Microscopic traffic flow models enable predictions of traffic operations, which allows traffic engineers to assess the efficiency and safety effects of roadway designs. Modeling vehicle trajectories inside intersections is challenging because there is an infinite number of possible paths in a two-dimensional space, and drivers can simultaneously adapt their speeds as well. To date, human driver models for simultaneous longitudinal and lateral vehicle control based on the infrastructure characteristics and interactions with other drivers inside an intersection are still lacking. The contribution of this paper is threefold. First, it proposes an integrated microscopic traffic flow model to describe human-driven vehicle maneuvers under interactions. Drivers plan their heading and acceleration in the predicted future to minimize costs representing undesirable situations. The model works with a joint optimization for an interaction cost term. The weights associated with the interaction cost reflect how selfish or altruistic drivers are. Second, the proposed model endogenously gives the order of vehicles in case of crossing paths. Third, the paper develops a clustered validation method for microscopic traffic flow models with interacting vehicles, which account for interdriver variations. Results show that the model can accurately describe vehicle passing orders of interacting maneuvers, paths, and speeds against empirical data. The model can be applied to assess various intersection designs.

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A joint control approach that simultaneously optimizes traffic signals and trajectories of cooperative (automated) vehicle platooning at urban intersections is presented in this paper. In the proposed approach, the signal phase lengths and the accelerations of the controlled platoons are optimized to maximize comfort and minimize travel delay within the signal cycle, subject to motion constraints on speeds, accelerations and safe following gaps. The red phases are initially considered as logic constraints, and then recast as several linear constraints to enable efficient solutions. The proposed approach is solved by mixed integer linear programming (MILP) techniques after linearization of the objective function. The generated outputs of the MILP problem are the optimal signal timings and the optimal accelerations of all vehicles. This joint control approach is flexible in incorporating multiple platoons and traffic movements under different traffic demand levels and it does not require prespecified terminal conditions on position and speed at the signal cycle tail. The performance of the proposed control approach is verified by simulation at a standard four-arm intersection under the balanced and unbalanced vehicle arrival rates from different arms, taking the released traffic movement numbers, turning proportions, signal cycle lengths and the controlled vehicle numbers into account. The simulation results demonstrate the platoon performance of the joint controller (such as split, merge, acceleration and deceleration maneuvers) under the optimal signals. Based on the simulation results, the optimal patterns of trajectories and signals are explored, which provide insights into the optimal traffic control actions at intersections in a cooperative vehicle environment. Furthermore, the computational performance of the proposed control approach is analyzed, and the benefits of the proposed approach on the average travel delay, throughput, fuel consumption, and emission are proved by comparing with the two-layer approaches using the car following model, the signal optimization models, and the state-of-the-art approach.

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Owing to the rapid development of emergency rescue transportation in cities and the frequent emergencies, demand for emergency rescue is increasing drastically. How to select an emergency rescue route quickly and shorten the rescue travel time under the condition of limited urban road resources is of great significance. Based on the characteristics analysis of emergency rescue, this paper classifies priority levels of different emergency traffic, moreover, the travel times are also analysed with three scenarios: 1) emergency rescue vehicles encountering no queues; 2) encountered queues but lanes available; 3) encountered queues with no available lanes. Related case study shows that model in this paper can effectively shorten travel time of emergency traffic in the route and improve its efficiency.

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Modeling traffic flow at intersections is essential for the design, control, and management of intersections. A challenging feature of microscopic modeling vehicular movement at intersections is that drivers can choose among an infinite number of alternative traveling paths and speeds. This makes it fundamentally different from structured straight road sections with lanes. This study proposes a novel method to model the trajectories of vehicles in two-dimensional space and speed. Based on optimal control theory, it assumes drivers schedule their driving behavior, including the steering and acceleration, to minimize the predicted costs. The costs contain the running costs, which consist of the travel time and driving smoothness (longitudinally and laterally), and the terminal cost, which penalizes the deviations from the desired final state. Different than conventional methods, the vehicle motion dynamics are formulated in distance rather than in time. The model is solved by an iterative numerical solution algorithm based on the Minimum Principle of Pontryagin. The descriptive power, plausibility, and accuracy of the proposed model are investigated by comparing the calculated results under several cases, which can be solved from symmetry or analytically. The proposed model is further calibrated and validated using empirical trajectory data, and the quality of the predicted trajectory is confirmed. Qualitatively, the optimal trajectory changes in the range of the shortest path and smoothest path under different weights of the running cost. The proposed model can be used as a starting point and extended with more considerations of intersection operation in the real world for future applications.@en

The continuous flow intersection [CFI) is an unconventional intersection design which has been used in many cities all over the world. However, as an important parameter for the geometric design, signal timing, and operation evaluation, the saturation flow rate at CFI has not been carefully examined. In this paper, a saturation flow rate adjustment model for CFI intersections is established based on field data under the calculation framework of the HCM2016. Four movements related with CFI, namely the left-turn at the CFI approach, through movement at the CFI approach, left-turn at the pre-signal, and exit movement at the pre-signal, are discussed. The proposed model is validated and the relative error is less than 10%. The treatments to mitigate the negative impact on the saturation flow rate at the CFI are also recommended. The results show the saturation flow rate of the first three movements are decreased due to the CFI control. For the left-turn, through movement, and left-turn at the pre-signal, the degree of the reduction of the saturation flow rate are mainly related to the heavy vehicle ratio, the proportion of lane changing vehicles, and the length of displaced left-turn lanes, respectively.

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Traffic throughput at intersections can be improved by using exit lanes for left-turning (EFL), tidal flow lanes near an intersection, which has been recently introduced. This paper considers the operational robustness of the EFL intersection in relation to the control scheme applied to the traffic light setting. For safety and efficiency, it is important that the tidal lanes are emptied before traffic in the opposing direction uses these lanes. Hence, the signal control should not only be optimized for the mean value but be robust for all kinds of fluctuations. This paper formulates a traffic control scheme using robust optimization, i.e. an optimization scheme which explicitly accounts for extreme events. The fluctuation of traffic is considered from three aspects: the distribution of traffic demand, the distribution of base saturation flow rate, and the distribution of actual travel speed. Via a case study and extensive numerical analysis, we find that the established robust optimization method produces an efficient design of signal control and design speed at the EFL intersection under traffic demand and supply fluctuations. Though the optimization method is now applied to intersections with an EFL, it is considered useful for all intersections with high fluctuation of traffic demand and saturation flow rate.

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The lane closures caused by the work zone at the approaches create a negative impact on the operational effectiveness of the signalized intersections. This paper presents an innovative design for intersections with work zones to improve the intersection’s practical capacity. In this design, the lanes in the leg with work zone can be used dynamically as approach and exit lanes during different periods of a signal cycle by using the pre-signal. An optimization model for an optimal geometric layout and signal timing design is built to capture real-world operational constraints, including the lane assignment, the signal timing of the main signal and pre-signal, the distance of the mixed-usage area and the transition area, and the degree of saturation restriction. A case study and extensive numerical analysis demonstrate the effectiveness of the prospective design as compared with conventional designs under different geometric layout and traffic demand situations. Overall, the proposed design can lead to an increment in the practical capacity of the intersection with a work zone (by up to 30%) and reduce the average vehicular delay accordingly (by 50%) without necessitating an expansion of the intersection. The results show that the promising application of the proposed design when the length of the work zone is less than 160 m.

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The intersection with special width approach lane (SWAL) is a newly proposed unconventional intersection design. A microscopic traffic flow model was proposed for describing the operation of vehicles at signalised intersections with SWAL. The operation process of driving on the SWAL was divided into four segments, including entering segment, transition segment, special width lane segment, and exiting segment. The car-following and lane selection behaviours of vehicles in these segments are analysed. The parameters used in the model were calibrated using the field data collected in Germany. The proposed model was realised in a time-discretised simulation. The sensitivity analyses of geometric, traffic, and signal factors were conducted. The results show that for the car-following behaviour, the passenger cars on the narrowed lanes cannot drive as efficient as on the normal width lane. For lane selection behaviour, it mainly depends on the distance between the two nearest vehicles in front of the two narrow lanes. The effectiveness of the SWAL depends on whether it is long enough to accommodate the queuing vehicles, which is a combined result of the layout design and the signal timing.

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Violation probability of taxi drivers in metropolis is far more than that of normal drivers because they are labor-intensive, overconfident of self-driving skill, and always searching potential customers, sometimes even picking up or dropping off passengers randomly. In this paper, four types of violated behavior of taxi drivers in metropolis were first summarized, based on which corresponding scale table was initial designed with social statistical method. Furthermore, with certain samples, relative item analysis, exploratory factor analysis, validity analysis and reliability analysis were conducted to verify validity of the initial scale table, based on which some improvements were made, and we can see that the modified scale table in the paper has high fitness degree, good reliability and validity to detect violated behavior of taxi driver accurately. Finally, large area survey data of taxi driver questionnaire from Shanghai was collected with the modified scale table above, the analysis results showed that among four types of violated behavior of taxi drivers in metropolis, the probability over-speed is top to 89.57%, in which probabilities of behaviors of “driving over-speed at mid-night” and “accelerating to across the intersection during the yellow signal” are top to 64.2% and 58.2% respectively, which is meaningful for the improvement of taxi drivers’ behaviors specification and traffic safety regulation.

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To improve the practical capacity of the continuous flow intersections (CFI)
and eliminate the conflict between left-turn bicycles and through vehicles,
an optimization design method for left-turn bicycles was proposed.
The pre-stop line for through vehicles and the crossing passage for leftturn
bicycles were set at the pre-signal points of the CFI. The control of the
through vehicles at pre-signal was added in the proposed method. A linear
programming model was established to achieve the maximum vehicular
practical capacity. The optimization effectiveness and applicability for this
design were validated by a case study and sensitivity analyses. The results
show that the improvements in practical capacity obtained by the proposed
method increase with the increase of the left-turn bicycles volume
and through vehicle percentage, while decrease with longer cycle length.
As for bicycles, the proposed method can reduce the delay in the case of
high traffic demand.@en