A multi-path progression model for synchronization of arterial traffic signals

To contend with congestion and spillback on commuting arterials, serving as connectors between freeway and surface-street flows, this paper presents three multi-path progression models to offer progression bands for multiple critical path-flows contributing to the high volume in each arterial link. The first proposed model is a direct extension of MAXBAND under a predetermined phasing plan, but using the path-flow data to yield the progression bands. The second model further takes the phase sequence at each intersection as a decision variable, and concurrently optimizes the signal plans with offsets for the entire arterial. Due to the competing nature of multi-path progression flows over the same green duration, the third model is proposed with a function to automatically select the optimal number of paths in their bandwidths maximization process. The results of extensive simulation studies have shown that the proposed models outperform conventional design methods, such as MAXBAND or TRANSYT, especially for those arterials with multiple heavy path-flows. The research results from this study have also reflected the need to collect more traffic pattern data such as major path-flow volumes, in addition to the typical intersection volume counts.     

A dynamic shortest path algorithm using multi‐step ahead link travel time prediction

In this paper, a multi‐step ahead prediction algorithm of link travel speeds has been developed using a Kalman filtering technique in order to calculate a dynamic shortest path. The one‐step and the multi‐step ahead link travel time prediction models for the calculation of the dynamic shortest path have been applied to the directed test network that is composed of 16 nodes: 3 entrance nodes, 2 exit nodes and 11 internal nodes. Time‐varying traffic conditions such as flows and travel time data for the test network have been generated using the CORSIM model. The results show that the multi‐step ahead algorithm is compared more favorably for searching the dynamic shortest time path than the other algorithm.     

A two-stage taxi scheduling strategy at airports with multiple independent runways

Long taxiing times at large airports lead to fuel wastage and dissatisfied passengers. This paper investigates the 4D taxi scheduling problem in airports to minimize the taxiing time. We propose an iterative two-stage scheduling strategy. In the first stage, all aircrafts in a current schedule period are assigned initial 4D routes. In the second stage, landing aircrafts that are unavailable to fulfil their initially assigned routes are rescheduled using a shortest path algorithm based approach. In this paper, the simplified model used in most existing literature, that depicts a runway as having a single entrance and a single exit or even sets only one point to represent both of them has been discarded. Instead, we model the fact that a runway has multiple entrance and exit points and use an emerging concept—Runway Exit Availability (REA)—to measure the probability of clearing a runway from a specific exit during a specific time interval so that the taxiing scheduling model can be much higher approximation to the practical operation. An integer programming (IP) model factoring REA is proposed for assigning 4D taxiing routes in the first stage. The IP model covers most practical constraints faced in airport taxiing procedures, such as the rear-end/head-on conflict constraint, runway-crossing constraint, take-off/landing separation constraint, and taxi-out constraint. Besides, flight holding patterns at intersections are much more realistically modelled. Furthermore, to accelerate the solving process of the IP model, we have refined the formulation using several tricks. Simulation results by proposed scheduling approach for operations at the Beijing Capital International Airport (PEK) for an entire day demonstrate a surprising taxiing time saving against the empirical data and simulation results based on a strategy similar to what being used now days while showing an acceptable running time of our approach, which supports that our approach may help in real operation in the future.     

Deciding whether and how to improve statewide travel demand models based on transportation planning application needs

Many states in the USA have developed statewide travel demand models for transportation planning at the state level and along intercity corridors. Travel demand models at mega-region and provincial levels are also widely used in Europe and Asia. With modern transportation planning applications requiring enhanced model capabilities, many states are considering improving their four-step statewide demand models. This paper synthesizes representative statewide models developed with traditional four-step, advanced four-step, and integrated micro-simulation methods. The focus of this synthesis study is as much on model applications and data requirements as on modeling methods. An incremental model improvement approach toward advanced statewide models is recommended. Review findings also suggest model improvement activities should be justified by planning application needs. For statewide model improvement plans to be successful and financially sustainable, the return on model improvement investment needs to be demonstrated by timely applications that rely on improved model capabilities.     

A stochastic model for highway traffic

A nonlinear model for unidirectional flow of heavy traffic on a two-lane highway is considered. Features such as entrance, exit and lane transfer with time-dependent parameters are incorporated into the model, with the result that a number of previous models employed in the study of traffic flow become special cases of ours. Using the method of system-size expansion, an asymptotic analysis of the problem, including the time evolution of both deterministic and stochastic aspects of the traffic system, is carried out. In addition, a scheme for obtaining the moments of the probability distribution for systems of finite size is developed and a comparison is made with the exact results appropriate to a particular model. The agreement between the two sets of results turns out to be remarkably good.     

Methods of dropping auxiliary lanes at freeway weaving segments

Auxiliary lanes connecting freeway entrance and exit ramps provide additional space for entering and exiting vehicles to change lanes. The method of dropping auxiliary lanes is critical in the design of freeway auxiliary lanes. This study investigates the performance of different methods of dropping auxiliary lanes. Case studies were conducted at two selected freeway segments with successive entrance or exit ramps in the City of Houston. Traffic simulation analysis results of these two case studies show that additional operational benefits can be achieved by extending an auxiliary lane beyond the freeway weaving segment. The study also found that if the weaving segment is followed by an entrance/exit ramp and this ramp has high traffic volume, it can be less operationally favorable to extend and terminate the auxiliary lane at this entrance/exit ramp location. Instead, dropping the auxiliary lane before this entrance/exit ramp represents a more operationally effective option.     

A microscopic simulation model for merging control on a dedicated-lane automated highway system

The automated highway systems (AHS) are not designed as stand-alone transportation facilities. Drivers will by necessity drive from their origins to the AHS entrance, and from the AHS exit to their final destinations. Therefore, the AHS will affect other transportation facilities, and should be integrated with all other facilities in the transportation system. Interfaces create much of the congestion for today’s transportation systems. Likewise, AHS interfaces may cause a similar problem, due to either AHS interactions with conventional systems or internal limitations from AHS merging capabilities. If these problems exist, either the AHS or the conventional road network cannot function properly. Consequently, the system as a whole may break down and the AHS could potentially become a detriment to the overall transportation system.Clearly, not enough is known about the automated merging process to determine what conditions would lead to congestion at interface points. The current macroscopic analysis techniques assume parameters that are not applicable to an AHS, and no detailed AHS merging models have been developed and validated. This paper addresses the interface problem between an AHS, and conventional roadway. Specifically, it presents a microscopic simulation model for one scenario of the automated merging maneuver. The results of the model show that for low flows and conventional highway speeds, an one-lane AHS merging section with a dedicated automated entrance ramp has many similar characteristics as a two-lane conventional freeway with or without fixed-time ramp metering. However, when the conventional freeway starts to “break down” near its capacity, the AHS continues to perform with little delay. The model also validates that the minimum ramp length requirements are a function of the merging vehicle’s speed, the mainline vehicles’ speed, and the acceleration and deceleration rates of the merging vehicle.     

上海轨道交通人民广场站出入口与周边道路相关因素分析

人民广场站是目前上海轨道交通网络中大型换乘枢纽之一,具有出入口数量多,出入口功能差异性大等特点。详细介绍了车站各出入口的设置情况,以及与周边道路、客流等关系,分析研究了各出入口的客流特征,可为今后类似换乘枢纽出入口的设计提供借鉴。     

Simulation model for the analysis of complex traffic weaving problems

A simulation modeling approach has been developed to analyze a complex traffic weaving problem. It is presented, discussed, and demonstrated on an actual dual purpose weaving area that is closely followed by an entrance‐exit junction. Specifically, the model identifies problem areas in the system, assists the traffic engineer in the formulation of feasible solution strategies, and analyzes the effectiveness of alternative strategies. The simulation model is not presented as a panacea to weaving analysis rather as an interesting and unique approach that has the potential to analyze a wide variety of weaving patterns. The primary conclusion of the paper is that the model can be a valuable tool for analysis of certain types of traffic congestion problems.     

Dynamic travel mode searching and switching analysis considering hidden model preference and behavioral decision processes

This paper proposes a conceptual framework to model the travel mode searching and switching dynamics. The proposed approach is structurally different from existing mode choice models in the way that a non-homogeneous hidden Markov model (HMM) has been constructed and estimated to model the dynamic mode srching process. In the proposed model, each hidden state represents the latent modal preference of each traveler. The empirical application suggests that the states can be interpreted as car loving and carpool/transit loving, respectively. At each time period, transitions between the states are functions of time-varying covariates such as travel time and travel cost of the habitual modes. The level-of-service (LOS) changes are believed to have an enduring impact by shifting travelers to a different state. While longitudinal data is not readily available, the paper develops an easy-to-implement memory-recall survey to collect required process data for the empirical estimation. Bayesian estimation and Markov chain Monte Carlo method have been applied to implement full Bayesian inference. As demonstrated in the paper, the estimated HMM is reasonably sensitive to mode-specific LOS changes and can capture individual and system dynamics. Once applied with travel demand and/or traffic simulation models, the proposed model can describe time-dependent multimodal behavior responses to various planning/policy stimuli.     

Real‐time identification of traffic conditions prone to injury and non‐injury crashes on freeways using genetic programming

This study applied the genetic programming (GP) model to identify traffic conditions prone to injury and property‐damage‐only (PDO) crashes in different traffic states on freeways. It was found that the traffic conditions prone to injury and PDO crashes can be classified into a high‐speed and a low‐speed traffic state. The random forest (RF) analyses were conducted to identify the contributing factors to injury and PDO crashes in these two traffic states. Four separate GP models were then developed to link the risks of injury and PDO crashes in two traffic states to the variables selected by the RF. An overall GP model was also developed for the combined dataset. It was found that the separate GP models that considered different traffic states and crash severity provided better predictive performance than the overall model, and the traffic flow variables that affected injury and PDO crashes were quite different across different traffic states. The proposed GP models were also compared with the traditional logistic regression models. The results suggested that the GP models outperformed the logistic regression models in terms of the prediction accuracy. More specifically, the GP models increased the prediction accuracy of injury crashes by 10.7% and 8.0% in the low‐speed and high‐speed traffic states. For PDO crashes, the GP models increased the prediction accuracy by 7.4% and 6.0% in the low‐speed and high‐speed traffic states. Copyright © 2016 John Wiley & Sons, Ltd.     

Assessment of spatial transferability of an activity-based model,TASHA

Spatial transferability has been recognized as a useful validation test for travel demand models. To date, however, transferability of activity-based models has not been frequently assessed. This paper assesses the spatial transferability of an activity-based model, TASHA (Travel Activity Scheduler for Household Agents), which has been developed for the Greater Toronto Area (GTA), Canada. TASHA has been transferred to the context of the Island of Montreal, Canada using the 2003 Origin–Destination (O–D) travel survey and the 2001 Canadian Census. It generates daily schedules of activities (individual and joint) for each individual in this region. The modelled activity attributes (frequency, start time, duration and distance) from TASHA and observed attributes from the 2003 O–D travel survey are compared for five different activities (i.e. work, school, shopping, other, and return to home). At the aggregate level, TASHA provides quite reasonable outcomes (in some cases – better results than for the Toronto Area) for all four attributes for work, school and return to home activities with few exceptions (for instance, school start time). The model outcomes are also promising for shopping frequency and start times; however, TASHA provides larger differences for average shopping durations and distances. Only the forecasts for all four attributes for the ‘other’ activity type differ greatly with the observed attributes for the Montreal Island. These large differences most likely indicate the differences in behaviour between the Montreal Island and the Toronto Area. In general, we conclude that re-estimation of model parameters and the use of local activity attribute distributions (frequency, start time and duration) is a desirable step in the transfer of the TASHA model from one context to another.     

A competing Markov model for cracking prediction on civil structures

Cracks on the surface of civil structures (e.g. pavement sections, concrete structures) progress in several formations and under different deterioration mechanisms. In monitoring practice, it is often that cracking type with its worst damage level is selected as a representative condition state, while other cracking types and their damage levels are neglected in records, remaining as hidden information. Therefore, the practice in monitoring has a potential to conceal with a bias selection process, which possibly result in not optimal intervention strategies. In overcoming these problems, our paper presents a non-homogeneous Markov hazard model, with competing hazard rates. Cracking condition states are classified in three types (longitudinal crack, horizontal crack, and alligator crack), with three respective damage levels. The dynamic selection of cracking condition states are undergone a competing process of cracking types and damage levels. We apply a numerical solution using Bayesian estimation and Markov Chain Monte Carlo method to solve the problem of high-order integration of complete likelihood function. An empirical study on a data-set of Japanese pavement system is presented to demonstrate the applicability and contribution of the model.     

An analysis of household vehicle holding durations considering intended holding durations

Household vehicle holding durations are examined in this study using panel data. Panel data enable the observation of changes in household vehicle holdings in discrete time periods. If the data set contains retrospective recall data which offer information on the types and the occurrence time points of the transactions since the last survey, direct observation of the transaction process along a continuous time axis is possible. Furthermore, if the data contain information on intentions for future transactions and actual outcomes of the intentions in later waves, the relationship between intended transactions and actual transactions can be observed. In this study, we develop models of actual vehicle holding durations and models of intended vehicle holding durations for the same set of vehicles. Comparing these two sets of models, the effects on household vehicle holding durations of changes in the household’s plans for vehicle holding and unexpected events can be inferred. To represent unaccounted associations between intended vehicle holding durations and actual vehicle holding durations, vehicle specific error components are introduced into the duration models. A non-parametric approach is adopted in model estimation using mass points, which requires no assumption on the distribution of the error components.     

Maximizing bus discharge flows from multi-berth stops by regulating exit maneuvers

Upon having loaded and unloaded their passengers, buses are often free to exit a multi-berth bus stop without delay. A bus need not wait to perform this exit maneuver, even if it requires circumventing one or more other buses that are still dwelling in the stop’s downstream berths. Yet, many jurisdictions impose restrictions on bus entry maneuvers into a stop to limit disruptions to cars and other buses. Buses are typically prohibited from entering a stop whenever this would require maneuvering around other buses still dwelling in upstream berths. An entering bus is instead required to wait in queue until the upstream berths are vacated.Analytical models are formulated to predict how bus discharge flows from busy, multi-berth stops are affected by allowing buses to freely exit, but not freely enter berths. These models apply when: a bus queue is always present at the stop’s entrance; buses depart the entry queue and enter the stop as per the restriction described above; and the stop is isolated from the effects of nearby traffic signals and other bus stops. We find that for these restricted-entry stops, bus-carrying capacities can often be improved by regulating the exit maneuvers as well. This turns out to be particularly true when the stop’s number of berths is large. Simulations show that these findings still hold when a stop is only moderately busy with entry queues that persist for much, but not all of the time. The simulations also indicate that removing any restrictions on bus exit maneuvers is almost always productive when stops are not busy, such that short entry queues form only on occasion, and only for short periods. We argue why certain simple policies for regulating exit maneuvers would likely enhance bus-stop discharge flows.     

A time-use investigation of shopping participation in three Canadian cities: is there evidence of social exclusion?

Increasing awareness and concern about the status of mobility-disadvantaged groups in society has given rise to a wide body of research that focuses on the social exclusion dimension of transportation. To date, much of the empirical work on this topic is mainly spatial in nature despite recent developments that call for the inclusion of time use analyses in social exclusion research. In this paper we attempt to fill this gap by estimating activity and trip durations to determine whether poverty, old age, or being a single parent results in time use patterns indicative of exclusion. Given the importance of shopping and using services for social inclusion objectives, these activities are the focus of this investigation. In terms of methods, use of a multiple equation approach allows for the estimation of the daily duration of shopping activities and trips while simultaneously controlling for daily durations of four broad categories of activities as well as their associated travel times. The results indicate: that being a senior citizen increases travel durations while decreasing shopping activity durations; that coming from a low income household decreases shopping activity durations; and single-parent status does not impact shopping activity durations when holding income and other activity durations constant. These results highlight the feasibility and challenges of time-use and activity analysis in social exclusion research.     

Optimal funding allocation strategies for safety improvements on urban intersections

Urban intersections crashes cause significant economic loss. The safety management process undertaken by most states in the United States is referred to as Highway Safety Improvement Program and consists of three standardized steps: (i) identification of critical crash locations, (ii) development of countermeasures, and (iii) resource allocation among identified crash locations. Often these three steps are undertaken independently, with limited detail of each step at the state planning agencies. The literature review underlines the importance of the third step, and the lack of sophisticated tools available to state planning agencies for leveraging information obtained from the first two steps. Further, non-strategic approaches and unavailability of methods for evaluating policies may lead to sub-optimal funding allocation. This paper overcomes these limitations and proposes multiple optimal resource allocation strategies for improvements at urban intersections that maximize safety benefits, under budget and policy constraints. Proposed policy measures based on benefits maximization (economic competitiveness), equitable allocation (equity), and relaxation of mutually exclusiveness (multiple alternatives at one location) produce significantly different alternative and fund allocation. The proposed models are applied to selected intersections in four counties of southeast Michigan. Results reinforce the applicability of the strategies/policies and tools developed in this paper for safety project funding allocation on critical urban intersections.     

Motorway crash duration and its determinants: do durations vary across motorways?

Traffic congestion has been a growing issue in many metropolitan areas during recent years, which necessitates the identification of its key contributors and development of sustainable strategies to help decrease its adverse impacts on traffic networks. Road incidents generally and crashes specifically have been acknowledged as the cause of a large proportion of travel delays in urban areas and account for 25% to 60% of traffic congestion on motorways. Identifying the critical determinants of travel delays has been of significant importance to the incident management systems, which constantly collect and store the incident duration data. This study investigates the individual and simultaneous differential effects of the relevant determinants on motorway crash duration probabilities. In particular, it applies parametric Accelerated Failure Time (AFT) hazard‐based models to develop in‐depth insights into how the crash‐specific characteristic and the associated temporal and infrastructural determinants impact the duration. AFT models with both fixed and random parameters have been calibrated on one year of traffic crash records from two major Australian motorways in South East Queensland, and the differential effects of determinants on crash survival functions have been studied on these two motorways individually. A comprehensive spectrum of commonly used parametric fixed parameter AFT models, including generalized gamma and generalized F families, has been compared with random parameter AFT structures in terms of goodness of fit to the duration data, and as a result, the random parameter Weibull AFT model has been selected as the most appropriate model. Significant determinants of motorway crash duration included traffic diversion requirement, crash injury type, number and type of vehicles involved in a crash, day of week and time of day, towing support requirement and damage to the infrastructure. A major finding of this research is that the motorways under study are significantly different in terms of crash durations; such that motorway 1 exhibits durations that are on average 19% shorter compared with the durations on motorway 2. The differential effects of explanatory variables on crash durations are also different on the two motorways. The detailed presented analysis confirms that looking at the motorway network as a whole, neglecting the individual differences between roads, can lead to erroneous interpretations of duration and inefficient strategies for mitigating travel delays along a particular motorway.     

An analysis of the effects of French vehicle inspection program and grant for scrappage on household vehicle transaction

The French government has implemented a periodical vehicle inspection program, which aims at maintaining proper functioning of the vehicle and ensuring the emissions control systems installed on the vehicle work properly. Also, an incentive program for scrapping old vehicles was introduced in 1994 through 1996 to promote the replacement of those vehicles with higher emissions by newer vehicles with lower emissions. A hazard-based duration model of household vehicle transaction behavior has been developed in this study to examine the effects of the inspection program and the grant for scrappage on vehicle transaction timing. The model is developed as a competing risks model assuming the following three types of competing risks: replacing one of the vehicles in the household fleet, disposing of one vehicle in the fleet, and acquiring one vehicle to add to the fleet. The empirical analysis is carried out using the panel data of French households' vehicle ownership from 1984 to 1998, obtained by the panel survey called Parc-Auto, which has been conducted by a French marketing firm, SOFRES, since 1976. The long panel observation period facilitates the introduction of macro-economic indicators into the model, enabling the analysis to distinguish the effects of policy measures from macro-economic factors. The empirical results indicate that the expected vehicle holding duration becomes 1.3 years longer under the inspection program than before the program commenced, given that the vehicle is replaced by another vehicle at the end of the holding duration; and that the conditional probability of replacing a vehicle aged 10 years and over becomes 1.2 times higher, and the average holding duration becomes shorter by 3.3 years, when the grant for scrappage is available.     

Competing risk mixture model and text analysis for sequential incident duration prediction

Predicting the duration of traffic incidents sequentially during the incident clearance period is helpful in deploying efficient measures and minimizing traffic congestion related to such incidents. This study proposes a competing risk mixture hazard-based model to analyze the effect of various factors on traffic incident duration and predict the duration sequentially. First, topic modeling, a text analysis technique, is used to process the textual features of the traffic incident to extract time-dependent topics. Given four specific clearance methods and the uncertainty of these methods when used during traffic incidents, the proposed mixture model uses the multinomial logistic model and parametric hazard-based model to assess the influence of covariates on the probability of clearance methods and on the duration of the incident. Subsequently, the performance of estimated mixture model in sequentially predicting the incident duration is compared with that of the non-mixture model. The prediction results show that the presented mixture model outperforms the non-mixture model.