Autonomous vehicles are currently developed, and are expected to be introduced gradually. Society needs a basis for decisions regarding market interventions. This study identifies, quantifies and values the benefits and costs of autonomous trucks and cars considering generalized costs, external effects and social marginal cost pricing to consumers with Swedish data. The results show that the greatest benefits are saved driver costs for trucks and decreased travel time costs for car drivers. In the example calculations, capital costs may increase by 22 percent for cars and 36 percent for trucks for benefits to exceed costs in 2025. Subsidies are not needed since the producers and consumers get the major benefits and pay the costs.
The vehicle industry is developing new technologies for trucks and cars to be autonomous, also referred to as automated or self-driving vehicles that are expected to be introduced gradually and gain market shares. When commercial success is up to the manufacturers, the benefits and costs to society as a whole are crucial not only for the technology’s success but also for the implementation of the right policies and public investments. Questions include whether policies should be proactive, promote development with rapid adjustment of regulations, and give subsidies if the technology has net benefits to society, or whether institutions should evolve gradually in response to innovation within the industry. We study the relative importance of the different identified effects when autonomous vehicles (AVs) are introduced, in particular the dominance of saved driver costs for both trucks and cars. The applied methodology is common for evaluating infrastructure investments; in this study it is applied to the introduction of a new technology for transportation. We use today’s knowledge to quantify the magnitude of benefits and costs related to AVs.
The purpose of the study is to estimate the relative importance of identified effects of autonomous trucks and cars, the distribution of effects, and whether benefits are greater than costs, by using theory, previous studies and the unit values for transportation costs applied in Sweden. In an example calculation, some studied alternatives based on Swedish statistics and forecasts are compared with a reference scenario. A number of assumptions about effects are altered in a sensitivity analysis to find out which effects are crucial.
The real effects of creating or using resources, excluding any redistribution effects, based on changes in generalized cost are presented. We consider whether social marginal cost pricing to consumers prevails on the markets concerned, both to estimate all effects accurately and to be able to analyse how the effects for society as a whole and the effects for producers and consumers on the transport markets are interrelated. Based on the latter, it is possible to discuss the policy implications of the result. To our knowledge, no such holistic approach has been applied to quantify the benefits and costs of both freight and passenger transportation on the road. Few studies appear to have aimed to quantify and value the effects on society as a whole including the saved resources for driving cars and trucks.
SAE International [
We construct a reference alternative where all vehicles develop to level 2, manually driven vehicles (MDV), and compare this to studied alternatives where AVs with full automation are introduced. Level 3 is assumed transitory, since several car producers, as Ford and Volvo, are avoiding this level, because they consider it difficult for the driver to keep track of traffic and, if necessary, take over from automated driving (Wired [
In this study, welfare theory is used to analyse all relevant effects to society. We are identifying, quantifying and valuing effects of autonomous trucks and cars. The aim is to determine the relative importance of identified benefits and costs, who receives them, and whether benefits are greater than costs. We use the method cost-benefit analysis (CBA), with the limitation that some effects are difficult to quantify and value. The results from a CBA can be used as a basis for decisions whether the public sector should consider producing on, financing or regulating the market.
The generalized cost (GC) of transportation, used as a key concept in transport economics, is a central term for the identification, quantification and valuation of effects for autonomous trucks and cars. Generalized cost refers to all monetary and non-monetary costs for the transport service user. The benefits of AVs consist of lower generalized costs for the vehicle kilometres (vkm) driven by autonomous trucks and cars instead of MDVs, and of more transportation. Some of the latter will be newly generated, and some will be transferred from other modes of transport. The extent of the effects depends on elasticities. We will use the term social generalized cost (SGC) for generalized cost when all external effects are internalised in the price to the consumer.
The benefits of the change in social generalized cost for trips transferred from MDVs on the road to AVs is calculated as
B e n e f i t = Q 1 ( S G C 0 − S G C 1 ) (1)
If social marginal cost pricing prevails, i.e. all used resources are considered when deciding to drive another vkm; new vehicle kilometres give a net social benefit to society, as the additional value is higher than the cost. In reality, however, such optimal pricing may not be the case. If the studied (primary) market for driving with trucks and cars or interrelated (secondary) markets do not have social marginal cost pricing and the consumers do not accurately consider all benefits and costs to society of the new vehicle kilometres, adjustment posts need to be added (Boardman et al. [
The net benefits of the change in generalized cost for new vkm on the road is calculated as
N e t b e n e f i t = 0.5 ( Q 2 − Q 1 ) ( S G C 0 − S G C 1 ) (2)
How much traffic is shifted from MDVs to AVs depends on the relative magnitude of the decrease in SGC, the cost of buying a new vehicle, the depreciation rate of the existing fleet, technological and legal restraints and preferences. The rule of half is applied, which is to assume linear demand curves.
If social marginal cost pricing does not apply in all the relevant transport markets, this must be taken into account as added adjustment posts. In order to determine whether such adjustment posts needs to be added in conjunction with new vehicle kilometres by an AV when generalized cost decreases, it must be determined whether or not the consumers of vehicle kilometres by truck and car, as well as freight and passenger transportation by alternative modes of transport, consider the social marginal cost. The social marginal cost may differ from the private marginal cost if infrastructure usage or other external effects are not correctly internalized in the price.
For passenger traffic by private car, the producer and the consumer of the vehicle kilometres is the same. It is then sufficient to study whether negative and positive external effects are internalized by Pigouvian taxes and subsidies (Pigou [
A d d e d p o s t c a r = ( G C 1 − M C s o c i a l 1 ) ∗ ( Q 2 − Q 1 ) (3)
For freight transport by truck, producers and consumers may be different actors. Therefore, the competitive condition and pricing strategies must also be studied. On the one hand, it may be that freight service providers pay a price lower than the social marginal cost of using infrastructure if negative external effects are not internalized by Pigouvian taxes. On the other hand, limited competition, or a cost structure of decreasing average costs, may lead to consumers still paying a price that is higher than the social marginal cost. Thus for trucks, if needed an adjustment post is added as
A d d e d p o s t t r u c k = ( P c o n s u m e r − M C s o c i a l 1 ) ∗ ( Q 2 − Q 1 ) (4)
Some of the new vehicle kilometres by truck or car will be transferred from substitute markets such as transport by train. If social marginal cost pricing to the consumer does not prevail in these markets, adjustments must be made in the calculation.
A post is added as
A d d e d p o s t s u b s t i t u t e = ( M C s o c i a l − P c o n s u m e r ) ∗ ( Q 0 − Q 1 ) (5)
If the price of the mode of transport is lower or higher than the social marginal cost, a benefit of for example saved negative external effects or lost positive external effects must be added. Only if full competition prevails, public sector regulation with Pigouvian taxes or subsidies is enough to achieve social marginal cost pricing for consumers. If the market is a private monopoly or an oligopoly, or a public company with economies of scale and full cost pricing, or private profit maximization, the price to the consumers may be higher than the social marginal cost.
Capital costs vary depending on both time and mileage. Part of the change in capital costs with AVs compared to MDVs varies with vehicle kilometres and changes generalized cost. Maintenance costs per vehicle kilometre might also be different. However, studies have shown that travellers take little account of marginal capital and maintenance costs when deciding how many vehicle kilometres to drive with their car (Hang et al. [
A number of studies have taken a comprehensive approach towards identifying all effects of AVs (Anderson et al. [
Anderson et al. [
Milakis et al. [
Other studies focus on a certain aspect of AVs, such as fuel consumption and market shares (Brown et al. [
Bansal and Kockelman [
For freight transport by truck we use three vehicle types: one for long-distance transportation with 6 - 7 axles and a capacity of 40 tonnes (HGV40), one for distribution with two axles and carrying up to 16 tonnes (MGV16), and one for transportation of bulk materials like stone, sand, etc. for construction purposes with three axles and carrying 16 - 24 tonnes (MGV24). Based on Transport Analysis [
For passenger traffic by road, we use one type of car, where fuel consumption is a weighted average of petrol (70 percent) and diesel (30 percent) according to Transport Analysis [
Effect | Freight | Passenger |
---|---|---|
Quantified and valued effects | ||
Saved driver costs for freight transported by truck | Benefit | |
Saved time-value if the driver in the vehicle can do other things | Benefit | |
Saved fuel due to convoy driving (platooning) | Benefit | |
Saved fuel due to smoother driving | Benefit | Benefit |
Reduced environmental emissions due to less fuel consumption | Benefit | Benefit |
Increased traffic safety | Benefit | Benefit |
Increased transportation due to lower generalized costs | Benefit | Benefit |
Added adjustment posts due to transport markets not applying social marginal cost pricing to consumers | Benefit/cost | Benefit/cost |
Effects that are calculated in terms of how high they can be for ∑B > ∑C | ||
Technology development for vehicles | Cost | Cost |
Higher capital costs | Cost | Cost |
Changed maintenance cost for AVs | Benefit/cost | Benefit/cost |
Effects that are not quantified or valued | ||
Elderly people, disabled people and those without driving licenses can travel by car | Benefit | |
Perceived change in safety and privacy with AVs | Benefit/cost | Benefit/cost |
Changed cost of infrastructure investments | Benefit/cost | Benefit/cost |
Changed land use | Benefit/cost | Benefit/cost |
Changed congestion | Benefit/cost | Benefit/cost |
The Swedish Transport Administration [
Concerning passenger transportation, the Swedish Transport Administration [
To calculate how the social generalized cost changes with autonomous trucks and cars, we must make some assumptions about how factors change, based on previous research presented in Section 2.
1We use the recommended enumeration factors 1.1605 from 2014 to 2025 and 1.4509 from 2014 to 2040 for travel time and environmental impacts, and 1.0722 and 1.1905 for petrol and 1.0829 and 1.2204 for diesel for the years 2025 and 2040.
For long-distance trucks, autonomous driving will reduce fuel consumption because platooning can be established on the road, leading to less wind resistance for the vehicles inside the platoon. In addition, fuel can be saved by smoother driving in general. We estimate that fuel consumption can be reduced by 10 percent for long-distance truck, but not for the other types of trucks, as they typically cannot form platoons. Moreover, we conclude that AVs will not be introduced until they are at least as safe as MDVs, and we make a modest assumption that accidents will be reduced by 10% in the example calculation. With AVs, the entire driver cost will be saved, as there is no need for a driver to be on board, or if the driver is on board, the person can perform other tasks, thus freeing someone else.
Long-distance (HGV 40) | Distribution (MGV 16) | Construction (MGV 24) | ||||
---|---|---|---|---|---|---|
2025 | 2040 | 2025 | 2040 | 2025 | 2040 | |
Fuel (product price incl. VAT) | 2.71 | 3.06 | 1.71 | 1.92 | 2.09 | 2.36 |
Noise | 0.46 | 0.58 | 1.49 | 1.86 | 1.02 | 1.28 |
Carbon dioxide | 1.15 | 1.44 | 0.84 | 1.04 | 1.15 | 1.44 |
Other emissions | 0.63 | 0.78 | 1.10 | 1.38 | 0.41 | 0.51 |
Accidents | 0.38 | 0.48 | 0.67 | 0.84 | 0.38 | 0.48 |
Marginal capital and maintenance cost | 3.75 | 3.75 | 2.95 | 2.95 | 3.50 | 3.50 |
Driver costs | 6.18 | 6.18 | 10.84 | 10.84 | 9.40 | 9.40 |
Time value of transported goods | 0.74 | 0.74 | 1.24 | 1.24 | 0.24 | 0.24 |
SGC | 16.00 | 17.01 | 20.84 | 22.07 | 18.19 | 19.21 |
Total capital cost (depreciation and interest) | 2.83 | 2.83 | 3.28 | 3.28 | 5.22 | 5.22 |
Source: Own calculations based on the Swedish Transport Administration [
2025 | 2040 | |
---|---|---|
Fuel (product price incl. VAT) | 0.58 | 0.65 |
Noise | 0.21 | 0.26 |
Carbon dioxide | 0.19 | 0.19 |
Other emissions | 0.04 | 0.03 |
Accidents | 0.19 | 0.23 |
Marginal capital and maintenance costs | 0.95 | 0.95 |
Travel time by car, work travel | 4.64 | 5.81 |
Travel time by car, private travel | 1.40 | 1.74 |
SGC private travel | 3.56 | 4.05 |
SGC work travel | 6.80 | 8.12 |
Total capital cost (depreciation and interest) | 2.42 | 2.42 |
Source: Own calculations based on the Swedish Transport Administration [
Transport Analysis [
The average gain when the driver is freed from driving the car is thus estimated at 24 SEK per hour for 2025 and 30 SEK for 2040. For work travel, the gain is estimated at 109 SEK per hour in 2025 and 136 SEK per hour in 2040, with the assumption that 30 percent of travel time is devoted to work in an AV. Smoother driving with an AV than with a MDV is assumed to result in 10 percent less fuel and emissions. With an AV we assume 10 percent fewer accidents in 2025 and 30 percent in 2040 than today. The most important effect for autonomous cars is the decreased travel time cost. It counts for approximately three fourths of the change in SGC for private travel and more than nine tenths of the change in SGC for work travel by car. The consumer will get this benefit. The same goes for the next highest benefit of decreased fuel consumption. To
2025 | 2040 | |||
---|---|---|---|---|
ΔSGC in SEK | Percent of total ΔSGC | ΔSGC in SEK | Percent of total ΔSGC | |
Fuel (product price incl. VAT) | −0.27 | 4.0 | −0.31 | 4.3 |
Noise | 0 | 0 | 0 | 0 |
Carbon dioxide | −0.11 | 1.7 | −0.14 | 2.0 |
Other emissions | −0.06 | 0.9 | −0.08 | 1.1 |
Accidents | −0.04 | 0.6 | −0.33 | 4.8 |
Marginal capital and maintenance costs | 0 | 0 | 0 | 0 |
Driver costs | −6.18 | 92.7 | −6.18 | 87.8 |
Time value of transported goods | 0 | 0 | 0 | 0 |
ΔSGC | −6.67 | 100 | −7.04 | 100 |
2025 | 2040 | |||||
---|---|---|---|---|---|---|
ΔSGC in SEK | Percent of total ΔSGC private | Percent of total ΔSGC work | ΔSGC in SEK | Percent of total ΔSGC private | Percent of total ΔSGC work | |
Fuel (product price incl. VAT) | −0.06 | 14.1 | 3.9 | −0.06 | 11.4 | 3.4 |
Noise | 0 | −0.03 | 4.5 | 1.4 | ||
Carbon dioxide | −0.02 | 4.6 | 1.3 | −0.02 | 3.3 | 0.9 |
Other emissions | −0.004 | 0.9 | 0.2 | −0.003 | 0.5 | 0.2 |
Accidents | −0.02 | 4.6 | 1.3 | −0.07 | 12.1 | 3.6 |
Marginal capital and maintenance costs | 0 | 0 | ||||
Travel time by car, private travel | −0.31 | 75.6 | −0.39 | 68.2 | ||
Travel time by car, work travel | −1.40 | 93.3 | −1,74 | 90.5 | ||
ΔSGC private travel | −0,41 | −0.57 | ||||
ΔSGC work travel | −1.5 | −1.92 | ||||
100 | 100 | 100 | 100 |
what extent reduced emissions will benefit the consumer depends on the internalization of the external effects in the fuel taxes. The only effect that will be external is most of the change in accidents in 2040 because it changes more than fuel consumption. If accidents would change to zero with AVs the effects not internalized would still only account for less than one third of the effects for private travel and one tenths for work travel.
It is difficult to predict how much different capital costs will be for AVs compared to MDVs in 2025 and 2040. Fagnant and Kockelman [
This section will discuss effects of autonomous vehicles that are not quantified or valued in this study. These effects may add to both benefits and costs, and reliable information about their future impact is still lacking.
When autonomous vehicles begin to operate in regular traffic, additional costs may arise, related to the trucks and cars. Some may be of transitional character, such as development costs for the new technology, whereas others may be more persistent, such as higher production costs for more advanced vehicles and maintenance. In the longer term, however, production of vehicles may become less expensive, because they can be designed without any devices for driving, and become more productive when the space for the driver of trucks is transferred into more room for cargo. Capital costs for the vehicles may eventually decrease because of learning by doing and economies of scale in the manufacturing industry. The costs of developing the necessary technology for the vehicles and any higher production costs for the vehicles will be included in the price the consumer pays for the autonomous vehicles. As mentioned earlier, we study how much capital costs can increase in order not to completely counteract the quantified and valued net benefits.
In the short term, the digital infrastructure can require more investment, and, as long as the traffic is mixed between AVs and MDVs, special lanes may be needed. Development costs for the new technologies may also be significant. In the longer term, on the other hand, investments in infrastructure may decrease. Private cars can use road and parking capacity more efficiently, requiring less space. Fewer or narrower streets and lanes may come as a result, as well as reduced demand for parking spaces in areas with high land value. However, vehicles parking in other areas could induce more traffic. Zakharenko [
Older people, people with disabilities and those without driving licenses can benefit from being able to ride in an autonomous car. Their improved potential mobility is discussed by Harper et al. [
The effects on people’s perceived safety and concerns for privacy when large amounts of data need to be processed for the required communication are not quantified and valued in this study. People may presume higher risks related to vehicles without a driver and to reduced privacy, at least during an early stage. On the other hand, driver-related mistakes are eliminated. Bansal and Kockelman [
Problems with congestion can be both enhanced and mitigated. This is determined by how the quantity of travelling, the traffic flow and the number of vehicles change with AVs. Improved mobility may stimulate more traffic, as well as empty vehicles driving to their parking spaces or picking up people sharing cars, which may counteract the positive effects. Transport Analysis [
In this section, values for SGC presented in Section 4 are used to make an example calculation of the magnitude of the effects of automated vehicles in 2025 and 2040. An initial example calculation of benefits and costs of self-driving vehicles on the road was made by the authors for a Swedish Government Inquiry [
In the example calculations, traffic volumes are based on official Swedish statistics and forecasts. In 2015, traffic by Swedish registered trucks totalled 3043 million vehicle kilometres on domestic roads. Traffic by foreign vehicles is not registered, but was estimated at 625 million vehicle kilometres in 2010, and rising (Transport Analysis [
Transport Analysis [
Year | Vehicle type | Total increase | Million vkm (incl. foreign) | Assumed share of AVs | |
---|---|---|---|---|---|
Reference alt. | Studied alt. | ||||
22,025 | long-distance | 22% | 3160 | 0% | 10% |
distribution | 16% | 418 | 0% | 5% | |
construction | 16% | 547 | 10% | 20% | |
22,040 | long-distance | 65% | 4280 | 0% | 50% |
distribution | 44% | 520 | 0% | 50% | |
construction | 44% | 681 | 10% | 50% |
Source: The Swedish Transport Administration [
Year | Total increase | Million vkm | Assumed share of AVs | |
---|---|---|---|---|
Reference alt. | Studied alt. | |||
2025 | 12% | 73.76 | 0 | 10% |
2040 | 26% | 82.98 | 0 | 50% |
Source: Annual increases: The Swedish Transport Administration [
Litman [
Price elasticities of demand for transportation by car are based on an analysis of the effects of introducing congestion fees in Stockholm and Gothenburg (Börjesson and Kristoffersson [
A Swedish project called Samkost 2 has estimated how well external effects are priced to the producers of transportation in Sweden (The Swedish National Road and Transport Research Institute [
Based on the unit costs for freight trains (The Swedish Transport Administration [
Based on the annual report from the main state-owned company for passenger traffic, SJ [
In this section, example calculations of the net benefits of AVs are carried out and considered in relation to how much the capital costs (defined earlier) can increase without making AVs unprofitable for society. The analysis includes freight transport by truck and passenger transport by car, and considers effects on the substitute markets passenger transport and freight by train. Transportation in the substitute markets air and sea is not considered. They account for 2.8 and 0.6 percent of passenger kilometres respectively in Sweden (Transport Analysis [
When calculating new traffic for passenger transport by car it is, as mentioned, assumed that all external effects are internalized to the GC for the consumer. This means that the savings in GC that the traveller in an AV will perceive are somewhat higher than the savings for society in 2025 but somewhat lower in 2040. The savings from reduced fuel when the price includes all external effects will include noise that will remain unchanged, but the savings in traffic safety in 2040 will be greater than the part included in the fuel price (saved fuel is 10% while increased traffic safety is 30%). The difference is less than five percent. The relative change in GC combined with the applied price elasticity of demand results in increases of 7.2 percent in 2025 and 7.7 percent in 2040 for private travelling by car, and 13.4 percent in 2025 and 13.9 percent in 2040 for work travelling by car. The corresponding increase in vehicle kilometres for trucks in long-distance traffic is 7.0 percent in 2025 and 15.5 percent in 2040.
Effect | Quantities and values |
---|---|
Saved driver costs for long-distance | 15% of long-distance transport by AV in 2025 is driver-free, 50% in 2050 |
Saved driver costs for other transport by truck | 10% of distribution and 20% of construction vehicles that are AVs are driver-free in 2025, 50% in 2040. |
Saved fuel and environmental costs due to convoy driving | convoy = 10% of long-distance in 2025, 50% in 2040; 10% saved fuel |
Increased traffic safety | 10% fewer accidents in 2025 and 30% in 2040 compared with today |
Net benefit new traffic and added post for difference between price and MC | Price elasticity of demand for long-distance is −0.8, other transport −0.5; price 20% over marginal cost |
Adjustment post: transferred traffic from train | 5% of new long-distance transport transferred from train |
Effect | Quantities and values |
---|---|
Decreased travel time cost, private travelling | The difference between travel value in car and train |
Decreased travel time cost, work travelling | 30% of the travel time in a car is used to work in an AV |
Saved fuel and reduced emissions | Smoother driving means 10% less fuel and emissions |
Increased traffic safety | 10% fewer accidents in 2025 and 30% in 2040 than today |
Net benefit of new traffic | The price elasticity of demand for cars is −0.6 |
Adjustment post: transferred traffic from train | 5% of new passenger transport transferred from train |
2The average exchange rate 9.3562 SEK/euro for 2014 (the Riksbank [
2025 | 2040 | |
---|---|---|
Saved driver costs for long-distance transport | 31.4 | 706.8 |
Saved driver costs for other transport by truck | 13.4 | 287.6 |
Saved fuel due to convoy driving | 0.9 | 34.9 |
Saved environmental costs due to convoy driving | 0.6 | 25.3 |
Increased traffic safety | 1.7 | 44.0 |
New traffic | 1.2 | 30.6 |
Adjustment post: difference between consumer price and MC | 0.5 | 12.2 |
Added post: Transferred traffic from train | − 0.5 | − 2.6 |
Effect | 2025 | 2040 |
---|---|---|
Decreased travel time cost, private travelling | 218.3 | 1534.9 |
Decreased travel time cost, work travelling | 110.2 | 773.2 |
Saved fuel | 45.7 | 288.2 |
Saved environmental effects | 18.1 | 97.6 |
Increased traffic safety | 15.0 | 306.0 |
New traffic | 19.0 | 137.8 |
Adjustment post: Transferred traffic from train | −1.6 | −9.4 |
The net benefits of the quantified and valued effects of self-driving trucks are 49.2 million euro in 2025. Saved driver costs are the largest benefit. For total net benefits to exceed costs in 2025, capital costs cannot rise by more than 36.8 percent. The most important factor for the size of net benefits for AVs is that a sufficient proportion of travelling is actually carried out without drivers on board or that the driver performs other duties that can free up other employees. As truck drivers currently carry out other tasks than only driving the vehicle, we do not estimate that more than 50 percent of the drivers’ time can be freed up by 2040. By 2040, the effects are greater than 2025, because higher shares of traffic consist of AVs, the total traffic has grown and larger shares of traffic by AV are assumed to exist without any driver on board. The net benefit of the quantified and valued effects becomes 1138.9 million euro and capital costs can increase by 127.9 percent before AVs become unprofitable to society in the example calculations.
For passenger transport, the net benefit of the quantified and valued effects is 424.7 million euro in 2025. The biggest calculated effect is the decreased travel time costs with AVs. Although work travelling only accounts for a tenth of transport, it accounts for one third of the benefits of reduced travel costs. This is because the travel time cost is higher per hour for work travelling than for private travelling. For the year 2040, the net benefit is 3128.3 million euro. For the benefits and costs in the example calculation to be equal, with all other quantities and values equal, the capital cost for AVs may be no more than 22.3 percent higher than for MDVs in 2025 and 29.2 percent higher in 2040.
If all external effects are internalized in GC for the consumer, the effects of decreased GC that the traveller in an AV will experience are somewhat larger than the savings for society in 2025 but somewhat lower in 2040. The difference is less than five percent between what the consumers perceive and the total effects for society. For trucks, the difference is less than three percent.
A sensitivity analysis means that quantities and values are varied to see the effect on the overall result. One factor at a time is varied in the example calculation for AVs.
It can be noted that transport volume and the share of AVs have no impact on whether benefits exceed costs of AVs in the example calculations, since benefits and costs will increase by the same proportion because all effects in the example calculations are per vehicle kilometre. Thus, forecasts of growth in traffic or shares of AVs will not determine whether AVs’ benefits exceed costs to society, only how big the gain (or loss) is. For this to alter, one benefit or cost must change more than the others do. As the sensitivity analysis shows, altering the quantities or values related to saving driver costs has the biggest impact on the results.
The most important factor for benefits to exceed costs for AVs for freight transport by truck is the share of the number of vehicle kilometres by AVs driven without a driver. The sensitivity analysis underlines that only a minor variation is crucial for the result for autonomous trucks. For autonomous cars, the most decisive effect is the extent to which the drivers’ value of travel time changes.
Maximum increase in capital cost for AVs for benefits to exceed costs | ||
---|---|---|
Truck | Car | |
Main example calculation | 36.8% | 22.3% |
Halved increase in transport volume | 36.8% | 22.3% |
Share of AVs is twice as large | 36.8% | 22.3% |
Share of AVs is half as large | 36.8% | 22.3% |
Driver-free 7.5% of AVs in long-distance transport | 24.5% | |
Driver-free 30% of AVs in long-distance transport | 61.3% | |
The change in travel time value is twice as large | 39.5% | |
The change in travel time value is half as large | 13.7% | |
Twice as large saving in fuel | 38.0% | 25.6% |
Twice as large decrease in accidents | 38.1% | 23.0% |
The decrease in emissions is half as large from a given reduction in fuel consumption | 36.6% | 21.8% |
25% higher average speed | 32.8% | 19.6% |
25% lower average speed | 42.2% | 28.8% |
Platooning 20% instead of 10% of long-distance transport | 38.0% |
Maximum increase in capital cost for AVs for benefits to exceed costs | ||
---|---|---|
Truck | Car | |
Main example calculation | 127.9% | 29.1% |
Halved increase in transport volume | 127.9% | 29.1% |
Share of AVs is twice as large | 127.9% | 29.1% |
Share of AVs is half as large | 127.9% | 29.1% |
Driver-free 25% instead of 50% of AVs in long-distance transport | 86.7% | 29.1% |
The change in travel time value is twice as large | 50.6% | |
The change in travel time value is half as large | 18.4% | |
Twice as large saving in fuel | 135.0% | 32.7% |
Twice as large decrease in accidents (60% instead of 30%) | 132.8% | 32.0% |
The decrease in emissions is half as large from a given decrease in fuel consumption | 126.4% | 28.7% |
25% higher average speed | 114.4% | 24.8% |
25% lower average speed | 145.7% | 36.3% |
2025 | 2040 | |||
---|---|---|---|---|
Freight | Passenger | Freight | Passenger | |
Driver costs | 91.1% | 77.3% | 87.3% | 73.8% |
Fuel | 1.8% | 10.8% | 3.1% | 9.2% |
Emissions | 1.2% | 4.3% | 2.2% | 3.1% |
Safety | 3.5% | 3.5% | 3.9% | 9.8% |
Net new traffic | 2.4% | 4.1% | 3.5% | 4.1% |
Reduction in fuel consumption because of convoys and smoother driving and the resulting decrease in emissions on the roads are benefits. However, a shift to fossil-free fuels in the future may reduce these benefits. In the example, emission reductions represent 25 - 28 percent of the benefit of reduced fuel consumption for cars and 40 - 42 percent for trucks. As is demonstrated by the example calculations, these factors contribute to a relatively small share of the total benefits. Better safety is another effect. As the effect of freeing drivers from their duties is so dominant, alternative scenarios about fuel consumption or safety have small effects on the result. The acceptance level for autonomous vehicles is another crucial factor. We have used a modest decrease in accidents by 10 percent for 2025, but it is possible that the autonomous vehicles must be a lot safer than MDVs before they will be accepted on the roads.
As autonomous vehicles have a lower generalized cost, the total traffic will increase. More traffic is a net benefit, as long as the price to the consumer is equal to the social marginal cost. This contributes 2.4 - 4.1 percent of the total benefits, including the lost value of rail traffic.
The real gain is achieved if trucks and cars can indeed be driver-free and resources saved for other uses. For drivers of cars, this shift is unproblematic. For trucks, it means a period of structural change in the labour market. As autonomous trucks will be replacing manually driven trucks during a period that will probably last for several decades, the labour market will have time to adjust and no permanent unemployment can be expected.
No assumptions are made about how much an AV will cost. The example calculations show how much higher capital costs (including technology development for vehicles, higher capital costs due to more expensive production costs and changed maintenance costs) for AVs can be compared to MDVs without costs being larger than the benefits. In the example calculations, the costs can increase more than marginally without making AVs unprofitable to society, as presented in
The results show that nearly all benefits will come to consumers and producers of the goods. Thus, an important policy conclusion is that there is no reason for giving subsidies to the industry producing AVs or to the consumers buying them. The market mechanisms will lead to the introduction of AVs without subsidies if it is profitable. The sole external effect in this study is part of a possible future reduction in accidents compared to MDVs, but this effect is relatively small in Sweden. However, it is important to adjust regulations so that the new technology can be implemented if safety is satisfactory.
In addition to the contribution from this study, the value of new groups being able to ride a car, the perceived safety, privacy, changed congestion and change in land use are factors that remain to be analysed.
The authors declare no conflicts of interest regarding the publication of this paper.
Andersson, P. and Ivehammar, P. (2019) Benefits and Costs of Autonomous Trucks and Cars. Journal of Transportation Technologies, 9, 121-145. https://doi.org/10.4236/jtts.2019.92008