Assessment of Drivers’ Perceptions of Various Police Enforcement Strategies and Associated Penalties and Rewards

Road crashes are a major cause of death in many countries. Qatar has been battling to improve road safety on several fronts using different strategies, including road policing. The purpose of this study is to ascertain drivers’ perceptions towards five existing and four proposed police traffic enforcement strategies and associated penalties and rewards in Qatar using face-to-face surveys. The results show that red-light running cameras were perceived to be the most successful existing strategy. The high violation fine and the automation of the system were mentioned as the main reasons for making this strategy the most successful. Three of the existing strategies, fixed-speed enforcement cameras, police enforcement, and mobile speed cameras, were conferred almost the same success percentage, followed by the demerit point system. Regarding the proposed strategies, rewarding safe drivers was selected by the participants as the most successful proposed strategy, followed by introducing more automated enforcement methods. Community service for traffic tickets came in third, followed by defensive driving school. These results can be used to influence future enhancements of existing strategies and guide the development of future traffic strategies being introduced in the traffic system.

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Evaluation of a Public Technology-Based Traffic Enforcement Program

Sustainability ◽

10.3390/su132111966 ◽

2021 ◽

Vol 13 (21) ◽

pp. 11966

Author(s):

Gila Albert ◽

Dimitry Bukchin ◽

Tomer Toledo

Keyword(s):

Red Light ◽

Evaluation Process ◽

Traffic Enforcement ◽

Unique Type ◽

Red Light Running ◽

Rigorous Evaluation ◽

Video Recordings ◽

Traffic Violations ◽

Police Enforcement ◽

Simple Technology

While police enforcement is a well-known means of reducing traffic violations, it is also recognized that other agents should be involved in creating sustainable deterrence. This paper describes and evaluates the Israeli Road Guards program, a new and unique type of traffic enforcement, which enables simple technology-based enforcement of traffic violations by citizens. In its 24 months of operation, more than 3400 volunteers who submitted over 64,000 violation reports were involved in this program. Each report went through a rigorous evaluation process. More than 80% of the submitted reports were rejected in the various stages of the procedure. In 13.7% of the cases a notice letter was sent, and in 4.3% of cases (reflecting the most severe offenses) a citation was issued by the police. The monthly rate of report submission by the volunteers was at its highest initially, then decreased and stabilized after about six months at 1.4 reports per month. The proportion of active volunteers also decreased over time to a level of 0.26 at the end of the study period. The violation types reported within the program differed substantially from those captured by police enforcement. These differences are likely due to the manner in which each mode of enforcement was performed. The most common violations reported by volunteers were lane deviations, red light running and driving on the roads’ shoulders, which are easily documented by means of video recordings. They are also associated with higher crash risks. Thus, the results show that such public technology-based traffic enforcement, which can be carried out during regular daily driving and does not require anyone to make extra trips, may efficiently complement traditional police enforcement.

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Road safety risk factors for non-motorised vehicle users in a Chinese city: an observational study

Injury Prevention ◽

10.1136/injuryprev-2018-043071 ◽

2019 ◽

Vol 26 (2) ◽

pp. 116-122 ◽

Cited By ~ 2

Author(s):

Qingfeng Li ◽

Sile Yu ◽

Ting Chen ◽

David M Bishai ◽

Abdulgafoor Bachani ◽

...

Keyword(s):

Comprehensive Evaluation ◽

Red Light ◽

National Standards ◽

Road User ◽

Intervention Package ◽

Red Light Running ◽

Helmet Use ◽

Cox Proportional Hazard ◽

Design Speed ◽

Speed Enforcement

ObjectiveThe objective of this study is to describe and analyse the prevalence of speeding, helmet use and red-light running among riders of non-motorised vehicles (NMVs) in Shanghai, China, with a focus on electric bikes (ebikes).MethodsObservational studies were conducted in eight randomly selected locations in Shanghai. Descriptive statistics and a Cox proportional hazard (PH) model were used in the analyses.FindingsA total of 14 828 NMVs were observed in November 2017. At the free flow sites, the average speed was 22.5 km/hour for ebikes and 13.4 km/hour for bicycles. 95.5% of ebikes run above 15 km/hour, the legal speed limit for NMVs in China and 83.8% above 20 km/hour, the maximum design speed for ebikes. Helmet wearing rate was 13.5% for ebike drivers and 9.4% for passengers. Riders of commercial ebikes were nearly three times more likely to wear a helmet than personal ebikes. 22.4% of ebikes were observed to run a red light. The Cox PH model showed that ebikes (vs bicycles), males (vs females), clear weather (vs cloudy, rainy and snowy), helmet users (vs nonusers) are associated with a higher hazard for running a red light.ConclusionTo our knowledge, this study is among the first comprehensive evaluation of road user behaviours for NMVs in China. An effective intervention package including regulating ebike production to national standards, strengthening speed enforcement and passing legislation on mandatory helmet use for ebike users may be able to help.

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Perancangan Sistem Kontrol Lampu Lalulintas Cerdas Dengan Menggunakan Mikrokontroler dan Kamera

Jurnal MIPA ◽

10.35799/jmuo.8.3.2019.26198 ◽

2019 ◽

Vol 8 (3) ◽

pp. 200

Author(s):

Tjerie Pangemanan ◽

Arnold Rondonuwu

Keyword(s):

Real Time ◽

Digital Image ◽

Red Light ◽

Green Light ◽

Processing Method ◽

Traffic Lights ◽

Traffic System ◽

Road Users ◽

Adjustment System ◽

System Time

Masalah lalu lintas merupakan salah satu masalah yang sangat sulit diatasi dengan hanya menggunakan system waktu (timer). Oleh sebab itu diperlukan suatu system pengaturan otomatis yang bersifat real-time sehingga waktu pengaturan lampu lalu lintas dapat disesuaikan dnegan keadaan di lapangan. Penelitian ini bertujuan mengembangkan suatu simulasi sistem yang mampu mengestimasi panjang antrian kendaraan menggunakan metoda pengolahan citra digital hanya dengan menggunakan satu kamera untuk dijadikan parameter masukan dalam menghitung lama waktu nyala lampu merah dan lampu hijau. Oleh karena itu, sistem lalulintas sangatlah diperlukan, sebagai sarana dan prasarana untuk menjadikan lalulintas lancar, aman, bahkan sebagai media pembelajaran disiplin bagi masyarakat pengguna jalan raya. Penelitian ini penulis menggunakan sistem pengontrolan berbasis citra digital dimana camera sebagai sensor. Untuk aplikasi dari semua metode dalam penelitian ini digunakan Microcontroller AurdinoTraffic problems is one of the problems that is very difficult to overcome by only using the system time (timer). Therefore we need an automatic real-time adjustment system so that the time settings for traffic lights can be adjusted according to the conditions on the ground. This study aims to develop a system simulation that is able to estimate the length of the vehicle queue using a digital image processing method using only one camera to be used as input parameters in calculating the length of time the red light and green light. Therefore, the traffic system is very necessary, as a means and infrastructure to make traffic smooth, safe, even as a medium for disciplined learning for road users. In this study the authors used a digital image-based control system where the camera as a sensor. For the application of all methods in this study, Aurdino Microcontroller is used

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Autonomous Vehicles and Vulnerable Road-Users—Important Considerations and Requirements Based on Crash Data from Two Countries

Behavioral Sciences ◽

10.3390/bs11070101 ◽

2021 ◽

Vol 11 (7) ◽

pp. 101

Author(s):

Andrew Paul Morris ◽

Narelle Haworth ◽

Ashleigh Filtness ◽

Daryl-Palma Asongu Nguatem ◽

Laurie Brown ◽

...

Keyword(s):

Autonomous Vehicles ◽

Red Light ◽

Road User ◽

Red Light Running ◽

Crash Data ◽

Passenger Vehicles ◽

Road Users ◽

Vulnerable Road User ◽

Vulnerable Road Users ◽

Road Intersections

(1) Background: Passenger vehicles equipped with advanced driver-assistance system (ADAS) functionalities are becoming more prevalent within vehicle fleets. However, the full effects of offering such systems, which may allow for drivers to become less than 100% engaged with the task of driving, may have detrimental impacts on other road-users, particularly vulnerable road-users, for a variety of reasons. (2) Crash data were analysed in two countries (Great Britain and Australia) to examine some challenging traffic scenarios that are prevalent in both countries and represent scenarios in which future connected and autonomous vehicles may be challenged in terms of safe manoeuvring. (3) Road intersections are currently very common locations for vulnerable road-user accidents; traffic flows and road-user behaviours at intersections can be unpredictable, with many vehicles behaving inconsistently (e.g., red-light running and failure to stop or give way), and many vulnerable road-users taking unforeseen risks. (4) Conclusions: The challenges of unpredictable vulnerable road-user behaviour at intersections (including road-users violating traffic or safe-crossing signals, or taking other risks) combined with the lack of knowledge of CAV responses to intersection rules, could be problematic. This could be further compounded by changes to nonverbal communication that currently exist between road-users, which could become more challenging once CAVs become more widespread.

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Real-Time Prediction of Vehicle Trajectories for Proactively Identifying Risky Driving Behaviors at High-Speed Intersections

Transportation Research Record Journal of the Transportation Research Board ◽

10.1177/0361198118797211 ◽

2018 ◽

Vol 2672 (38) ◽

pp. 233-244 ◽

Cited By ~ 1

Author(s):

Chaopeng Tan ◽

Nan Zhou ◽

Fen Wang ◽

Keshuang Tang ◽

Yangbeibei Ji

Keyword(s):

Phase Transition ◽

High Speed ◽

Red Light ◽

Risky Behaviors ◽

Risky Driving ◽

Red Light Running ◽

Driving Behaviors ◽

Vehicle Trajectories ◽

Single Vehicle ◽

Risky Driving Behaviors

At high-speed intersections in many Chinese cities, a traffic-light warning sequence at the end of the green phase—three seconds of flashing green followed by three seconds of yellow—is commonly implemented. Such a long phase transition time leads to heterogeneous decision-making by approaching drivers as to whether to pass the signal or stop. Therefore, risky driving behaviors such as red-light running, abrupt stop, and aggressive pass are more likely to occur at these intersections. Proactive identification of risky behaviors can facilitate mitigation of the dilemma zone and development of on-board safety altering strategies. In this study, a real-time vehicle trajectory prediction method is proposed to help identify risky behaviors during the signal phase transition. Two cases are considered and treated differently in the proposed method: a single vehicle case and a following vehicle case. The adaptive Kalman filter (KF) model and the K-nearest neighbor model are integrated to predict vehicle trajectories. The adaptive KF model and intelligent driver model are fused to predict the following vehicles’ trajectories. The proposed models are calibrated and validated using 1,281 vehicle trajectories collected at three high-speed intersections in Shanghai. Results indicate that the root mean square error between the predicted trajectories and the actual trajectories is 5.02 m for single vehicles and 2.33 m for following vehicles. The proposed method is further applied to predict risky behaviors, including red-light running, abrupt stop, aggressive pass, speeding pass, and aggressive following. The overall prediction accuracy is 95.1% for the single vehicle case and 96.2% for the following vehicle case.

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Prediction of Red Light Running Based on Statistics of Discrete Point Sensors

Transportation Research Record Journal of the Transportation Research Board ◽

10.3141/2128-14 ◽

2009 ◽

Vol 2128 (1) ◽

pp. 132-142 ◽

Cited By ~ 23

Author(s):

Liping Zhang ◽

Kun Zhou ◽

Wei-bin Zhang ◽

James A. Misener

Keyword(s):

Red Light ◽

Discrete Point ◽

Red Light Running

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Evaluation of Automated Enforcement Program in Amman

Periodica Polytechnica Transportation Engineering ◽

10.3311/pptr.10939 ◽

2018 ◽

Author(s):

Hana Naghawi ◽

Bushra Al Qatawneh ◽

Rabab Al Louzi

Keyword(s):

Traffic Safety ◽

Questionnaire Survey ◽

Positive Impact ◽

Red Light ◽

Crash Frequency ◽

Red Light Running ◽

Red Light Cameras ◽

Percent Confidence Level ◽

Before And After ◽

Traffic Violations

This study aims, in a first attempt, to evaluate the effectiveness of using the Automated Enforcement Program (AEP) to improve traffic safety in Amman, Jordan. The evaluation of the program on crashes and violations was examined based on a “before-and-after” study using the paired t-test at 95 percent confidence level. Twenty one locations including signalized intersections monitored by red light cameras and arterial roads monitored by excessive speed cameras were selected. Nine locations were used to study the effectiveness of the program on violations, and twelve locations were used to determine the effectiveness of the program on frequency and severity of crashes. Data on number and severity of crashes were taken from Jordan Traffic Institution. Among the general findings, it was found that the AEP was generally associated with positive impact on crashes. Crash frequency was significantly reduced by up to 63%. Crash severities were reduced by up to 62.5%. Also, traffic violations were significantly reduced by up to 66%. Finally, drivers’ opinion and attitude on the program was also analyzed using a questionnaire survey. The questionnaire survey revealed that 35.5% of drivers are unaware of AEP in Amman, 63.9% of drivers don’t know the camera locations, most drivers knew about excessive speed and red light running penalties, most drivers reduce their speed at camera locations, 44.4% of drivers think that the program satisfies its objective in improving traffic safety and 52% of drivers encourage increasing the number of camera devices in Amman.

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