Proposed collision warning system for right-turning vehicles at two-way stop-controlled rural intersections

At two-way stop-controlled (TWSC) rural intersections, a right-turning driver who is departing the minor road may select an improper gap and subsequently may be involved in a rear-end collision with another vehicle approaching on the rightmost lane on the major road. This paper provides perceptual framework and algorithm design of a proposed infrastructure-based collision warning system that has the potential to aid unprotected right-turning drivers at TWSC rural intersections. The proposed system utilizes a radar sensor that measures the location, speed, and acceleration of the approaching vehicle on the major road. Based on these measurements, the system’s algorithm determines if there will be any potential conflict between the approaching and the turning vehicles and warns the driver of the latter vehicle if such a conflict is found. The algorithm is based on realistic acceleration profile of the turning vehicle to estimate its acceleration rates at different times so that the system can accurately estimate the time and distance needed for the departing vehicle to accelerate to the same speed as for the approaching vehicle. That realistic acceleration profile is established using actual experimental data collected by a Global Positioning System (GPS) data logger device that was used to record the positions and instantaneous speeds of different right-turning vehicles at 1-s intervals. The algorithm also gives consideration to the time needed by the driver of the departing vehicle to perceive the message displayed by the system and react to it (to start departure) where it was found that 95% of drivers have a perception–reaction time of 1.89 s or less. A methodology is also illustrated to select the maximum measurement errors suggested for the detectors in measuring the locations of the approaching vehicle on the major road where it was found that the accuracy of the system significantly deteriorates if the errors in measuring the distance and the azimuth angle exceed 0.1 m and 0.2°, respectively. An application example is provided to illustrate the algorithm used by the proposed system.     

An application-oriented model of passenger waiting time based on bus departure time intervals

This paper develops an application-oriented model to estimate waiting times as a function of bus departure time intervals. Bus stops are classified into Type A and B depending on whether they are connected with urban rail transit systems. Distributions of passenger arrival rates are analyzed based on field data for Beijing. The results indicate that the best fits for the distribution of passenger arrival rates for Type A and B bus stops are the lognormal distribution and gamma distribution, respectively. By analyzing relationships between passenger arrival rates and bus departure time intervals, it is demonstrated that parameters of the passenger arrival rate distribution can be expressed by the average and coefficient of variation of bus departure time intervals in functional relationships. The validation shows that the model provides a reliable estimation of the average passenger waiting time based on readily available bus departure time intervals.     

Design policies for sight distance at stop-controlled intersections based on gap acceptance

The current AASHTO policy for sight distance at stop-controlled intersections is based on a model of the acceleration performance of a minor-road vehicle turning left or right onto a major road and the deceleration performance of the following major-road vehicle. This paper develops and quantifies an alternative intersection sight distance model based on gap acceptance. The paper describes field studies that were performed to determine the critical gaps appropriate for use in sight distance design. It is recommended that the sight distance along the major road for a passenger car at a stop-controlled intersection be based on a distance equal to 7.5 s of travel time at the design speed of the major road. Longer sight distances are recommended for minor-road approaches that have sufficient truck volumes to warrant consideration of a truck as the design vehicle. ©     

Infrastructure based approach for roadway departure risk assessment

This paper presents a warning device to prevent the roadway departure of light vehicles while cornering. The proposed risk assessment methodology is based on recent works from the authors (Rey et al., 2011b,a; Rey, 2010). Given the random variability arising from the driver, the vehicle and the infrastructure at the entrance to the curve, a probabilistic strategy is adopted to assess the roadway departure risk. The infrastructure-based methodology enables the real curve characteristics to be considered and an alarm triggering decision to be made. Two safety criteria are tested and the potential safety benefits of the proposed warning device are evaluated. Contrary to existing roadway departure warning systems, the proposed approach does not require extra equipment for vehicles; it only requires that the measuring and warning devices be part of the road infrastructure, which is a great advantage in terms of economic cost.     

Delay to major street through vehicles at two-way stop-controlled intersections

This paper describes a methodology for predicting the delay to major street through vehicles at two-way stop-controlled intersections. This delay is incurred when major street left-turn demand exceeds the available storage area and blocks the adjacent through lane. The through lane blockage problem does not generally occur with significant frequency on streets with divided cross sections that have left-turn bays or lanes; however, it frequently occurs on undivided streets due to their lack of left-turn storage. To minimize this delay, through drivers often merge with vehicles in the adjacent through lane—if there is an adequate gap for them to safely merge into. If there is no merge opportunity, then the through drivers will stay in the inside lane until the queue ahead dissipates. The through vehicle delay predicted by the methodology was found to be relatively small (i.e. less than 5 s veh⁻¹) when compared with delays commonly incurred by non-priority movements at unsignalized intersections. However, when expressed in terms of total vehicle hours of delay, the effect can be quite significant. In general, through vehicle delay increases with increasing approach flow rate and left-turn percentage. However, at flow rates in excess of about 1400 veh h⁻¹, delays increase very rapidly and there is evidence that larger left-turn percentages may have lower delays. ©     

Implementing the maximum likelihood methodology to measure a driver’s critical gap

Most of the capacity calculation procedures for two-way stop-controlled (TWSC) intersections are based on gap acceptance models. Critical gap is one of the major parameters for gap acceptance models. The accuracy of capacity estimation is mainly determined by the accuracy of the critical gap. This paper focuses on the implementation of the maximum likelihood technique to measure a driver’s critical gap using field data. A methodology to define gap events is proposed, so that the accepted gaps and maximum rejected gaps required by the maximum likelihood technique could be obtained. Specific issues regarding multi-lane situations and major street right turn movement are discussed. Special conditions observed during the research are addressed when the proposed method cannot be applied directly, such as the existence of a mid-block refuge area where minor street drivers can seek gaps in a two-stage process, pedestrian blockage, and downstream queue spill back. The proposed method was adopted in measuring critical gap under US conditions during a research project, described by Kyte et al. (1996). ©     

Extensions of theoretical capacity models to account for special conditions

The computational procedures used to analyze two-way stop-controlled intersections were extended in the National Cooperative Highway Research Project 3-46 to account for a number of effects commonly observed at actual unsignalized intersections. This paper presents theoretical extensions that can account for commonly observed phenomena, such as two-stage gap acceptance when median storage is available; right-turn “sneakers” at flared minor-street approaches; non-random arrivals caused by upstream signals; impedance due to pedestrian crossings; and delay to major-street through vehicles using shared left-turn and through lanes. The individual effects are then combined into an analytical framework suitable for inclusion in the Unsignalized Intersections procedures of the 1997 “Highway Capacity Manual”. ©     

A practical method to estimate the benefits of improved road network reliability: an application to departing air passengers

This paper develops and applies a practical method to estimate the benefits of improved reliability of road networks. We present a general methodology to estimate the scheduling costs due to travel time variability for car travel. In contrast to existing practical methods, we explicitly consider the effect of travel time variability on departure time choices. We focus on situations when only mean delays are known, which is typically the case when standard transport models are used. We first show how travel time variability can be predicted from mean delays. We then estimate the scheduling costs of travellers, taking into account their optimal departure time choice given the estimated travel time variability. We illustrate the methodology for air passengers traveling by car to Amsterdam Schiphol Airport. We find that on average planned improvements in network reliability only lead to a small reduction in access costs per trip in absolute terms, mainly because most air passengers drive to the airport outside peak hours, when travel time variability tends to be low. However, in relative terms the reduction in access costs due to the improvements in network reliability is substantial. In our case we find that for every 1 Euro reduction in travel time costs, there is an additional cost reduction of 0.7 Euro due to lower travel time variability, and hence lower scheduling costs. Ignoring the benefits from improved reliability may therefore lead to a severe underestimation of the total benefits of infrastructure improvements.     

A multi-instrumented approach to observing the activity rescheduling decision process

Activity scheduling simulation models represent an emerging and proposing approach to forecasting travel demand. The most significant developmental challenge is the lack of empirical data on how people actually proceed through the scheduling and conflict resolution process. This paper develops a new methodology to collect data about the rescheduling decision process. The data collection involves six stages: preplanned schedule interview, coding of the preplanned schedule, second-by-second Global Positioning System tracking, internet-based prompted recall diary, detection of rescheduling decisions (via comparison of planned versus executed activities), and a final in-depth interview probing the how and why of rescheduling decisions. Each stage of the methodology is described in detail with example results drawn from a pilot study. Key discoveries include: elicitation of multiple preplanned schedule reporting methods (verbal, point-form, calendar); discovery that activity attributes (time, location, involved persons) are planned on significantly different time horizons and include partial elaboration; and provision of new insights into how and why rescheduling decisions are made. A method for automatically tracking rescheduling decisions was also discovered. Overall, the new methodology has potential to contribute to the development of more realistic models of the entire scheduling process, especially rescheduling and conflict resolution sub-models.     

Conflict-free arrival and departure trajectory planning for parallel runway with advanced point-merge system

In this paper, an efficient trajectory planning system is proposed to solve the integration of arrivals and departures on parallel runways with a novel route network system. Our first effort is made in designing an advanced Point Merge (PM) route network named Multi-Level Point Merge (ML-PM) to meet the requirements of parallel runway operations. Then, more efforts are paid on finding a complete and efficient framework capable of dynamically modelling the integration of arrival and departure trajectories on parallel runways, modelling the conflict detection and resolution in presence of curved trajectory and radius-to-fix merging process. After that, a suitable mathematical optimization formulation is built up. Receding Horizon Control (RHC) and Simulated Annealing (SA) algorithms are proposed to search the near-optimal solution for the large scale trajectories in routine dense operations. Taking Beijing Capital International Airport (BCIA) as a study case, the experimental results show that our system shows good performances on the management of arrivals and departures. It can automatically solve all the potential conflicts in presence of dense traffic flows. With its unique ML-PM route network, it can realize a shorter flying time and a near-Continuous Descent Approach (CDA) descent for arrival aircraft, an economical climbing for departure aircraft, an easier runway allocation together with trajectory control solutions. It shows a good and dynamic sequencing efficiency in Terminal Manoeuvring Area (TMA). In mixed ML-PM mode, under tested conditions, our proposed system can increase throughput at BCIA around 26%, compared with baseline. The methodology defined here could be easily applied to airports worldwide.     

Optimal multi-step toll design under general user heterogeneity

This paper studies the optimal multi-step toll design problem for the bottleneck model with general user heterogeneity. The design model is formulated as a mathematical program with equilibrium constraints (MPEC), which is NP-hard due to non-convexity in both the objective function and the feasible set. An analytical method is proposed to solve the MPEC by decomposing it into smaller and easier quadratic programs, each corresponding to a unique departure order of different user classes. The quadratic programs are defined on a polyhedral set, which makes it easier to identify a local optimum. Importantly, each quadratic program is constrained by a set of linear feasibility cuts that define the presence of each user class in the arrival window. We prove that the proposed method ensures global optimality provided that each quadratic program can be solved globally. To obviate enumerating all departure orders, a heuristic method is developed to navigate through the solution space by using the multipliers associated with the feasibility cuts. Numerical experiments are conducted on several small examples to validate the proposed methodology. These experiments show that the proposed heuristic method is effective in finding near-optimal solutions within a relatively small number of iterations.     

Design of an intersection decision support (IDS) interface to reduce crashes at rural stop-controlled intersections

Rural, stop-controlled intersections pose a crash risk to drivers, particularly elderly drivers. This paper outlines the design phase of an infrastructure-based intersection decision support (IDS) system to help drivers make safer gap acceptance decisions at rural intersections. A human factors-based design process was conducted to determine the type of information that should be presented to drivers. Information considered important for presentation to the driver included showing the presence of gaps, indicating the size of available gaps, and/or judging the safety of available gaps. This paper discusses the process used to determine the appropriate design specifications for initial testing of the IDS system interface.     

How routine is a routine? An analysis of the day-to-day variability in prism vertex location

This study is concerned with how routine an individual’s routine really can be. This question is addressed by examining the day-to-day variability of the time co-ordinate of the vertex of a time–space prism; in other words, by examining how the timeframe which governs the individual’s daily schedule varies from day to day. When the timeframe varies, it is likely that the individual’s behavior also varies. When the timeframe is stable, on the other hand, a routine can be maintained. The analysis presented in this paper attempts to determine how much of the variation in travel is due to the variation in the timeframe. The origin vertices of workers’ morning prisms, which determine how early they can leave home in the morning, are examined in this study, along with the departure times of the first trips in the prisms, which are mostly supposedly routine commute trips. The results indicate that the vertices are located with a much smaller variance, but vary more systematically than do the departure times of the first trips in the prisms. This implies that a large degree of variability is introduced when a trip is made within the timeframe as determined by a prism vertex. It is also shown that the departure time varies from worker to worker according to unobserved heterogeneity—i.e., unexplained differences across individuals—much more than does the prism vertex. The study results indicate that large degrees of flexibility are associated with trip making, and suggest the presence of room for behavioral modification with respect to workers’ first trips in the morning.     

A conflict model and interactive simulator (FASTCARS) for predicting enroute driver behavior in response to real-time traffic condition information

This paper proposes a theoretical methodology and practical data collection approach for modeling enroute driver behavioral choice under Advanced Traveler Information Systems (ATIS). The theoretical framework is based on conflict assessment and resolution theories popularized in psychology and applied to models of individual consumer behavior. It is posed that enroute assessment and adjustment is a reactionary process influenced by increased conflict arousal and motivation to change. When conflict rises to a level at which conflict exceeds a personal threshold of tolerance, drivers are likely to alter enroute behavior to alleviate conflict through either route diversion of goal revision. Assessment and response to conflict arousal directly relate to the driver's abilities to perceive and predict network conditions in conjunction with familiarity of network configurations and accessible alternate routes.Data collection is accomplished through FASTCARS (Freeway andArterialStreetTrafficConflictArousal andResolutionSimulator), in interactive microcomputer-based driving simulator. Limited real-world implementation of ATIS has made it difficult to study or predict individual driver reaction to these technologies. It is contended here that in-laboratory experimentation with interactive route choice simulators can substitute for the lack of real-world applications and provide an alternate approach to data collection and driver behavior analysis. This paper will explain how FASTCARS is useful for collecting data and testing theories of driver behavior.     

基于潜在冲突量的交叉口安全评价方法研究

文章提出了潜在冲突量的概念,并对其进行了分类,通过车速、交通量、车道宽度等易获取的交通参数来推算交叉口潜在冲突量,引入混合交通当量,将潜在冲突量与混合交通当量比值作为交叉口安全评价的指标,并结合桂林市的9个交叉口进行了安全程度的评价。     

Exploring the trade-off between greenhouse gas emissions and travel time in daily travel decisions: Route and departure time choices

This study analyzes the problem of conflicting travel time and emissions minimization in context of daily travel decisions. The conflict occurs because the least travel time option does not always lead to least emissions for the trip. Experiments are designed and conducted to collect data on daily trips. Random parameter (mixed) logit models accounting for correlations among repeated observations are estimated to find the trade-off between emissions and travel time. Our results show that the trade-off values vary with contexts such as route and departure time choice scenarios. Further, we find that the trade-off values are different for population groups representing male, female, individuals from high income households, and individuals who prefer bike for daily commute. Based on the findings, several policies are proposed that can help to lower greenhouse gas (GHG) emissions from transportation networks. This is one of the first exploratory studies that analyzes travel decisions and the corresponding trade-off when emissions related information are provided to the road users.     

Impact of continuous climb operations on airport capacity

The full benefits of Continuous Climb Operations (CCO) are realised when CCO are performed without interruption. However, CCO require safe departures that necessarily implies a reduction in capacity at high density traffic airports. This paper quantifies the capacity impact due to the integration of CCO (conflict-free with other departures and arrivals) in a high density traffic airport. The methodology develops a scheduling algorithm, a conflict-detection and resolution algorithm, and Monte Carlo simulations. The scheduling algorithm calculates two schedules, one for departures and another for arrivals, considering the CCO Rate. The conflict-detection and resolution algorithm compares CCO and arrival trajectories to detect which aircraft pairs are in conflict. The Air Traffic Control (ATC) intervention required to solve the conflict is modelled by delaying the CCO take-off. Numerical simulations based on Monte Carlo techniques are used to analyse scheduling combinations that are statistically significant in terms of conflict, ATC interventions, total delay and capacity. The results show a 32% reduction in the maximum theoretical capacity with a CCO Rate of 100%. Despite the reduction, the number of CCO departures is above the maximum operational capacity (50% of the maximum theoretical capacity). This implies that with optimised scheduling it is possible for all departures to be CCO.     

Methodology for Validating Dynamic Origin–Destination Matrix Estimation Models with Implications for Advanced Traveler Information Systems

This paper describes a methodology for validating online dynamic O–D matrix estimation models using loop detector data in large-scale transportation networks. The simulation procedure focuses on travel aspects related to the collective trip structure of users, including the amount and duration of trips between O–D pairs, trip departure rates, average travel time from each origin and combinations of them. The analysis identifies emerging systematic patterns between these factors and issues related to the model performance, including network scale effects. This procedure aims to enhance the usage of prior O–D information based on, e.g. travel surveys, that are typically used in the estimation process. Moreover, it seeks to integrate the validation of dynamic O–D matrix estimation models with strategies for identifying target population groups for online planning and assessment of real-time travel information services within the context of Advanced Traveler Information Systems (ATIS).     

From Twitter to detector: Real-time traffic incident detection using social media data

The effectiveness of traditional incident detection is often limited by sparse sensor coverage, and reporting incidents to emergency response systems is labor-intensive. We propose to mine tweet texts to extract incident information on both highways and arterials as an efficient and cost-effective alternative to existing data sources. This paper presents a methodology to crawl, process and filter tweets that are accessible by the public for free. Tweets are acquired from Twitter using the REST API in real time. The process of adaptive data acquisition establishes a dictionary of important keywords and their combinations that can imply traffic incidents (TI). A tweet is then mapped into a high dimensional binary vector in a feature space formed by the dictionary, and classified into either TI related or not. All the TI tweets are then geocoded to determine their locations, and further classified into one of the five incident categories.We apply the methodology in two regions, the Pittsburgh and Philadelphia Metropolitan Areas. Overall, mining tweets holds great potentials to complement existing traffic incident data in a very cheap way. A small sample of tweets acquired from the Twitter API cover most of the incidents reported in the existing data set, and additional incidents can be identified through analyzing tweets text. Twitter also provides ample additional information with a reasonable coverage on arterials. A tweet that is related to TI and geocodable accounts for approximately 5% of all the acquired tweets. Of those geocodable TI tweets, 60–70% are posted by influential users (IU), namely public Twitter accounts mostly owned by public agencies and media, while the rest is contributed by individual users. There is more incident information provided by Twitter on weekends than on weekdays. Within the same day, both individuals and IUs tend to report incidents more frequently during the day time than at night, especially during traffic peak hours. Individual tweets are more likely to report incidents near the center of a city, and the volume of information significantly decays outwards from the center.     

Economic effects of air transport market liberalization in Africa

Although the aviation industry is increasingly becoming important for Africa’s economic development and integration, the ability of airlines to access foreign markets remains hindered by restrictive regulatory policies. Attempts have been made to fully liberalize the intra-African air transport market. Except for general assertions about the merits/demerits of liberalization, our empirical understanding of the welfare effects of such polices in Africa remains rudimentary. This study empirically measures the economic effects of air transport liberalization, mainly on two supply side variables: fare and service quality, measured as departure frequency. The empirical models evaluate how air fares and departure frequency respond to measures of openness in air services agreements, while controlling for other determinants. The results show up to 40% increase in departure frequency in routes that experienced some type of liberalization compared to those governed by restrictive bilateral air service agreements. Furthermore, there is a relatively larger increase in departure frequency in routes which experienced partial liberalization compared to fully liberalized ones. This can be explained by the diminishing marginal effect of progressive liberalization on departure frequency. While the effect of liberalization is substantial in improving service quality, there is no evidence of its fare reducing effect.