How can you accurately measure vehicle occupancy?

The accuracy of manual count for occupancy is much higher nowaday with video recording, manual surveyor can easily playback and check if needed.

There are multiple methods to measure the vehicle occupancy. These methods involves, visual observations, sensors, head count through cards, video cameras etc. Each method have their own strength and weakness. Depending on the type of vehicle, e.g., motorcycle, car and bus the required method or tool may vary. In larger vehicles, during their movements, it is challenging to get accurate and precise counts.

several methods, such as visual observation, manual counting or technological solutions. each method has its own strengths and weakness. The choice of method depends on factors such as accuracy requirements, cost, and ease of implementation

When conducting a manual count an engaged observer is key. It’s much easier on a bus or light rail as opposed to a train with 2000+ customers.

Pour une optimisation des résultats sur le taux d'occupation, je pense qu'une combinaison de méthodes, donc à une approche hybride( manuels et à l'aide de capteurs automatiques).

It is very difficult to count the full number of occupants in a moving vehicle reliably, let alone trying to use technology to achieve this. Why? Although it is now achievable to use video with AI to verify front seat occupants, it is much harder to see into the rear of vehicles. Cars with second or third rows of seats, crew cabs in vans and pickups, mini-buses and RV's all pose an issue of obscuration to see into these areas reliably for a variety of reasons, including tall front seats, headrests and dark windows etc. But if you are just interested in the front row, you can not only count them, but also automatically detect a range of other parameters, including seatbelt and handheld device use.

In my opinion, as always technology can help researchers in this area. By using sensors which count the entered person or take a photo and then count the number of entered persons.

Les capteurs automatique peuvent être utiles dans le cas ou le rayon est bien défini, tout en calculant un périmètre sur un ensemble fermé

Automatic sensors will be cheap. In order to negate the drawbacks, automatic sensors with strong police monitoring should do the trick. Strong police monitoring should be enforced when the new sensors are installed and then random checks should be performed on and off to catch the law breakers

Why not use some automatic sensors that scan car license plate? Nowadays, each country has public APIs that provide you all informations about a specific license plate. And when traffic is too big, it is possible to use cameras with a high resolutions like speed cameras to recognise traffic.

There are two approaches for vehicle occupancy, static and dynamic. The static one is when you measure the vehicle occupancy for a predetermined number of sample of each vehicle passing through the observed roadside. The dynamic approach is by counting the remaining number of passenger inside the vehicle. Generally for passenger car/motorcycle/truck, we use static an dynamic approaches as well. However, for public transport survey, the dynamic approach is more accurate rather than static. Both data will be powerful to validate the model.

Origin-destination surveys and various models are valuable for comprehending traffic flow. However, current constraints, such as limited survey time and frequent traffic blocks, pose challenges. Nevertheless, it remains a reliable method still employed in transportation design.

Likewise, those surveys must be done during specific periods that are representative of a normal day. It is usually necessary to carry out these surveys over several days, for one day in the end.

Cette méthode est déjà employée par certains systèmes de technologies embarquées comme Google apps Le fait de demander aux utilisateurs de signaler leur utilisation revient à leurs demander de se signaler = attention aux risques et dérives

Surveys are great for collecting traveler behavior information but in my experience, vehicle occupancy is a byproduct. Travel behavior is a complicated topic important for understanding regional differences and developing strategies for programs and infrastructure projects that can help reach defined goals. When it comes to vehicle occupancy, surveys are better for helping to understand the projects and programs that will help increase occupancy, not measure it in the first place. Models are only as good as the data that goes into them so I would be cautious of trying to use models to understand actual occupancy.

Combining hybrid methods may offer the most accurate results. Employing a combination of manual counting and automatic sensors for vehicle counting can yield valuable survey outcomes, contingent on the circumstances and results.

In an ideal world, a hybrid approach would absolutely be the best way to measure occupancy. Data could be collected with automated sensors and verified with manual counts. A traveler behavior survey could be used to better understand what is affecting occupancy and develop the assumptions, variables and sensitivities that go into the model. Then the model could be used (with some level of confidence) to test the long-term effectiveness of various program and infrastructure scenarios at changing vehicle occupancy.

In my experience a hybrid approach works very well not only to calibrate but also, on the manual side, to gain additional information such as ticket type and origin destination if the passengers. This information helps to calibrate a demand model beyond occupancy but also origin destination giving a complete picture.

Hybrid approaches would be best to increase accuracy, as we can evaluate the difference between the sensors based vehicle counting and manual data counting which have different levels of accuracy depending on circumstances and locations

La logística híbrida, por ejemplo, adopta sistemas de distribución de múltiples canales para llegar a uno o más clientes. Consiste en una alianza entre dos compañías con el objetivo de conseguir una logística dinámica, solidaria, sin rupturas y con la misma filosofía, incluyendo los colaboradores y sistemas tecnológicos. De esta forma, se comparten los recursos físicos de ambas partes, para poder ofrecer una mejor calidad en los servicios y llegar a un mayor número de personas

Vehicle occupancy measurement is crucial for several reasons. It aids in understanding the utilization of our transportation system. By knowing how many people are in a vehicle, we can assess the efficiency of our roads and highways. It helps in planning and managing traffic. High vehicle occupancy indicates carpooling, which reduces the number of vehicles on the road, leading to less traffic congestion. Also, it's beneficial for environmental reasons. Higher vehicle occupancy means fewer cars on the road, leading to lower emissions per person.

measuring auto occupancy is also employed to allow cars with more than one passenger to circulate in dedicated lanes. These lanes are referred to as 'carpooling lanes

Mesurer l'occupation des véhicules revient et/ou va aider à évaluer l'efficacité des systèmes de transport dans les relais, pont, et les routes principale et secondaire

Mesurer l occupation des véhicules est déjà en soi une orientation vers le moins de véhicules, si cela peut être une orientation écologique nécessaire pour une grande cité, elle est moins significative pour le milieu rurale ou le besoin de se déplacer est très différent entre les résidents. Une société n est pas unique , les besoins de chacun sont différents et le droit d'être libre à se déplacer doit être pris en considération et faire l objet de pédagogie réelle.

La medición de ocupación de los vehículos favorece a los siguientes factores; Control de la vida útil del vehículo, seguridad en los recursos, minimización de costos y contribuye a la maximización de la calidad y el servicio prestado.

Each city has its own parameters and its own planning of transport modes. In this sense, reading the results of a vehicle count must be critical. The actions taken based on this counting must be related to the city's objectives. Abu Dhabi, for example, is a city that to a certain extent has planned for the use and encouragement of individual and private transportation. However, when we look at the case of Paris, with a city hall that creates 30km/h speed limit zones and reduces parking spaces, we have a case of prioritizing public spaces for collective use. In these two cases, the vehicle count reading will have different interpretations, which shows how the context in which the city is inserted is essential in this process.

Vehicle occupancy can be accurately measured using methods such as: 1. **Visual Inspection:** Direct observation to count occupants, but this may not be practical for large-scale or continuous monitoring. 2. **Manual Surveys:** Surveys conducted by personnel to record the number of occupants, but this can be time-consuming and costly. 3. **Automated Passenger Counting Systems:** Install sensors like infrared or video cameras that can automatically count occupants as they enter or exit the vehicle. 4. **Weight Sensors:** 5. **Smart Ticketing Systems:** Choose a method based on the context and resources available, considering factors like accuracy, cost, and practicality.

Understanding vehicle occupancy is valuable in assessing demand trends, yet it provides a limited perspective on actual demand. It typically focuses on specific modes like headcounts on buses or cars between designated points, disregarding unfulfilled travel plans and other modes. Consequently, it falls short in presenting a comprehensive overview. Incorporating external data sources like mobile networks is pivotal for a more accurate understanding of genuine demand patterns. These additional datasets offer a broader scope, capturing latent demand and diverse travel modes that traditional occupancy metrics might overlook.

There easiest way to measure vehicle occupancy is using simple math. You add the number of seats plus standing capabilities within the vehicle and divide by the number of occupants/passengers on board. The key here is having real-time data which constantly and accurately measures boardings and alightings through APC's located at each door.

Due to the cost and political sensitivities surrounding automated sensor systems, I don't think we will see widespread systems any time soon. As such, vehicle occupancy data will still be collected manually. As a young planner, I used to go on traffic and occupancy counts. I don't remember it as a pleasant experience, especially when I had to do it by myself. I remember being in the shoulder of a busy freeway connector and almost getting hit by a speeding car. It was scary. For those developing count programs, keep the safety of your team paramount.