour after introducing highquality regional railway services

Introduction of new public transport services or improvement of existing ones change trip patterns as well as"br" generate new trips. Scale of both, mode shift and induced trips, is often difficult to predict. It happens especially"br" when introduced services was not available before or quality change is significant. This kind of situation happened"br" in Małopolska region (Poland) after development of regional rapid railway connections. Based on revealed"br" preferences survey among new railway service passengers authors investigated dimension of mode shift and"br" induced trips. In particular trip length distribution was analysed. Key findings shown that new, fast and high quality"br" railway connection attracted passengers from other modes of transport and new passengers as well. Moreover trip"br" length distribution has not changed significantly, however essentials savings of travel time and cost were shown

Investigation of Instantaneous Effects of Real-time Crowding Information (RTCI) Availability upon Urban Public Transport System Performance: Results from a Simulation-based Case Study

The purpose of this study would be to analyse the implications of providing real-time crowding information (RTCI) on instantaneous (current) crowding levels of public transport (PT) services to travelers – and more specifically, to investigate the output RTCI impact for the on-going PT system performance, based on simulation works on a case study (city-level) network model. In recent years, an increasing emphasis has been put on development of various travel demand management tools and especially advanced traveler information systems (ATIS), which aim to overcome problems associated with ever growing passenger congestion in urban transport systems - and thus improve the overall travel experience, reliability and quality of service of the PT system. One of key ATIS developments has witnessed the widespread introduction of real-time information (RTI) systems [3], which provide passengers with information on current travel times of public transport services, waiting times at stops etc. Likewise, a further extension of these systems is highly feasible within the framework of modern-day ITS systems, as passenger flow data collected from various sources – APC and AFC systems, smart-card ticketing systems etc. – can be then utilized to inform travelers about the current passenger flows, i.e. real-time loading levels of public transport vehicles (the so-called RTCI system). However, this also indicates a substantial research gap as (to the best of our knowledge) there is still a fairly limited amount of relevant studies, with just individual sources having investigated the effects of RTCI provision in terms of simulation approach [2], [5] or survey analysis [6], [9]. Moreover, practical implementation of such systems in PT networks is yet (to this date) confined to limited-scale deployment, often on pilot (trial) basis. Consequently, little is known about the potential effectiveness of RTCI systems and their implications both on demand (passengers’) side or supply (operators’ side)

Modelling the effects of real-time crowding information in urban public transport systems

Public transport (PT) overcrowding is a notorious problem in urban transport networks. Its negative effects upon travel experience can be potentially addressed by disseminating real-time crowding information (RTCI) to passengers. However, impacts of RTCI provision in urban PT networks remain largely unknown. This study aims to contribute by developing an extended dynamic PT simulation model that enables a thorough analysis of instantaneous RTCI consequences. In the model, RTCI is generated and disseminated across the network, and then utilised in passengers’ sequential en-route choices. A case-study demonstration of the RTCI algorithm on urban PT network model of Kraków (Poland) shows that instantaneous RTCI has the potential to improve passengers’ travel experience, although it is also susceptible to inaccuracy. RTCI provision can yield total travel utility improvements of 3% in typical PM peak-hour, with reduced impacts of the worst overcrowding effects (in terms of denied-boarding and in-vehicle travel disutility in overcrowded conditions) of 30%

Lewis–Mogridge Points: A Nonarbitrary Method to Include Induced Traffic in Cost-Benefit Analyses

We propose a new method to estimate benefits of road network improvements, which allows to include the induced demand without arbitrary assumptions. Instead of estimating induced demand (which is nontrivial and hardly possible in practice), we search for demand induction where initial benefits are mitigated to zero. Such approach allows to formulate a dual measure of benefit, covering both the potential benefits and the likelihood of consuming them by the induced traffic. We first estimate benefits of road network improvement assuming that traffic demand is fixed. Consequently, we find demand model configurations at which the benefits of the new investment become null, i.e., all the initial benefits are consumed by the traffic demand growth. We call such states of induced demand the Lewis–Mogridge points of the analysed improvement. We select the most probable of such points and use it to calculate the proposed novel indicator μ, for which the initial benefits (obtained under a fixed-demand assumption) are multiplied with a demand increase rate needed to consume them. We believe that such measure allows to include the critical phenomena of induced traffic and, at the same time, to overcome problems associated with reliable estimation of induced demand. As we illustrate with the case of two alternative road improvement schemes in Kraków, Poland, the proposed method allows to estimate maximal threshold of induced traffic and to select scenario more resilient to induced traffic

Mitigating bus bunching with real-time crowding information

A common problem in public transport systems is bus bunching, characterized by a negative feedback loop between service headways, number of boarding passengers and dwell times. In this study, we examine whether providing real-time crowding information (RTCI) at the stop regarding the two next vehicle departures can stimulate passengers to wait for a less-crowded departure, and thus alleviate the bunching effect. To this end, we leverage on results from own stated-preference survey and develop a boarding choice model. The model accounts for the presence of RTCI and is implemented within dynamic public transport simulation framework. Application to the case-study model of a major bus corridor in Warsaw (Poland) reveals that RTCI can induce a significant probability (30–70%) of intentionally skipping an overcrowded bus and waiting for a later departure instead. This behaviour, in turn, results in significantly lower vehicle headway and load variations, without deteriorations in total waiting utility. Overall, journey experience improves by 6%, and crucially—the prevalence of denial-of-boarding and excessive on-board overcrowding is substantially reduced, by ca. 40%. Results of our study indicate that the willingness to wait induced by RTCI can be a potential demand management strategy in counteracting bunching, with benefits already attainable at limited RTCI response rates.Transport and Plannin