Minimizing driver's irritation at a roadblock (original) (raw)
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arXiv: Physics and Society, 2020
We present a microscopic driving algorithm that prescribes the acceleration using three parameters: the distance to the leading vehicle, to the next traffic light and to the nearest stopping point when the next traffic light is in the red phase. We apply this algorithm to construct decision trees that enable two driving behaviors: aggressive and careful. The focus of this study is to analyze the amount of aggressive drivers that are needed in order to generate a traffic gridlock in a portion of a city with signalized intersections. At rush hour, aggressive drivers will enter the intersection regardless if they have enough time or space to clear it. When their traffic light changes they block other drivers, thus providing the conditions for a gridlock to develop. We find that gridlocks emerge even with very few aggressive drivers present. These results support the idea of promoting good driving behavior to avoid heavy congestion during rush hours.
1994
We use a very simple description of human driving behavior to simulate traffic. The regime of maximum vehicle flow in a closed system shows near-critical behavior, and as a result a sharp decrease of the predictability of travel time. Since Advanced Traffic Management Systems (ATMSs) tend to drive larger parts of the transportation system towards this regime of maximum flow, we argue that in consequence the traffic system as a whole will be driven closer to criticality, thus making predictions much harder. A simulation of a simplified transportation network supports our argument. * Permanent affiliation 1 microsimulation of the dynamics of all travelers and loads at the level of where the transport decisions are made. Starting with a generation of travel demands and trip decisions, then routing, over traffic, eventually the consequences for congestion frequencies, travel time, air quality etc. are generated and can thus be analyzed. This is the approach used by the TRANSIMS project , which this work also is a part of. Note that all the performance properties that we may be interested in in a transportation system (in fact in any man-made system) are emergent properties from the interacting objects in the system. They are nowhere explicitly represented at the level of the interacting objects. They are generated through the dynamics.
Traffic Jams: An Evolutionary Investigation
2004
Traffic at the rush hours is a big problem in every city so that city councils try to encourage citizens to choose mass transportation instead of driving cars. However, this effort is counterbalanced by the fact that travelers' utilities from car usage are more than those from taking buses in most cases. We build a traffic problem model with many agents who have the two options of choosing the car or the bus based on their memory of utilities achieved in previous journeys. Simulating this problem with a genetic algorithm can investigate commuters' behavior and can help identify if a Nash equilibrium exists in this model. We find that a Nash equilibrium exists in theoretical discussion but the population does not converge during the simulation to the Nash equilibrium point. Only a few travelers in the population moved between the two transport methods to establish dynamic stability and all others use only one means of transport throughout the simulation. However, some travelers choose to use the bus all the time (which increases the utilities of the population as a whole) even though their utilities are relatively lower than those of other travelers. Therefore, these simulations describe the emergence of cooperation which is built on some players bearing worse utilities to obtain more for all the population. so that there may be an intersection point of two payoff lines vs. the traffic situation (see ).
Vehicular traffic modeling with greedy lane-changing and inordinate waiting
Physica A: Statistical Mechanics and its Applications, 2019
Lane changing and vehicular slowdowns are known to impact traffic flow. Using a modified Nagel-Schreckenberg cellular automata model for two vehicle types: blocking (e.g. cars) and non-blocking (e.g. motorcycles), we determined the thresholds at which the interplay of lane changing, random and non-random slowdowns strongly impact vehicle speeds. Lane changing improves speed with diminishing returns as vehicles opt to change lanes. At the same time, lane changing is detrimental to the overall speed when lane straddling occurs. Increasing random slowdowns beyond a critical value (in the case of motorcycles, slowdown values of p slow ≈ [0.2, 0.3, 0.4] for densities ρ = [0.20, 0.15, 0.10] respectively) can force crossover from free flowing traffic into a state where interactions between vehicles reduce the average speed.
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A Computational Model to Study Urban Traffic Control
International Journal of Computer Theory and Engineering, 2014
The purpose of this paper is to develop a computational model to study vehicle flow on urban roads. The model presents a study undertaken at a two-way intersection where vehicle flow is controlled by traffic lights operating according to fixed intervals of times. This model is computationally simulated using Matlab/Simulink. Several simulations were processed and in practice the model proved to be stable and reliable. It is expected that the results will contribute to the creation of a stochastic predictive model to anticipate situations that lead to traffic jams.
Modeling Traffic on Crossroads
2007
A simplified traffic model is studied, consisting of two vehicles traveling through a sequence of crossroads regulated by yield signs. A car approaching a yield sign stops if, in the other street, there is a car closer than a certain distance x tol from the intersection. It is shown that the function which maps the state of the vehicles displays a period doubling transition to chaos. An interesting feature of the dynamics is that for extremely cautious drivers (x tol too large), the map turns chaotic, thus becoming a potential source of emergent jams. Complex behavior such as the one observed in this simple system seems to be an essential ingredient in traffic patterns, and could be of relevance in studying actual crossroads situations.
Stability analysis of a single-lane microscopic car-following model is studied analytically from the perspective of delayed reactions of human drivers. In the literature, the delayed reactions of the drivers are modeled with discrete delays, which assume that drivers make their control decisions based on the stimuli they receive from a point of time in the history. We improve this model by introducing a distribution of delays, which assumes that the control actions are based on information distributed over an interval of time in history. Such an assumption is more realistic, as it takes into consideration the memory capabilities of the drivers and the inevitable heterogeneity of their delay times. We calculate exact stability regions in the parameter space of some realistic delay distributions. Case studies are provided demonstrating the application of the results.
A behavioral theory of multi-lane traffic flow. Part I: Long homogeneous freeway sections
Transportation Research Part B: Methodological, 2002
This paper proposes a macroscopic behavioral theory of traffic dynamics for homogeneous, multilane freeways. The theory makes predictions for separate groups of lanes while recognizing that the traffic stream is usually composed of aggressive and timid drivers. Its principles are so simple that non-scientist drivers can understand them. The simplest version of the theory, which is described in its full complexity without calculus, is shown to be qualitatively consistent with experimental observations, including the most puzzling. Its predictions agree with the following phenomena: (i) the 'reversed lambda' pattern frequently observed in scatter-plots of flow versus occupancy and the lane-specific evolution of the data points with time, including the 'hysteresis' phenomenon, (ii) the lane-specific patterns in the time series of speed (and flow) in both queued and unqueued traffic, and (iii) the peculiar ways in which disturbances of various types propagate across detector stations. The latter effects include the evolution of both, stoppages and transitions between the queued and unqueued traffic regimes. The simple model is specified by means of eight observable parameters. The paper gives a recipe for solving any well-posed problem with this model and does so in sufficient detail to allow the development of computer models. A few approaches and possible generalizations are suggested. A sequel to this paper, devoted to freeway sections near on-ramps, will attempt to explain in more detail than previously attempted how queuing begins at merges.
Simulating the Impact of Traffic Calming Strategies
2019
This study assessed the impact of traffic calming measures to the speed, travel times and capacity of residential roadways. The study focused on two types of speed tables, speed humps and a raised crosswalk. A moving test vehicle equipped with GPS receivers that allowed calculation of speeds and determination of speed profiles at 1s intervals were used. Multi-regime model was used to provide the best fit using steady state equations; hence the corresponding speed-flow relationships were established for different calming scenarios. It was found that capacities of residential roadway segments due to presence of calming features ranged from 640 to 730 vph. However, the capacity varied with the spacing of the calming features in which spacing speed tables at 1050 ft apart caused a 23% reduction in capacity while 350-ft spacing reduced capacity by 32%. Analysis showed a linear decrease of capacity of approximately 20 vphpl, 37 vphpl and 34 vphpl when 17 ft wide speed tables were spaced at 350 ft, 700 ft, and 1050 ft apart respectively. For speed hump calming features, spacing humps at 350 ft reduced capacity by about 33% while a 700 ft spacing reduced capacity by 30%. The study concludes that speed tables are slightly better than speed humps in terms of preserving the roadway capacity. Also, traffic calming measures significantly reduce the speeds of vehicles, and it is best to keep spacing of 630 ft or less to achieve desirable crossing speeds of less or equal to 15 mph especially in a street with schools nearby. A microscopic simulation model was developed to replicate the driving behavior of traffic on urban road diets roads to analyze the influence of bus stops on traffic flow and safety. The impacts of safety were assessed using surrogate measures of safety (SSAM). The study found that presence of a bus stops for 10, 20 and 30 s dwell times have almost 9.5%, 12%, and 20% effect on traffic speed reductions when 300 veh/hr flow is considered. A comparison of reduction in speed of traffic on an 11ft wide road lane of a road diet due to curbside stops and bus bays for a mean of 30s with a standard deviation of 5s dwell time case was conducted. Results showed that a bus stop bay with the stated bus dwell time causes an approximate 8% speed reduction to traffic at a flow level of about 1400 vph. Analysis of the trajectories from bust stop locations showed that at 0, 25, 50, 75, 100, 125, 150, and 175 feet from the intersection the number of conflicts is affected by the presence and location of a curbside stop on a segment with a road diet.