Traffic Regulations Research Articles

The Impact of Traffic Law Enforcement Regulations on the Incidence and Severity of Maxillofacial Injuries.

This study aimed to assess the effectiveness of the new traffic law enforcement regulations (TLERs) on the incidence and severity of maxillofacial injuries in Oman, as road traffic accidents (RTAs) are the main cause of facial injuries in Oman. A retrospective longitudinal analytic study was conducted at three tertiary care hospitals in Muscat, Oman. All patients with RTA-related maxillofacial injuries during a five-year period from January 2005 to December 2009 (before the new TLERs) and the five-year period from January 2015 to December 2019 (after the new TLERs) were included in the study. A total of 1,127 patients were included in the study. Of these, 646 (57.3%) patients sustained RTA-related maxillofacial injuries before the implementation of the new TLERs compared to 481 (42.7%) after the introduction of TLERs. No significant gender-based difference was found between the two study periods. The incidence of injury before the implementation of the new TLERs was 22.7 per 100,000 population, which then reduced significantly to 11 per 100,000 after the TLERs were implemented. Overall, the mean facial injury severity score reduced significantly, from 3.2 to 2.3, after the implementation of the new TLERs. The findings of this study indicate that the newly introduced TLERs have resulted in a reduction in the incidence and severity of RTA-related maxillofacial injuries. Continuous improvement and reinforcement of TLERs will further help reduce the burden of these injuries to society in general and health services in particular.

Decision-Making Method of Autonomous Vehicles in Urban Environments Considering Traffic Laws

In order to improve the efficiency and safety of autonomous vehicles’ decision-making process in complex urban scenarios, a decision-making method for hierarchical processing of static traffic law information and dynamic traffic participant information is proposed in this paper. In the decision-making method, the candidate behavior set is constructed by extracting the element of traffic laws and fully considering the traffic laws constraints to ensure the legality and effectiveness of the decision-making algorithm. Besides, four evaluation indicators and two-level entry threshold are designed to select the optimal driving behavior with the consideration of driving efficiency, ride safety and macro path requirement. The advantage of proposed method is that it avoids the problem of poor adaptability to traffic laws and regulations as the existing methods usually make decisions under the condition of mixed traffic laws and traffic participant information. A complete driving task simulation and analysis, including six typical urban traffic scenarios, is given under Matlab environment. The results show that the proposed decision-making method is able to make reasonable and feasible decisions and highly consistent with the actual driver’s decision-making behavior in complex urban scenarios, which verifies the effectiveness of the proposed method.

Lunar landing necessary building blocks and good practices for a sustainable development of human lunar activities

After almost 50 years from the last step on the Moon in 1972, Space Agencies and companies from all over the World are evaluating once again the need, potential, and benefits of human settlements on the Moon and beyond. Several spacecraft, landers, and rovers have already made their way on Earth’s only natural satellite, and more will come in the coming years, followed by or in parallel with human missions, with all the related challenges and issues to overcome. At first, Human activities will target specific locations on the lunar surface, mainly driven by scientific objectives. For these missions, the landing site will necessarily be close to the target areas until a surface transport infrastructure is put in place, such as a system of transport rovers or a rail network. As the interest and involvement of public and private actors grow, and depending on their mission objectives, we will see either massive landings with multiple spacecraft involved or specific pinpointed landings with relatively small assets, to perform local analyses without the need to bring a full settlement to the location. Therefore, it is fundamental to see which resources/terrain characteristics will act as an attractor for intensive human activities with multiple landings that will need traffic management regulations. One of the objectives of our research is to analyze those potential attractors and identify key factors that would make specific locations of the Moon more suitable for landing (e.g. surface characteristics, distance from points of interest). Once defined, the following objective is to evaluate what features and services a landing site should have in order to support exploration or exploitation missions and become an efficient spaceport. In parallel, as mentioned above, all these activities on and around the Moon’s surface need to be regulated and coordinated to avoid a “far west” scenario, with the related potential hazards that could affect the lunar environment, human settlements, and facilities. The last objective of our project is to evaluate and propose ideas on how future missions could be regulated, taking into account that the Moon is a different celestial body that, at the current moment, is not under any national or international significant traffic management regulation. The present abstract is submitted under the auspices of Space Generation Advisory Council (SGAC) Technical Unit Research for a Thriving Lunar Ecosystem (TURTLE).

RISK FACTORS ANALYSIS OF WORK FATIGUE AMONG ONLINE MOTORCYCLE DRIVERS IN SOUTH TANGERANG CITY

Online motorcycle taxi drivers are one the road users, it is important to obey traffic regulations. In UU No. 22 2009 it is mentioned that the driver of the vehicle must be conscious and not distracted because of tiredness, this situation can cause traffic accidents if forced to keep driving. The purpose of this study is to analyze what factors are related to work fatigue that occurs in online drivers in South Tangerang City in 2022. The research method used in this study is a literature review. The data used are secondary data from scientific articles/journals, books, and documents. Search literature on internet sites such as Scopus, Google Scholar, Garuda, and College Journals. The research was conducted on 3 international articles and 2 national articles. The results of the study based on these five articles, after summarizing the findings of ten (10) risk factors related to work fatigue in online motorcycle taxi drivers, namely age, duration of work, total distance achieved, history of illness, length of sleep, over time, work stress, lack of physical activity, and marital status. This research is recommended for companies to further improve the welfare of online motorcycle taxi drivers by reducing income deductions, calculating basic costs and authorized capital issued by online motorcycle taxi drivers, there are some complaints by online motorcycle taxi drivers, namely working unhealthy in pursuit of bonuses, this has an impact on working hours that are too high so that it can cause work fatigue for online motorcycle taxi drivers.

The Characteristics of Mandibular Fracture In Rsup Dr. Hasan Sadikin General Hospital Bandung, Indonesia

Introduction Mandibular fracture poses a fatal complication because the mandible plays an essential role in occlusion and aesthetics. The mandible is one of the bones most affected by facial fractures commonly resulting from trauma to the face and may be associated with severe morbidity and serious consequences Methods The records of 282 patients referred to RSUP Dr. Hasan Sadikin General Hospital Bandung, Indonesia between January 2017 and January 2021 were analysed retrospectively. Data including age, sex, etiology of mandibular fracture, type of mandibular fracture, and treatment. Incompleted data from the medical record were excluded. Results Men aged 17-30 years were the most common victims of mandibular fracture. Road traffic accidents (RTAs) were responsible in 84% of cases. The most common anatomic site for mandibular fracture was parasymphysis region 28.7 with simple fractures 79%, and 82% of the total fractures were treated with open reduction Conclusion The characteristics of mandibular fracture patients describe trauma patterns in the community. This finding is similar with some readily available literature with RTAs was the most common etiology and parasymphysis was the most common fracture site. Reasons for this high frequency may include the large number of poorly maintained, overloaded vehicles on unsuitable roads, violation of traffic regulations particularly by inexperienced young drivers. Keywords: Fractures, Mandibular, Parasymphisis, Reduction

Fuzzy Ontology-Based System for Driver Behavior Classification.

Intelligent transportation systems encompass a series of technologies and applications that exchange information to improve road traffic and avoid accidents. According to statistics, some studies argue that human mistakes cause most road accidents worldwide. For this reason, it is essential to model driver behavior to improve road safety. This paper presents a Fuzzy Rule-Based System for driver classification into different profiles considering their behavior. The system’s knowledge base includes an ontology and a set of driving rules. The ontology models the main entities related to driver behavior and their relationships with the traffic environment. The driving rules help the inference system to make decisions in different situations according to traffic regulations. The classification system has been integrated on an intelligent transportation architecture. Considering the user’s driving style, the driving assistance system sends them recommendations, such as adjusting speed or choosing alternative routes, allowing them to prevent or mitigate negative transportation events, such as road crashes or traffic jams. We carry out a set of experiments in order to test the expressiveness of the ontology along with the effectiveness of the overall classification system in different simulated traffic situations. The results of the experiments show that the ontology is expressive enough to model the knowledge of the proposed traffic scenarios, with an F1 score of 0.9. In addition, the system allows proper classification of the drivers’ behavior, with an F1 score of 0.84, outperforming Random Forest and Naive Bayes classifiers. In the simulation experiments, we observe that most of the drivers who are recommended an alternative route experience an average time gain of 66.4%, showing the utility of the proposal.

Analysis of Korean Road Traffic Regulations to Establish Legal Layer for Evaluating Safety of Autonomous Driving

Currently, many governments, global automakers, and IT companies have been showing increasing interest in autonomous vehicles (AVs). Therefore, the research, development, and testing of AVs are underway worldwide and the development of scenarios for AV safety evaluation is emerging as an urgent issue in various nations and institutions. However, in Korea, research on an appropriate legal system for AVs is necessary because the existing one is insufficient for the development of a scenario for evaluating autonomous driving safety. In this study, the present legal system related to autonomous driving in Korea was selected to establish a five-layer format-based autonomous driving scenario for the PEGASUS project. The possibility of the expansion and improvement of the methodology was proposed by conducting a legal system analysis. Finally, an analysis of the related legal provisions for each layer was conducted to highlight the necessity of a legal system that is suitable for the era of autonomous driving in the future.

Load Effect of Automated Truck Platooning on Highway Bridges and Loading Strategy.

Automated truck platooning (ATP) has gained growing attention due to its advantage in reducing fuel consumption and carbon emissions. However, it poses serious challenges to highway bridges due to the load effect of multiple closely spaced heavy-duty trucks on the bridge. In China, ATP also has great application prospects in the massive and ever-increasing highway freight market. Therefore, the load effects of ATP on bridges need to be thoroughly investigated. In this study, typical Chinese highway bridges and trucks were adopted. ATP load models were designed according to the current Chinese road traffic regulations. The load effects of ATP on highway bridges were calculated using the influence line method and evaluated based on the Chinese bridge design specifications. Results show that the load effect of ATP on bridges increases with the increase in the gross vehicle mass and the truck platooning size but decreases with the increasing inter-truck spacing and the critical wheelbase. The Grade-I (best quality standard) highway bridges are generally capable of withstanding the ATP loads, while caution should be exercised for other bridges. Strategies for preventing serious adverse impacts of ATP load on highway bridges are proposed.

Fleet management and control system for developing countries implemented with Intelligent Transportation Systems (ITS) services

Fleet Management Control Systems (FMCS) monitor vehicles in real-time and help assessing schedule compliance. Transit services in developing countries must improve in aspects such as information about routes, schedules and users; and compliance with traffic regulations, to achieve an increase in their demand. Although a FMCS can deal with these issues, currently implemented systems have some limitations related to communications technology, associated costs, interoperability and standardization. This paper includes the following: 1) The Intelligent Transportation System (ITS) architecture designed for the FMCS; 2) The development of a FMCS prototype for developing countries, considering the proposed architecture, using the Long Range communication technology and Intelligent Transportation Systems services; 3) A validation and testing of the FMCS prototype, using transit vehicles in a city. The developed prototype was successfully tested. The ideal operating parameters of the FMCS in terms of communications technology were identified in one of the four routes used in the tests. The results in such route were validated with additional tests, using the same parameters, and reaching similar operating values. A data set with the information of the performed tests was generated. With the results obtained in the FMCS, a better control of the transit service can be achieved, helping to improve upon the problems identified for developing countries (especially in medium-sized cities) related to route and schedule compliance, speeding, safety, standardization and helpful information for users. Additionally, service operation costs are reduced by using cutting-edge communications technology and promoting interoperability with other mobility services created for these cities.

How more data reinforces evidence-based transport policy in the Short and Long-Term: Evaluating a policy pilot in two Dutch cities

Data have played a role in urban mobility policymaking for decades. Especially since the emergence of big data, many researchers have shown how to advance data use to improve understanding transport policy effects, but there is hardly insight in how this is adopted in policy practice. This study aims to address this gap by answering two questions: (1) how is data currently embedded in urban mobility policy- and decision-making; and (2) what are the advantages and limitations of more data use in these processes?We chose two Dutch cities -Maastricht and Groningen-that were both involved in a national programme (BeterBenutten) that trialed (and funded) a more evidence-based policymaking approach. We did ten semi-structured interviews with the people work in the mobility department and analyzed the twenty-one most relevant policy reports to understand how more data reinforces/impedes transport policymaking in practice. We found that data use differed in long-term and short-term policy cycles. In the long-term policy cycle, data was regarded as less important than political and societal trends and developments; in the short-term cycle, data played a major role in prompting traffic regulations and policy adjustments.Policy insights can be derived from this research on how data can be better embedded in policymaking practices (1) The support from national/regional level (i.e. BeterBenutten program): could provide extra opportunities for local governments to do ex-post policy assessments, which has been regarded as valuable resources for evidence-based decision-making by policymakers. (2) Survey data can still play a significant role in urban mobility planning by typically providing more insights in the ‘why’ of traveler behaviors than big data. (3) Transport policymakers need to strength their abilities in selecting suitable data (out of a much larger set) and having more (competent) personnel capacity to interpret data. (4) Promoting sustainable mobility is a strong driving force for the local governments to enhance data use.

Pedaling through a virtually redesigned city: Evaluation of traffic planning and urban design factors influencing bicycle traffic

To achieve the 1.5-degree target of the Paris Climate Agreement, it is of great importance to promote environmentally friendly means of transport. In urban areas, shifting motorized trips to active transport modes (i.e., walking and cycling) is essential. Therefore, knowledge of walking and cycling is indispensable for planning and policy, which is the basis for targeted promotion of active forms of mobility. This paper aims to identify factors that specifically influence cycling and to derive recommendations for action for planning and policy in a virtual testbed. Specifically, the influence of traffic planning measures (i.e., structural infrastructure facilities for stationary and moving traffic as well as traffic regulations) and urban design measures (i.e., the design of public space) on the promotion of cycling will be shown. For this purpose, a virtual reality simulation was used, independent of different external conditions during field surveys and the necessity of time-, cost- and regulation-intensive structural changes. Using an improved bicycle simulator, 93 people cycled through 20 variations of an approximately 680 m long road section, surveying the effect of selected traffic planning and urban design parameters. Special attention was paid to the subjective safety of the cyclists and the attractiveness of the urban environment. Furthermore, three types of infrastructure were differentiated: No bicycle infrastructure (riding on the roadway), a bicycle lane, and a structurally separated cycle path next to the sidewalk. The virtual road section represented a real location. In addition to the findings gained from the physiological optimization of the simulator, the results show that roadside greenery had the highest effectiveness in terms of subjective safety and attractiveness. Other factors with a high influence were a speed reduction from 50 to 30 km/h when riding on the roadway with cars and the red coloring of the bicycle lane, each increasing the perception of safety. In contrast, a lack of a boundary line between the cycle path and the sidewalk was unsettling for those who rarely or never ride bicycles in their daily lives. In addition, restaurant and recreation areas increased the attractiveness of the road section, although entailing a lower perception of safety. Other factors, such as motor vehicle traffic volume or vehicles parked at the roadside, showed no significant effects on the evaluation of cycling.With the help of these findings, the consequences of traffic planning and urban design measures can be better assessed in subsequent virtual testbeds. Also, initial trends can be identified as to which planning instruments should be used as a priority to promote cycling in urban areas. Future work should validate the transfer of these insights into physical urban spaces to support further the mid-term transformation towards sustainable urban mobility using scientific evidence.

A 2-Phase Method for Solving Transportation Problems with Prohibited Routes

The Transportation Problem (TP) is a mathematical optimization technique which regulates the flow of items along routes by adopting an optimum guiding principle to the total shipping cost. However, instances including road hazards, traffic regulations, road construction and unexpected floods sometimes arise in transportation to ban shipments via certain routes. In formulating the TPs, potential prohibited routes are assigned a large penalty cost, M, to prevent their presence in the model solution. The arbitrary usage of the big M as a remedy for this interdiction does not go well with a good solution. In this paper, a two-phase method is proposed to solve a TP with prohibited routes. The first phase is formulated as an All-Pairs Least Cost Problem (APLCP) which assigns respectively a non-discretionary penalty cost M*ij <= M to each of n prohibited routes present using the Floyd¢s method. At phase two, the new penalty values are substituted into the original problem respectively and the resulting model is solved using the transportation algorithm. The results show that, setting this modified penalty cost ( M*) logically presents a good solution. Therefore, the discretionary usage of the M <= ∞ is not a guarantee for good model solutions. The modified cost M*<= M so attained in the sample model, is relatively less than the Big M ( <= ∞) and gives a good solution which makes the method reliable.

Local Law Enforcement Variables as Moderating Effect on the Behavior of Foreign Motorcycle Riders in Tourism Areas in Bali

Foreign motorcyclists are prone to greater risks than the locals in most countries worldwide [1]. Risk parameters identified include lack of knowledge of traffic regulations, inadequate driving skills, different seasons, and general attitudes towards traffic safety reflected in driving behavior [2]. Along with tourism development, the number of foreign motorcyclists also increases. Therefore, safety measures are essential [3]. In this research, by using data collected from 71 foreign motorcyclists as respondents, we study the influence of local road and traffic conditions, human factors, and local law enforcement on the behavior of foreign motorcyclists around tourist areas in Bali. The method used is Structural Equation Modeling (SEM). The expected contribution is a model that finds how local law enforcement affects foreign motorcyclists' behavior around tourist areas in Bali, which can significantly reduce the risk of accidents for foreigners. The results are that local law enforcement can act as a moderating effect of human factors on the behavior of foreign motorcyclists with a P-value of 0.008. Foreign motorcyclists' behavior in tourist areas is also directly affected by their behavior in their origin country, with a P-value of 0.035. But local law enforcement cannot act as a moderating effect of local road and traffic conditions on the behavior of foreign motorcyclists with a P-value of 0.441. The research concluded that foreign motorcyclists' behavior in Bali tourist areas is positively influenced by the local law enforcement by authorized officials. It shows that the more stringent enforcement of the law, the better the behavior of foreign motorcyclists. And better conduct of foreign motorcyclists can reduce the number of accidents involving foreigners in the tourist areas in Bali.

Predicting the likelihood of airspace user rerouting to mitigate air traffic flow management delay

At present, the most common air traffic flow management measure used by the European Network Manager to solve en-route demand and capacity balance issues is to impose air traffic flow management regulations in congested airspace, which delay flights on the ground to smooth demand. The delay imposed on a regulated flight, however, has a negative operational and economic impact on the corresponding airspace user. When the impact is severe, the airspace user may reroute the flight to tactically circumvent the regulated airspace, thereby avoiding the regulation and reducing (or even eliminating) the delay. This legitimate strategy is unquestionably effective in mitigating the delay and the associated cost, but it may also increases traffic demand uncertainty due to last-minute changes as well as the environmental impact due to sub-optimal trajectories. This paper presents a gradient-boosted decision trees model that, trained on historical data, could assist in predicting the likelihood of a regulated flight rerouting to mitigate air traffic flow management delay. Specific metrics for highly imbalanced binary classification problems reveal that, while not perfect, the model outperforms a rudimentary decision tree and a dummy classifier. Furthermore, Shapley values computed with the model uncover the most important triggers for tactical rerouting from a data-driven perspective, namely the current delay, the aircraft operator, the airspace sector where the most penalising regulation is applied and the remaining time until departure. This interpretable model could be used to assist flow managers in their decision-making, as well as to accurately mimic the behaviour of flight dispatchers when facing delays in simulators.

Causation analysis of crashes and near crashes using naturalistic driving data

Understanding crash causation to the extent needed for applying countermeasures has always been a focus as well as a difficulty in the field of traffic safety. Previous research has been limited by insufficient crash data and analysis methods more suitable to single crashes. The use of crashes and near crashes (CNCs) and naturalistic driving studies can help solve the data problem, and use of pre-crash scenarios can identify the high-prevalence causes across multiple crashes of a given scenario. This study therefore proposes a two-stage crash causation analysis method based on pre-crash scenarios and a crash causation derivation framework that systematically categorizes and analyzes contributing factors. From the Shanghai Naturalistic Driving Study (SH-NDS), 536 CNCs were extracted, and were grouped into 23 different pre-crash scenarios based on the National Highway Traffic Safety Administration (NHTSA) pre-crash scenario typology. In-depth investigations were conducted, and CNCs sharing the same scenario were analyzed using the proposed framework, which identifies causation patterns based on the interaction of the framework’s road user, vehicle, roadway infrastructure, and roadway environment subsystems. Through statistical analysis, the causation patterns and their contributing factors were compared for three common pre-crash scenarios of highest incidence: rear-end, lane change, and vehicle-pedalcyclist. Braking error in low-speed car following, following too closely, and non-driving-related distraction were important causes of rear-end scenarios. In lane change scenarios, the main causation patterns included illegal use of turn signals and dangerous lane changes as critical factors. Pedalcyclist scenarios were particularly impacted by visual obstructions, inadequate lanes for non-motorized vehicles, and pedalcyclists violating traffic regulations. Based on the identified causation patterns and their contributing factors, countermeasures for the three common scenarios are suggested, which provide support for safety improvement projects and the development of advanced driver assistance systems.

Analisa Tingkat Keselamatan Lalu Lintas pada Simpang Empat Puncak Jelutung dengan Metode Traffic Conflict Technique (TCT)

Accidents can occur due to several factor such as road, environmental and human factors. Jelutung peak red light intersection is a place that is prone to accidents due to conflicts between vehicles and other vehicles or between vehicles and pedestrians. The four-peak Jelutung intersection has a fairly large input and output capacity, and a fairly high density alternately in each lane during peak hours. This study aim to analyze traffic conflicts and examine the problems or damage that occurred at the intersection of Jl. Hayam Wuruk – Jl. D.I Panjaitan – Jl. Dr. Sumbiyono – Jl. Gajah Mada using the Traffict Conflict Technique (TCT) method which caused an accident. The method used in collecting data in this research is a field survey at 07:00-09:00 WIB. The result obtained are 8 types of conflicts that occur at the highest peak hour at 07:45-08:45 WIB, with the highest traffic violations occurring in type 7 conflict, namely with 87 cases of violations which are potential Serious Conflicts, in the shortest Time To Accident (TA) 0.18 seconds and the longest time is 0.53 seconds. Conflicts that occur are caused by vehicle factors, damaged road conditions, lack of complementary road facilities such as road marking and traffic signs, and lack of awareness of road users in obeying traffic regulations.

Comparison of various temporal air traffic flow management models in critical scenarios

Overloads (i.e., critical imbalances between traffic demand and capacity) are currently resolved in the European air transportation network by activating air traffic flow management regulations. Flights subject to regulations are delayed on the ground by the computer assisted slot allocation system, which uses a first-planned, first-served principle to allocate the delays. In the last decades, many researchers have proposed alternative models based on more or less complex optimisation techniques, which could effectively resolve overloads with less delay. Despite the fact that these models were very promising, changing the current operational system and procedures - which trust is supported by a successful working history dating back to 1995–may not be realistic in the short term. This paper examines the gradual transition from current air traffic flow management to a futuristic model in which flights are assigned delays with massive cherry-picking measures that minimise the total delay in the network, without necessarily adhering to the first-planned, first-served rule. A reference model with greedy regulations representative of current operations is compared to a model where the Network Manager optimises regulations using hyper-heuristics, a model based on massive cherry-picking measures, and hybrid models that consider regulations to resolve major overloads and cherry-picking measures only for residual overloads. These models are compared in critical scenarios with major capacity issues caused by adverse weather conditions. Results suggest that hybrid models could be a viable option for reducing delays with minor changes in the current air traffic flow management paradigm.

PERTIMBANGAN PUTUSAN PENGENAAN DENDA DALAM PELANGGARAN LALU LINTAS JALAN RAYA

Traffic violations on the highway by motorists lead to accidents. The majority of traffic violations are in the form of violations of traffic signs, such as prohibitions on stopping and parking in certain places, violating traffic lights such as breaking through red lights, and others. Inspections of motorized vehicles on the road by police officers or police operations are in fact law enforcement officers who provide more criminal sanctions in the form of fines than imprisonment (imprisonment) for motorists who violate traffic regulations. The research method used is a normative legal research method through a statute approach and a conceptual approach to the decision to impose fines in road traffic violations according to Law No. 22 of 2009 concerning Road Traffic and Transportation. In deciding the case of traffic violations, the Judge in considering his decision is faced with two choices to decide the case, namely whether to decide to impose a maximum imprisonment of 2 (two) months or decide to impose a fine. In practice, judges choose a second alternative decision, which is to impose fines on violators. The legal basis and considerations are Article 7 paragraph (2) of the Regulation of the Supreme Court (PERMA) Number 12 of 2016 concerning Procedures for the Settlement of Traffic Violation Cases.

Design, Development and Validation of an Intelligent Collision Risk Detection System to Improve Transportation Safety: The Case of the City of Popayán, Colombia

Several approaches from different perspectives have been used to solve problems with traffic accidents (TA), which mainly affect low- and middle-income countries. Conditions of certain cities, regarding road infrastructure, enforcement of traffic safety regulations, and motor vehicle numbers, influence the increase in TAs. Therefore, medium-sized cities in developing countries (context of interest), which commonly have worrying conditions, are a relevant scenario. One of the approaches to reduce TAs has been the use of data analysis through Machine Learning (ML); however, these techniques require a large amount of data, and medium-sized cities commonly do not have enough. Techniques such as Naturalistic Driving (ND) can be applied as a data collection method. This work proposes an intelligent collision risk detection system (ICDRS) using ND and ML to improve sustainability and safety of transportation in medium-sized cities. The ICRDS design considered the limitations of the context of interest and uses two data collection devices in the vehicle. The ICRDS validation included the design and execution of tests using ND. This validation identified if the collected data in a certain time interval contained high-risk collision events (sudden acceleration, sudden braking, aggressive left or right turn, aggressive left or right lane change). The system implementation results were satisfactory. The developed ML algorithm obtained an average value 0.98 in all the metrics. Two data sets of driving on routes were collected. In addition, the performed tests were able to identify city areas with high accident rates.

Sosialisasi Sadar Keselamatan Berlalu Lintas Pada Siswa SMA Negeri 8 Jakarta

Safety is one of the attributes of transportation in general and road transportation or traffic and road transportation in particular. Safety is something that is priceless, but few people are aware of maintaining their own safety. Road traffic safety is a condition where everyone avoids the risk of accidents during traffic caused by human, vehicles, roads and environment (RI Law No 2, 2009). Many high school students violate traffic rules and lack understanding of traffic norms. Such as breaking traffic lights or running lights, driving a motorbike/car without a driver’s license, pillion not using a helmet, not turning on the lights during the day, not using a seat belt while driving. Because the understanding of the traffic norms in high school students has a big impact, according to the conditions that are increasing day by day, for this reason we propose participation in the form community service program in the form safety road socialization to students in grade 11 and 12 at SMAN 8 Jakarta. The socialization was carried out by explaining the importance of understanding traffic norms and obeying traffic regulations. Through this community service program, it is hoped that it can arouse the awareness of the hearts of students to increasingly obey traffic rules and understand more about traffic norms.