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This study investigates various risk factors associated with pedestrian crash occurrence and injury severity based on 78,497 reported pedestrian-involved crashes across Texas from 2010 through 2019. Crashes are mapped to over 708,738 road segments, along with road design, land use, transit, hospital, rainfall, and other location features. Negative binomial models examine the association between pedestrian crash frequency and various contributing factors, and a heteroskedastic ordered probit model investigates the severity of injuries at the individual crash level. Results from this study show the practical significance of microlevel variables in predicting pedestrian crashes. Proximity to schools and hospitals and presence of transit are all associated with higher pedestrian crash frequencies yet are rarely included in other models. Total pedestrian crash and fatal crash counts rise with the number of lanes, population, and job densities, though greater median and shoulder widths provide some protection. Higher speed limits are associated with lower crash frequencies but more deaths. Pedestrian crashes are more likely to be severe and fatal at night (8 p.m. to 5 a.m.), without overhead lighting, and when involved pedestrians and/or drivers are intoxicated. Use of light-duty trucks also significantly increases risk of severe or fatal pedestrian injury. Though newer vehicle safety features may be argued to lower crash severity or protect vehicle occupants, newer crash-involved vehicles in Texas are not found to deliver less severe pedestrian injury. Pedestrian and driver characteristics—both age and gender—are practically (and statistically) significant. Injury severity rises with pedestrian age, yet younger and/or female pedestrians on straight roadways, off the state (and interstate) highway system, and in the presence of a traffic control device (stop sign or signal) are less likely to be seriously injured, on average. Findings underscore the benefit of enhanced vehicle safety features for pedestrians, campaigns against driving and walking while intoxicated, improved roadway design, enforcement of safety countermeasures near schools and bus stops, and installment of additional traffic controls and streetlights wherever more pedestrians exist. [ABSTRACT FROM AUTHOR]

Traffic signals strongly influence traffic in cities – in terms of delay but also in terms of the emissions emitted by traffic. This work analyzes the effect of different traffic control strategies on emissions like NO x and PM x. Simulations of an inner-city arterial show that reducing the speed limit leads to a lower production of NO x and PM x , but to an increase in delay. The impact of the traffic signal control on the emissions is less distinct: A carefully designed co-ordination reduces emissions, while a simple actuated control cannot improve traffic flow and therefore increases pollutant production. [ABSTRACT FROM AUTHOR]

• Identify, formulate, and solve optimal location problem for VSL application areas. Formulation and solution for lane-drop, sag, and tunnel bottlenecks. • Lighthill-Whitham Richards model with bounded acceleration (BA-LWR) is used. • Capacity drop formation depends on speed limits and VSL locations. • Define admissible conditions for congested and uncongested stationary states. • Optimal distances of VSL application areas from bottlenecks increase in speed limits. Some studies consider variable speed limit (VSL) control as a viable option to prevent traffic breakdown at bottlenecks by limiting the mainline flow with reduced speed limits. However, few studies consider the location of the application area as a design variable of the problem. This paper explains why the location of a VSL control area is crucial to prevent the capacity drop phenomenon at lane drop bottlenecks. We first define two types of stationary states, congested and uncongested, inside a lane drop bottleneck assuming the Lighthill-Whitham Richards model with bounded acceleration. In particular, the characteristics of these stationary states and their admissible conditions are discussed thoroughly. If the speed limit imposed is low enough, the location of the VSL application area is irrelevant to ensure an uncongested stationary state inside the bottleneck. However, for a given range of speed limits, the location of the VSL application area should be designed carefully to allow for uncongested stationary states and prevent the occurrence of the capacity drop. We formulate an optimization problem and show that, contrary to the general belief, the larger the speed limit, the farther the VSL application area should be from the bottleneck. Finally, the results are extended to other types of bottlenecks, such as sag or tunnel bottlenecks. To the best of our knowledge, this is the first study to analytically identify, formulate, and solve the optimal location problem for variable speed limit application areas. It makes fundamental contributions to both traffic flow theory (by analyzing the stationary states for VSL-controlled bottlenecks) and traffic control (by determining the optimal location of a VSL application area). Moreover, the results presented are of practical relevance because they can help to establish some guidelines for practitioners to implement VSL control strategies. [ABSTRACT FROM AUTHOR]

Introduction: Traffic engineers require robust tools to assist with their day-to-day decision making, and there is no better example of this than traffic signal warrants. North American traffic signal warrant systems are lacking in how they incorporate motor-vehicle collisions from both a severity and prediction perspective. The objective of this study was to produce reliable collision costs for the development of improved traffic signal warrants that accounted for the variations in severity that practitioners should expect based on the characteristics of the intersection being studied. Method: The primary data used for this analysis were from the National Automotive Sampling System (NASS) Crashworthiness Data System, with adjustments from the NASS General Estimates System and Fatality Accident Reporting System. Generalized ordered logit models were used to identify the most significant intersection characteristics, which were then used to segregate the data to determine expected the collision severity profiles and average costs of both casualty and total collisions at intersections. Results: The average collision at a signalized intersection was found have a lower severity than the average collision at a stop-controlled intersection. A combination of posted speed limit, urban/rural, and divided/undivided were identified as the most significant intersection characteristics in most cases and were used to delineate the data for developing collision cost estimates. Conclusions: Posted speed limit, rural/urban land use, and the presence of divided approaches are intersection characteristics that traffic engineers can readily determine and/or control for that have significant effects on intersection collision severity. Practical applications: The collision costs produced through this process give traffic engineers a reliable estimate that can provide a more substantial foundation for justifying a proposed change in intersection traffic control. • Forward-selecting generalized ordered logit models used to explore study variables. • Variable selection order differs significantly for different forms of traffic control. • Urban/rural, speed limit, and divided/undivided were the most significant variables. • Signal control results in a lower average collision severity than stop control. [ABSTRACT FROM AUTHOR]

In general, the use of superelevation and changes in a road's transverse slope are typically based on the road's design speed to provide safety and comfort for a vehicle driving on a horizontal curve. However, due to the difference between operating and design speeds, there has always been uncertainty in determining the margin of safety using superelevation. This paper discusses the assessment of the safety margins obtained from the application of superelevation in horizontal-curve design. The assessment uses geometric design guides and a reliability index to determine any uncertainties in the design parameters. In addition, adjusted design charts of superelevation values related to the radius of horizontal curves at various levels of probability of noncompliance are provided. The results show that the adjusted superelevation values are generally greater than those derived from current standards. The adjusted design charts can help designers select an appropriate superelevation value for a particular horizontal curve for highways that have geometric constraints. These adjusted charts may also aid designers in predicting the consequences and safety margins associated with the selection of superelevation alternatives required to approve geometric designs that involve violations of the standard requirements due to environmental constraints. [ABSTRACT FROM AUTHOR]

Traffic signals, even though crucial for safe operations of busy intersections, are one of the leading causes of travel delays in urban settings, as well as the reason why billions of gallons of fuel are burned, and tons of toxic pollutants released to the atmosphere each year by idling engines. Recent advances in cellular networks and dedicated short-range communications make Vehicle-to-Infrastructure (V2I) communications a reality, as individual cars and traffic signals can now be equipped with communication and computing devices. In this paper, we first presented an integrated simulator with V2I, a car-following model and an emission model to simulate the behavior of vehicles at signalized intersections and calculate travel delays in queues, vehicle emissions, and fuel consumption. We then present a hierarchical green driving strategy based on feedback control to smooth stop-and-go traffic in signalized networks, where signals can disseminate traffic signal information and loop detector data to connected vehicles through V2I communications. In this strategy, the control variable is an individual advisory speed limit for each equipped vehicle, which is calculated from its location, signal settings, and traffic conditions. Finally, we quantify the mobility and environment improvements of the green driving strategy with respect to market penetration rates of equipped vehicles, traffic conditions, communication characteristics, location accuracy, and the car-following model itself, both in isolated and non-isolated intersections. In particular, we demonstrate savings of around 15% in travel delays and around 8% in fuel consumption and greenhouse gas emissions. Different from many existing ecodriving strategies in signalized road networks, where vehicles’ speed profiles are totally controlled, our strategy is hierarchical, since only the speed limit is provided, and vehicles still have to follow their leaders. Such a strategy is crucial for maintaining safety with mixed vehicles. [ABSTRACT FROM AUTHOR]

The problem of eco-driving is analyzed for an urban traffic network in presence of signalized intersections. It is assumed that the traffic light timings are known and available to the vehicles via infrastructure-to-vehicle communication. This work provides a solution to the energy consumption minimization while traveling through a sequence of signalized intersections and always catching a green light. The optimal- control problem is non-convex because of the constraints coming from the traffic lights; therefore, a sub-optimal strategy to restore the convexity and solve the problem is proposed. Firstly, a pruning algorithm aims at reducing the optimization domain by considering only the portions of the traffic light's green phases that allow to drive in compliance with the city speed limits. Then, a graph is created in the feasible region in order to approximate the energy consumption associated with each available path in the driving horizon. Lastly, after the problem convexity is recovered, a simple optimization problem is solved on the selected path to calculate the optimal crossing times at each intersection. The optimal speeds are then suggested to the driver. The proposed sub-optimal strategy is compared with the optimal solution provided by dynamic programming for validation purposes. It is also shown that the low computational load of the presented approach enables robustness properties and results very appealing for online use. Copyright © 2015 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

The importance of safety comes from the responsibility towards protecting the vulnerable road users, who seem to be the victims in most road crashes. Thus, authorities tend to focus on reducing the travelling speed of the vehicles, whereas some road users may consider the move to interfere with mobility. In this study, a case study in Perth's two roads was conducted to compare two engineering treatments of speed reductions on these two busy shopping strips. The study aim is to illustrate the effect of using the electronic flashing signs rather than the standard signs in terms of speeding reduction and harm minimisation. Crash data were analysed and supported the safety benefits of the electronic flashing signs. Authorities have measured the reduction of the travelling speeds of vehicles and found it to be encouraging. There are clear, positive safety benefits from the study in terms of engineering and enforcement measures. [ABSTRACT FROM AUTHOR]

Left-turn gap acceptance at an unsignalized intersection is dependent on many factors. The Highway Capacity Manual (HCM) uses a single value of critical gap for all types of intersections; however, this may be oversimplistic and lead to inaccurate estimates of left-turn delay and capacity. Most existing studies also do not differentiate between gap and lag when evaluating gap acceptance. In this paper, binary logit models were developed to estimate the probability of accepting or rejecting a given gap or lag for a left-turning vehicle from a major road at an unsignalized intersection considering a number of potential influencing factors. Gap acceptance behavior was found to be influenced by the type of gap presented to the driver (gap or lag). Gap duration, total wait time, time to turn, distance to next signal downstream, and median type were found to be significant factors in predicting the probability of accepting or rejecting a gap. In the model for lag acceptance lag duration, time to turn, crossing width, speed limit, and distance to next signal downstream were found to be significant. Equations for estimating the critical gap and lag were developed. Critical gap and lag were found to be varying over a wide range of values depending on the type of intersection. The range was smaller for critical gaps than lags. The findings from this study can improve operational analysis of left turns at unsignalized intersections by using different critical gaps for different traffic and geometric conditions. [ABSTRACT FROM AUTHOR]

Robust road-boundary extraction/tracking is one of the main problems in autonomous roadway navigation. Although the road boundary can be defined by various means including lane markings, curbs, and borders of vegetation, this paper focuses on road-boundary tracking using curbs. A vehicle-mounted (downward tilted) 2-D laser-measurement system is utilized to detect the curbs. The tracking problem is difficult because both the vehicle is moving and the target is disappearing, reappearing, and maneuvering in clutter. The interacting-multiple-model probabilistic-data-association filter (IMMPDAF) is proposed to solve the problems after detailed analysis. Track initiation, confirmation, and deletion are performed using the sequential-probability-ratio test. Extensive simulations followed by experiments in a campus environment show that the road-boundary tracking utilizing curbs is possible and robust through IMMPDAF. [ABSTRACT FROM AUTHOR]

In this paper, an iterative learning approach for the freeway density control under ramp metering and speed regulation is developed in a macroscopic level traffic environment. Rigorous analyses show that the proposed learning control schemes guarantee the asymptotic convergence of the traffic density to the desired one. The two major features of the learning-based density control are 1) less prior modeling knowledge required in the control system design and 2) the ability to reject exogenous traffic perturbations. The control schemes are applied to a freeway model, and simulation results confirm the efficacy of the proposed approach. [ABSTRACT FROM AUTHOR]