Zone Speed Limit Research Articles

Supervised and unsupervised techniques to analyze risk factors associated with motorcycle crash.

Motorcycles are one of the highly used modes of transport in Barcelona, Spain, in particular, and in many different regions, in general. This situation is compromising safety on the road and may be attributed to a potential increase in traffic crashes. Therefore, this study examines several risk factors and their consequential impacts on the level of injury that is resulted in case of a traffic crash. Two approaches are employed to analyze the risk factors, including a supervised learning technique which is a binary probit model, and an unsupervised technique which is the Kohonen clustering. The results for both models show that alcoholism and road in poor condition can indeed increase the probability of having different levels of injuries as reasons for the crash. Elderly users are less likely to be involved in motorcycle crash injuries compared to other age categories, especially the age group that ranges from 25 to 40 years old which has the highest odds. For both techniques, the performance in analyzing the utilized data shows that both approaches can be successfully utilized for this type of dataset. This study highlights the considerable danger faced by motorcyclists due to various risk factors. It stresses the critical importance of maintaining roads in optimal condition not just for efficient travel but also to enhance motorcyclists' safety. Additionally, the research underscores the significant threat posed by speeding, particularly exceeding speed limits, to motorcyclists' safety, emphasizing the urgent need for more 30 km/h speed limit zones and stricter enforcement of speed regulations. As a result, the research has identified several risk factors that increase the likelihood of severe or fatal injuries among motorcyclists in Barcelona and has suggested certain recommendations to mitigate their impact.

Reinforcement Learning-Based Dynamic Zone Positions for Mixed Traffic Flow Variable Speed Limit Control with Congestion Detection

Existing transportation infrastructure and traffic control systems face increasing strain as a result of rising demand, resulting in frequent congestion. Expanding infrastructure is not a feasible solution for enhancing the capacity of the road. Hence, Intelligent Transportation Systems are often employed to enhance the Level of Service (LoS). One such approach is Variable Speed Limit (VSL) control. VSL increases the LoS and safety on motorways by optimizing the speed limit according to the traffic conditions. The proliferation of Connected and Autonomous Vehicles (CAVs) presents fresh prospects for improving the operation and measurement of traffic states for the operation of the VSL control system. This paper introduces a method for the detection of multiple congested areas that is used for state estimation for a dynamically positioned VSL control system for urban motorways. The method utilizes Q-Learning (QL) and CAVs as mobile sensors and actuators. The proposed control approach, named Congestion Detection QL Dynamic Position VSL (CD-QL-DPVSL), dynamically detects all of the congested areas and applies two sets of actions, involving the dynamic positioning of speed limit zones and imposed speed limits for all detected congested areas simultaneously. The proposed CD-QL-DPVSL control approach underwent an evaluation across six distinct traffic scenarios, encompassing CAV penetration rates spanning from 10% to 100% and demonstrated a significantly better performance compared to other control approaches, including no control, rule-based VSL, two Speed-Transition-Matrices-based QL-VSL configurations with fixed speed limit zone positions, and a Speed-Transition-Matrices-based QL-DVSL with a dynamic speed limit zone position. It achieved enhancements in macroscopic traffic parameters such as the Mean Travel Time and Total Time Spent by adapting its control policy to every simulated scenario.

Comparison of Analytical and Simulation Results for One-Lane Operation on Low-Volume Two-Lane Highway

Work zones on two-lane highways with one lane closed require sharing the open lane with traffic from the closed directions. In such work zones, traffic control resembles operating a two-phase traffic signal and, in rare cases, a three-phase traffic signal. Temporary traffic signals (or flaggers) allow the open lane to be used in an alternating manner. Signal timing (green times and cycle length) of the temporary traffic lights directly affects the delay and queue in the work zones. Delay and queue computations must consider queue build up that often happens in oversaturated conditions. Another influential variable is the average operating speed of the work zone. The operating speed is affected by the work zone speed limit, work intensity, speed control technique, lane and shoulder widths, acceleration capability of vehicles, and work zone length. WorkZoneQ-Pro (WZQ-Pro) is developed with a new signal timing method that considers the above-mentioned factors. The procedure can handle multiple hours of analysis with two- or three-phase signal operations. Test scenarios are real-world work zone examples from three different U.S. states that were used to compute signal time variables and use them to compute queue and delay. These values were also computed using Highway Capacity Manual (HCM) 2016 procedures and are compared. In addition, the computed values were input into Vissim simulation software, and the results were compared. It showed that the WZQ-Pro results are reasonably close to Vissim simulation results, and that further validated that an acceptable agreement existed between the analytical and simulation results.

An exploratory analysis of the effects of speed limits on pedestrian injury severities in vehicle-pedestrian crashes

IntroductionPedestrian safety is gaining nationwide attention in the recent years with increasing fatalities and serious injuries relative to other modes of transportation. The percentage of pedestrian fatalities in all traffic fatalities in Florida clearly highlights the importance of the vulnerability. Considering the importance of ‘Safe System’ approach, this study aims to investigate the contributing factors for different speed limits in vehicle-pedestrian crashes and resulting injury severities. MethodThis study explored the pedestrian crashes over three speed limit zones, namely, low- (≤25 mph), medium- (30–40 mph) and high-speed (45–70 mph) roadways in Florida. Utilizing 2017 (inclusive) crash data in Florida, random parameters multinomial logit models with unobserved heterogeneity in means and variances were estimated. The crash data include a wide variety of factors related to the spatial, temporal, vehicle and traffic characteristics, environmental characteristics, roadway attributes, and human factors. ResultsThe model estimates indicated that there were significant differences in pedestrian-injury severities in these speed limit zones. It is noteworthy that crashes involving pedestrian had many explanatory variables that produced marginal effects varying across low-, medium-, and high-speed limit zones. More importantly, the likelihood of pedestrian injury severity at high-speed limit zones is about 3.1 times higher for roadways with 40,000 vehicles per day, 3.2 times higher for two-way roads with positive median barrier, and 1.7 times higher for urban principal roadways relative than those at medium speed limit zones. The model results also indicate that the likelihood of severe pedestrian injury is higher for District 1, afternoon peak (4–6 p.m.), turn-lane, and dark condition on high-speed limit zones. ConclusionFormulation of countermeasures to mitigate pedestrian injury severity should be considered separately for three distinct speed limit zones. These countermeasures include the vehicle technology, roadway-infrastructure design, drivers' awareness, and pedestrians’ education interventions to minimize the system kinematic energy.

Performance Evaluation for Secure Communications in Mobile Internet of Vehicles With Joint Reactive Jamming and Eavesdropping Attacks

Internet of Vehicles (IoV) is considered to be a backbone of smart transportation system where vehicles are expected to exchange traffic information and other data using vehicle-to-vehicle (V2V) communications. Furthermore, V2V communications is regarded as a medium to send upcoming traffic information to vehicles/drivers or passengers using wireless technology in a timely manner. This will help reduce traffic accidents, traffic jams, fuel consumption caused by traffic jams, loss of hours caused by delayed commuting and carbon emission caused by vehicles. Because of the critical nature of IoV for smart transportation systems, secure wireless communication is one of the critical and essential components to offer trustworthy services through IoV. Like in other wireless systems, wireless communication is open in air, which makes attackers’ job easy to launch the malicious actions in IoV. In this paper, we investigate the impact of mobility of vehicles for secure communications in IoV with joint jamming and eavesdropping attacks. We investigate different scenarios, when vehicles (legitimate ones and attackers) travel in same and opposite directions with low speed (school zone speed) limit to highway speed limit. Furthermore, we study the impact of association time and encryption time not only for establishing the connection between vehicles for V2V communications but also for exchanging messages for vehicles after successful association between vehicles and encryption of the message. In addition, we also study the joint impact of jamming and eavesdropping attacks in IoV for different speed limits, transmission ranges and wireless bandwidths. We investigate the extra cost in terms of transmit power and bandwidth incurred by jamming and eavesdropping attacks while maintaining the same secrecy rate as it could have been without those attacks. Numerical results are used to support the analysis.

Influence of Spatial Placement of Variable Speed Limit Zones on Urban Motorway Traffic Control

Traffic control approaches, in particular Variable Speed Limit (VSL), are often studied as solutions to im-prove the level of service on urban motorways. How-ever, the efficiency of VSL strongly depends on the spa-tiotemporal arrangement of VSL zones. It is crucial to determine the length and location of VSL zones for best VSL efficiency before deployment in a real system, as the optimal length of the VSL zone and their distance from the bottleneck directly affects traffic dynamics and, thus, bottleneck control. Therefore, in this study, we perform the analysis of different VSL zones lengths and their po-sitions by using a closed-loop Simple Proportional Speed Controller for VSL (SPSC-VSL). We evaluate the different VSL zone configurations and their impact on traffic flow control and vehicle emissions in a SUMO microscopic simulation on a high traffic demand scenario. The results support the observations of previous researchers on the significant dependence of VSL zone placement on VSL efficiency. Additionally, new data-based (traffic parame-ters and vehicle emissions) evidence of the performance of the SPSC-VSL design are provided regarding the best placement of consecutive VSL zones for motorway bottle-neck control not analysed in previous research.

Impact of Deep Reinforcement Learning on Variable Speed Limit strategies in connected vehicles environments

The Variable Speed Limit (VSL) control is considered in the context of connected vehicles acting as moving sensors, while their obedience to speed limit is enforced by a mandatory Intelligent Speed Adaptation (ISA) system. The objective of this study is to extend spatially static differential VSL control by introducing novel VSL strategies that are based on spatially dynamic speed limit zones. The spatial configuration of speed limit zones requires a novel traffic state representation based on the set of consecutive matrices which encode each vehicle position and speed within the controlled motorway during the control time step. The actions for all proposed VSL strategies are computed by the same Deep Reinforcement Learning (DRL) approach based on the Deep Deterministic Policy Gradient (DDPG) architecture. The DDPG learning models contain integration of Convolution and Long Short-Term Memory (LSTM) known as ConvLSTM layers, along with the Convolution and Fully Connected layers. Thus, those models can learn complex spatio-temporal traffic dynamics based on proposed traffic state representation. The results show that proposed VSL strategies have achieved higher overall motorway throughput compared to one which is based on the static speed limit zones and baseline cases (no-control and Simple Proportional Speed Controller algorithm). Simultaneously, they achieved a minimal increase in the number of aggressive braking, while the average headway is increased. All proposed VSL control approaches are simulated and analyzed by using a synthetic microscopic motorway model and characteristic traffic scenario for urban motorways.

Review of Methods for Estimating Construction Work Zone Capacity

Road reconstruction and the resulting work zones are considered as a major source of traffic congestion and delays on freeways. The roadway capacity is decreased as a result of a reduced number of traffic lanes, narrower lanes, and work zone speed limits. Accurate prediction of construction work zone capacity helps traffic engineers to have a better estimation of the traffic flow characteristics. To this end, multiple methodologies have been developed to quantify the impacts of work zones on traffic flow. This paper presents a critical review of the three types of approaches to estimating construction work zone capacities, including parametric, non-parametric, and simulation. Then the most commonly considered factors and their frequency are presented. It also performs a detailed review of the approaches, their objectives, and weaknesses. Lastly, it provides recommendations for future research. The presented work could help researchers in the area of work zone capacity estimation by presenting all the previous methodologies in one place.

Visual and Cognitive Impairments Differentially Affect Speed Limit Compliance in Older Drivers.

We test the hypothesis that clinical measures of age-related cognitive, visual, and mobility impairments negatively impact older driver speed limit compliance to advance method developments that improve older patient care and screen, identify, and advise at-risk older drivers. Real-world driver behaviors of older adults who had a range of cognitive, visual, and mobility abilities (measured with standardized, clinical tests) were assessed in environmental context (e.g., speed limit, traffic density, roadway type). Older driver speed limit compliance was measured in constant speed limit zones and at transition zones, where speed limits changed. A naturalistic driving study of older adults living around Omaha, Nebraska. Seventy-seven, legally licensed, active, and typically aging older drivers (65-90 years) who had a range of cognitive and visual abilities. Drivers typical, daily driving was continuously monitored for 3 months using sensor instrumentation installed in their own vehicles. At study start, each participant completed a comprehensive, standardized, clinical assessment of cognitive, visual, and mobility abilities relevant to aging and driving. Older drivers with greater cognitive impairment (P = .10) drove slower than drivers with less cognitive impairment, linking cognitive impairment to speed control. Drivers with greater visual impairment overall complied less with speed limit changes at transition zones (P = .01) and were more likely to comply with speed limit transitions when they occurred concurrently with changes in roadway features (P < .01). Results link clinical measures of age-related cognitive and visual impairment to impaired driver safety in real-world contexts. Real-world sensor data coupled with detailed, personalized older driver profiles can inform patients, caregivers, interventions, policy, and the design of supportive in-vehicle technology for at-risk older drivers.

The impact of injury on apparent survival of whale sharks (Rhincodon typus) in South Ari Atoll Marine Protected Area, Maldives

The whale shark (Rhincodon typus) is an endangered species with a declining global population. The South Ari Atoll Marine Protected Area (SAMPA), Maldives, is one of few locations globally where year-long residency of individuals occurs. This SAMPA aggregation appears to consist almost exclusively of immature males. Due to its year-round residency, this local aggregation is subjected to a high degree of tourism pressure. This ecotourism contributes to the high level of interest and protection offered to whale sharks by the local community. Unfortunately, if regulations are not followed or enforced, tourism can bring with it major stressors, such as accidental injuries. We used POPAN capture-mark-recapture models and lagged identification rate analysis to assess the effect of major injuries on whale shark residency within SAMPA. Injuries may be obtained outside SAMPA. We found individuals with major injuries had a higher apparent survival in the area than those without. Lagged identification rates also demonstrated that sharks with major injuries are more likely to return to the area. We suggest that major injuries result in sharks prolonging their time in the developmental habitat. These findings have implications for individual fitness and the population viability of this endangered species. We propose targeted conservation strategies be considered to protect sharks from further injury. Based on the presented spatio-temporal distributions of sharks, and current local knowledge of sighting patterns, speed limit zones and propeller-exclusion zones should be implemented and enforced. If carried out alongside tourist education, these measures will contribute to the protection of whale sharks within SAMPA and beyond. Furthermore, our results can aid research direction, alongside regulation and enforcement development, at similar sites worldwide.

Assessing driving behavior upstream of work zones by detecting response points in speed profile: A naturalistic driving study

Objective: To assess driving behavior when presented with different work zone features such as signs. Driving behavior upstream of a work zone is of interest since this is the point where drivers need to slow or react to upcoming conflicts such as lane closures, congested traffic, or presence of workers and equipment.Methods: Using 299 time series traces from four-lane roadways with both shoulder and lane closure scenario from the naturalistic driving study, this study analyzed driving behavior by detecting response points within the advance warning area from the first sign to the start of work zone. Response point was defined as the point where drivers reduced speed by a certain threshold. A mixed effect logistic model was developed to assess the relationship between driver response and work zone characteristics.Results: Results indicated the first work zone sign a driver encountered in the immediate area upstream of the work zone was not significantly likely to elicit a driver response. The model found lane ends, speed limit, and active changeable message signs (CMS) as statistically significant. Since more than one sign can be legible to the driver at the same time, the effect of overlapping signs was evaluated, but was not found to have significant effect on the driver response. In general, drivers were more likely to show a response to the signs the closer they got to the start of the work zone. Static work zone speed limit and dynamic speed feedback signs were both found to be more likely to elicit a response as compared to normal speed limit signs (non-work zone related). Drivers who were traveling over the posted speed limit were more likely to show response at any given work zone signs with the exception of the first sign. In addition, driver distraction, and driver information like age, gender, experience and other environmental factors were not found to be significant in the model.Conclusions: Overall, drivers were likely to show a response at the lane ends, work zone speed limit signs, and speed feedback signs.

Development of a Microsimulation Model for Motorway Roadworks With Narrow Lanes

This paper presents a newly developed microsimulation model for motorway roadwork sections to evaluate the efficiency of different temporary traffic management schemes (TTMSs) such as the use of narrow lanes, offside and inside lane closures. The effect on traffic performance of various parameters (e.g. flow rates, percentage of heavy goods vehicles (HGVs), roadwork zone lengths and speed limits) has been tested. The model was built using the FORTRAN programing language. It was developed based on car-following, discretionary lane changing, mandatory lane changing, gap acceptance and narrow lanes rules. Data from four sources (including data taken from different UK motorway sites) were collected and analyzed. The data were used in the verification, calibration and validation processes of the model. Observations from motorway roadwork sites with the narrow lanes scheme show certain prominent drivers’ behaviors, namely avoiding passing HGVs traveling on adjacent lanes and lane repositioning before passing a HGV. Such behaviors were included in the modeling process which suggested that the presence of HGVs had a noticeable impact on reducing section capacity.

Motorcyclists' beliefs of compliance with the Malaysian school zone speed limit (SZSL)

Many road crashes that occur in school zones involve child pedestrians. Research has identified three contributing factors to road crashes, namely child behaviour, driver behaviour, and the environment. This study aims to identify critical beliefs that influence motorcyclist's intention to comply with the Malaysian school zone speed limit (SZSL). 159 Malaysian motorcyclists who have travel experience in school zones during school hours and non-school hours were recruited by using purposive sampling. Participants responded to a survey distributed by enumerators in public places and house-to-house survey conducted in Kedah, Malaysia. Step-by-step correlation and regression analysis were used to identify the motorcyclists' critical beliefs. The results identified that motorcyclists' beliefs of the community expectation for them to comply and that complying with the speed limit in school zones may reduce risk of crashes with school children were the critical beliefs. In addition, the observation of many motorcyclists in the school zone was also identified as critical beliefs influencing motorcyclists' intention to comply with the SZSL. The practical relevance of this study is to combine a public awareness campaign and safety education for the motorcyclists together with an enforcement method to reinforce motorcyclists' compliance with the SZSL. Additionally, to increase the awareness level among motorcyclists, traffic control devices, such as flashing lights and yellow lines could be implemented.

Ecological Advanced Driver Assistance System for Optimal Energy Management in Electric Vehicles

Battery Electric Vehicles have a high potential in modern transportation, however, they are facing limited cruising range. The driving style, the road geometries including slopes, curves, the static and dynamic traffic conditions such as speed limits and preceding vehicles have their share of energy consumption in the host electric vehicle. Optimal energy management based on a semi-autonomous ecological advanced driver assistance system can improve the longitudinal velocity regulation in a safe and energy-efficient driving strategy. The main contribution of this paper is the design of a realtime risk-sensitive nonlinear model predictive controller to plan the online cost-effective cruising velocity in a stochastic traffic environment. The basic idea is to measure the relevant states of the electric vehicle at runtime, and account for the road slopes, the upcoming curves, and the speed limit zones, as well as uncertainty in the preceding vehicle behaviour to determine the energy-efficient velocity profile. Closed-loop Entropic Value-at-Risk as a coherent risk measure is introduced to quantify the risk involved in the system constraints violation. The obtained simulation and field experimental results demonstrate the effectiveness of the proposed method for a semi-autonomous electric vehicle in terms of safe and energy-efficient states regulation and constraints satisfaction.

School zone safety modeling in countermeasure evaluation and decision

ABSTRACTSafety of school zone areas has been an important topic in the transportation field because the school zones might cause a risk for the school-aged pedestrians and bicyclists, and motorists due to many types of travel activities near schools. This paper assessed the safety effects of roadway features in school zone areas by exploring the performance of five different types of alternative crash prediction models. The results indicated that the random effects Poisson inverse Gaussian (REPIG) models provide the most accurate crash predictions. Moreover, the results showed that increasing shoulder and lane widths, installation of flashing beacon at school zone speed limit sign, and decreasing the number of driveways were safety effective in reducing crash frequency at school zone areas. The findings from this study offer transportation practitioners and policymakers a dependable reference to enhance safety in schools based on the empirical evidence.

The effectiveness of new 3D visual effect speed hump in speed reduction

Intersection is a function of parsing and altering traffic movement. The safety of vehicle manoeuvres at the junction depends on the minimum speed. The purpose of this study is to identify the effectiveness of the usage of temporary speed hump (3D visual effect) to reduce vehicles speed approaching a Priority Junction. This study was conducted at three (3) different residential locations namely Taman Murni, Kampung Merdeka and Taman Bahagia Koperasi in Batu Pahat area. These intersections were chosen because it connects one housing area to another and acts as a short-pass to a destination. Based on the observational activity, there were some traffic conflicting and potential for accidents at the intersection as well. The speed data were collected using laser guns and filled into special forms including date, location, weather, start and end time of observation and also the category of vehicles passed through the intersection. A hypothesis test was conduct to analyze the vehicle speed data before and after installation of the temporary a new 3D visual effect of speed hump. The results were analyzed using the Chi-Square test in Statistical Package for Science Social (SPSS) software. The Chi-Square analysis demonstrates that the effectiveness of using temporary a new 3D visual effect of speed hump is significant statistically (p&lt;0.05, χ2== 291.575). Majority vehicles (74%) were complied with speed limit when approaching intersection compared to 26% of vehicles who do not to do so. In addition, there was decline in the number of uninterrupted vehicles can be seen after parking traffic. Therefore, the study confirmed that drivers who speeding over the speed limit zones before approaching the intersection might be intervened after the installation of the new 3D visual effect of speed hump.

Speed Dictators For Forced Speed Limit At Critical places Using Low Cost RF Transceivers with Integrated Immobilizer

An intention to work on the topic of this nature is emanated from the interest to explore alternative technological solution to achieve effective speed control. Objective of the study is to design and develop a new system that can effectively detect speed violations on the road and supports the driver to obey traffic rules while driving by maintaining the speed according to the speed limit prescribed. In the present day scenario traffic rules are frequently violated by the drivers and over speeding occur due to bad driving behavior. So, a driver assistance system is provided to prevent over speeding, violation of road rules and also to display alert messages. The proposed system has an alerting, recording and reporting system for over speed violation management. The proposed system automatically controls the speed of vehicles at speed restricted areas such as school and hospitals. The main reason behind developing this project is to avoid accident of vehicles at speed limit zones and also to help the passengers to cross the road safely without facing any danger from high speed vehicles. Normally, the vehicle drivers not consider the passengers who crosses road in speed limited areas and drive their vehicles at high speed. So, now accidents are increasing in these areas. The traffic police control the traffic but they are not able to avoid the accidents completely. To solve this problem we developed the proposed system, which not interrupts the vehicle drivers and controls the speed of the vehicles up to certain limit in these speed restricted zones. The LCD displays the lane speed limit. Even though the traffic police controls them we cannot achieve full response from them. Also it is not possible to monitor those areas at all time to regulate their speed. This project is very useful for the common people to walk safely in the roads of speed restricted zones¬¬ and also drivers can ride their vehicles safely.

Dynamic Speed Adaptation for Path Tracking Based on Curvature Information and Speed Limits.

A critical concern of autonomous vehicles is safety. Different approaches have tried to enhance driving safety to reduce the number of fatal crashes and severe injuries. As an example, Intelligent Speed Adaptation (ISA) systems warn the driver when the vehicle exceeds the recommended speed limit. However, these systems only take into account fixed speed limits without considering factors like road geometry. In this paper, we consider road curvature with speed limits to automatically adjust vehicle’s speed with the ideal one through our proposed Dynamic Speed Adaptation (DSA) method. Furthermore, ‘curve analysis extraction’ and ‘speed limits database creation’ are also part of our contribution. An algorithm that analyzes GPS information off-line identifies high curvature segments and estimates the speed for each curve. The speed limit database contains information about the different speed limit zones for each traveled path. Our DSA senses speed limits and curves of the road using GPS information and ensures smooth speed transitions between current and ideal speeds. Through experimental simulations with different control algorithms on real and simulated datasets, we prove that our method is able to significantly reduce lateral errors on sharp curves, to respect speed limits and consequently increase safety and comfort for the passenger.

Intention to comply with the school zone speed limit: Scenario-based study

This study assessed the ability of the extended Theory of Planned Behavior (TPB) to account for motorcyclists' intentions to comply with the school zone speed limit (SZSL) in 2 specific scenarios: presence of other drivers driving and the presence of school children in a school zone. A sample of motorcyclists (N=634) was surveyed with a questionnaire constructed to measure attitudes toward behaviors, subjective norms, perceived behavioral control, habit, personal norm and behavioral intentions. Results showed that the scenarios affect the motorcyclist attitude, habit and personal norm. In particular, with the presence of school children in a school zone, attitude and personal norm became significant predictors of intention to comply. In contrast, with the other drivers driving in the school zone and no school children around that area, attitude and habit were the significant predictor towards intention to comply. The relation between attitude and behavioral intentions was consistently stronger between the two scenarios.

The Effect of Sign Saturation on Driver Speed Limit Compliance in School Zones

School zone sign saturation can be defined as the density of the school zones around a reference school zone. This study investigated the effect of school zone sign saturation on vehicle speed and compliance to school zone speed limit. Based on the models of human information processing, the presence of too many school zone signs in a given area could lead to inattention or lack of attention to those signs leading to a non-compliance of the speed limit in school zones. To investigate the effect of sign saturation, vehicle speed data was collected in four school zones. Results found that the vehicle speed is significantly lower and compliance is significantly higher in high saturation school zones.